Note: Descriptions are shown in the official language in which they were submitted.
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TITLE
GEOTHERMAL HEAT PUMP DESIGN SIMULATION AND ANALYSIS
INVENTOR
Dennis J. Koop
BACKGROUND
[0001]This section is intended to introduce the reader to aspects of art that
may be related to
various aspects of the present disclosure described herein, which are
described and/or
claimed below. This discussion is believed to be helpful in providing the
reader with
background information to facilitate a better understanding of the various
aspects of the
present disclosure described herein. Accordingly, it should be understood that
these
statements are to be read in this light, and not as admissions of prior art.
[0002]A geothermal heat pump or ground source heat pump (GHP) is a central
heating and/or
cooling system that transfers heat to or from the ground. The traditional heat
and cooling
equipment delivered from the manufacture uses air for cooling and heating
operations. GHP
systems can use the earth as a heat source in cold winter climates or as a
heat sink in warm
summer climates. This design takes advantage of the moderate temperatures in
the ground to
boost efficiency and reduce the operational costs of heating and cooling
systems, and may be
combined with HVAC systems and energy conservation systems. GHPs employ a heat
exchanger in contact with the ground or groundwater to extract or dissipate
heat. This
component accounts for anywhere from a fifth to half of the total system cost,
and would be
the most cumbersome part to repair or replace. In conventional GHP systems,
the heat
exchanger unit is in fluid communication with a loop of tubing buried in the
ground, commonly
referred to as a ground loop. A variety of ground loop configurations can be
used
with geothermal heat pump systems. For "closed-loop" configurations, in which
the
ground loop provides a closed circuit for the circulating heat exchange fluid,
two known
configurations are commonly employed, namely horizontal closed-loop and
vertical closed-
loop configurations. In the horizontal closed-loop configuration, the ground
loop is typically laid
horizontally, or in a directionally drilled borehole, in a shallow trench dug
into the ground
adjacent to a building structure that is to be serviced by the geothermal heat
pump system. In
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the vertical closed-loop configuration, the ground loop is typically placed in
a 100 foot to 400
foot deep borehole formed in the ground adjacent to the building structure to
be serviced by
the GHP system. The heat exchanger unit must specifically be designed for the
specific
location and application. Correctly sizing the heat exchanger and loop
configuration and
design is necessary to assure long-term performance and energy efficiency of
the whole
system.
[0003]Even though geothermal heat pump equipment is know to be very energy
efficient, sales
in the United State have been limited to generally about 1.5% of the heating
and cooling
industry. One of the main causes for limited sales is the lack of
knowledgeable people in the
industry that know how to accurately design the in-ground heat exchanger
required. Designing
geothermal heat pump equipment for residential, commercial, and institutional
buildings can be
very complex especially for models that have a very high level of detail. GHP
designers can
easily be overwhelmed with the amount of information and variables for
designing such GHP
systems without the help of computer based design analysis and simulations.
[0004]Currently, there are many types of software programs that exist for in-
ground vertical or
horizontal loop geothermal heat pump design and simulation. However, these
programs are
largely ineffective, typically designed for residential applications (not
commercial), provide a
complex user interface, have limited or no internet/web based accessibility or
connectivity,
have slow computational speeds, require other third party front-end software
for various
calculations, and do not have up to date or real time data of geographical,
weather, climate,
soil, rock data, do not allow detailed parameters and multiple zones of a
building design to be
set (i.e. schedule/time for multiple building zones), do not allow for hybrid
designs and
comparisons (i.e. adding/removing cooling towers), do not provide accurate
results that allow a
designer to be confident in implementing the data in a real-world application,
and the
programs themselves are costly to develop, operate, distribute, and be adopted
by commercial
designers.
[0005]Hence, what is needed is a simple to use web-based geothermal heat pump
design,
simulation, and analysis program that can be accessed by users using any type
of mobile or
computing device, provides a simple to use interface, allows the user to run
multiple design
and analysis simulations, select from multiple heat pump manufacturers,
automatically
populate and gather geographical, building, and hourly weather data in real-
time, allow the
user to set exact and specific building parameters (such as a buildings
schedule/operational
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hours for each zone within a building), automatically correct raw heat pump
data into actual
heat pump performance, and further provide actual cost basis, hybrid designs,
operating
costs, benchmark, and efficiency comparisons.
BRIEF SUMMARY
[0006]In one aspect of the disclosure described herein, an in-ground GHP
design program
(referred to hereinafter as "GHP application" or "GHP program") is provided
for designing,
analyzing, and simulating a model of a detailed building energy analysis,
using an in-ground
geothermal heat pump system. In one aspect of the disclosure described herein,
the GHP
design program can reliably and efficiently predict the fluctuations of the
GHP equipment
performance in small increments. This enables the determination of energy
consumption and
demand information on a specific and unique hourly schedule basis. More
specifically, the
small increment method here can be used to eliminate overly broad
approximations by
evaluating GHP performance that is specific to building dynamics, constants,
and variables for
all of the building individual zones and the building's hourly operating
schedule.
[0007]In addition to building energy analysis and geothermal design
applications, the small
increment method of the disclosure described herein can be used for hybrid GHP
systems,
such as in combination with cooling towers. More specifically, in scenarios
where cooling loads
are very dominant, supplemental heat rejecters such as cooling towers can be
used. Further,
various operating strategies and conditions can be utilized in hybrid systems
with the GHP
design program of the disclosure described herein. For example, in order to
reduce heat build-
up in the ground, the GHP system can be simulated, modeled, and programmed to
run during
the winter, or consider running at night during the summer. In order to
quantify the impact of
various operating strategies on the in-ground heat exchanger size and
operating costs, it is
advantageous to utilize the GHP program of disclosure described herein for a
GHP design
model is advantageous since it can account for the hourly operating schedule
and interaction
between the in-ground heat exchanger and heat rejecter. For example, by
modeling and
simulating the use of supplemental heat rejecters (i.e. cooling towers) for
cooling in building
systems allows for a GHP design having smaller borehole fields, and thus
reducing overall
installation and operating costs, both in the near term and long term. Here,
earth thermal
degradation can be avoided by offsetting the annual load imbalance in the
borehole field and
the resulting long-term temperature rise.
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[0008]In another aspect of the disclosure described herein, a method of
simulating a ground
geothermal heat pump design is provided. The method can include receiving
location data,
wherein the location data further includes climate data, receiving an
operating schedule data
for a building, receiving heating or cooling load condition data for the
building, and calculating
and determining the building's ground geothermal heat pump design borehole
requirement,
heat pump requirement, and a loop field configuration based on the location
data, heating or
cooling load condition data, and operating schedule data. The method can
further include
calculating and determining the building's electric operating cost based on
the location data,
heating or cooling load conditions data, and operating schedule data. Here,
the building
operating schedule data is comprised of operating hours for the building in a
given year. In
addition, the climate condition data can include temperature data for each
hour of the year
based on the location data or for a specified location. The method can further
include receiving
borehole data, wherein the borehole data can include one or more of:
undisturbed earth
temperature data, ground conductivity, ground diffusivity, grout conductivity,
borehole
diameter, pipe material, pipe diameter, and pipe configuration in the
borehole.
[0009]The method can further include receiving zone data for one or more zones
within the
building. Here, the zone data can include one or more of: heat pump data,
internal heat gain
data, and maximum heating or cooling thermal loads. Here, the heat pump data
can include
one or more of: heat pump type, heat pump model, heat pump series, heat pump
power, and
heat pump capacity. The method can further include receiving an inlet water
temperature data
for the heat pump. In addition, the method can also include determining a
hybrid design,
wherein the hybrid design integrates with the ground geothermal heat pump
design one or
more of: a cooling tower, fluid cooler, chiller, boiler, furnace, hot water
heater, and a secondary
ground loop. The method can further include receiving heat pump model data and
retrieving
manufacturer performance data based on the heat pump model data, and
standardizing
performance data based on one or more of: the operating schedule data, an
entering water
temperature data, flow rate data, capacity data, power data, air temperature
data, and air flow
data. Here, the standardizing can be based on one or more iterations of the
performance data.
The method can also include determining the capacity of the heat pump based on
the
standardized heat pump performance data, and also simulating or modeling a
benchmark
comparison of another geothermal heat pump system having different heat pump
data. The
method can also include receiving internal heat gain data for the building,
wherein the heat
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gain data can include heat generated from one or more of: lighting, persons,
occupancy,
appliances, electronics, heat dissipating devices, windows, and building type.
[00010]In another aspect of the disclosure described herein, a method of
simulating a ground
geothermal design is provided. Here, the method can include receiving location
data, wherein
the location data further comprises temperature data, receiving an operating
schedule data for
a building, associating or mapping the operating schedule data with the
temperature data,
receiving earth condition data, receiving maximum heating or cooling load
condition data for
the building, receiving internal heat gain data for the building, receiving a
first heat pump data,
wherein the first heat pump data includes inlet water temperature, receiving a
second heat
pump data, wherein the second heat pump data includes manufacturer heat pump
performance technical data having heat pump flow rate, capacity, and power.
The method
further includes determining a third heat pump data, wherein the third heat
pump data is at
least partially based on iterating the first heat pump data with respect to
the second heat pump
data, wherein the third heat pump data includes calculated heat pump capacity
and power.
The method further includes calculating and modeling borehole length, total
building load, and
ground loop configuration for the ground geothermal design based on the
location data,
temperature data, operating schedule data, earth condition data, heating or
cooling load
condition data, heat gain data, and heat pump data.
[00011]In another aspect of the disclosure described herein, a computer
program product
embodied on a non-transitory computer readable medium for simulating an in-
ground
geothermal heat pump design is provided, wherein the computer program is
implemented by
one or more processors executing processor instructions, the computer program
product
including a first computer code for receiving location data, wherein the
location data further
comprises climate data, a second computer code for receiving an operating
schedule data for
a building, a third computer code for receiving heating or cooling load
condition data for the
building, and a fourth computer code for calculating and determining the
building's ground
geothermal heat pump design borehole requirement, heat pump requirement, and a
loop field
configuration based on the location data, heating or cooling load condition
data, and operating
schedule data.
[00012]In another aspect of the disclosure described herein, a method of
simulating a ground
geothermal heat pump design is disclosed. The method can include receiving a
geographical
location, receiving temperature data based on the the geographical location,
wherein the
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temperature data comprises a plurality of ambient temperature values for each
of the 8760
hours in a year, receiving a building type, and receiving an operating
schedule for the building
type, wherein the operating schedule is comprised of operating hours for the
building type for
one or more days in a week. The method can further include receiving one or
more zones for
the building type, receiving one or more internal heat conditions for each of
the one or more
zones, receiving a block heating or cooling load condition for each of the one
or more zones. In
addition, the method can include determining a plurality of zone load
conditions for each of the
one or more zones from the block heating or cooling load condition, wherein
the plurality of
zone load conditions are determined for each of the ambient temperature values
based on the
operating hours in the operating schedule, applying the internal heat
conditions to the plurality
of zone load conditions, and determining a capacity type operation for a
geothermal heat
pump for each of the one or more zones based on the plurality of zone load
conditions and the
applied internal heat conditions for each of the ambient temperature values
based on the
operating hours in the operating schedule. Here, the capacity type operation
for the geothermal
heat pump can be further comprised of at least one of a single, dual, or
variable capacity heat
pump. In addition, the method can include determining an amount of heat
transfer into or out
of the ground, a temperature ground effect, the building's ground geothermal
borehole
requirement and a ground loop field configuration.
[00013]In another aspect of the disclosure described herein, a method of
simulating a ground
geothermal heat pump system is disclosed. The method can include receiving a
geographical
location, receiving temperature data based on the geographical location,
wherein the
temperature data comprises a plurality of ambient temperature values for each
of the 8760
hours in a year, receiving a building type; receiving an operating schedule
for the building type,
wherein the operating schedule is comprised of operating hours for the
building type for one or
more days in a week. The method can also include receiving one or more zones
for the
building type, receiving a geothermal heat pump system type for the one or
more zones,
receiving an amount to be directed to a supplemental cooling or heating
component, receiving
one or more internal heat conditions for each of the one or more zones, and
receiving a block
heating or cooling load condition for each of the one or more zones. In
addition, the method
can include determining a plurality of zone load conditions for each of the
one or more zones
from the block heating or cooling load condition, wherein the plurality of
zone load conditions
are determined for each of the ambient temperature values based on the
operating hours in the
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operating schedule, and applying the internal heat conditions to the plurality
of zone load
conditions. Further, the method can include determining an event wherein the
plurality of zone
load conditions for each of the ambient temperature values based on the
operating hours in
the operating schedule are at least partially split between the geothermal
heat pump system
and the supplemental cooling or heating component, wherein the event is
further based on the
received amount to be directed to the supplemental cooling or heating
component, and
determining a first operation capacity for the geothermal heat pump system and
a second
operation capacity for the supplemental heating or cooling component.
[00014]The method can further include wherein the event is comprised of a
calculated or pre-
defined entering water temperature to the geothermal heat pump system. In
addition, the event
can be comprised of a calculated or pre-defined amount of heat transfer to the
geothermal
heat pump system. Further, the first operation capacity for the geothermal
heat pump system
comprises at least one of: a borehole length, number of boreholes, pipe
length, or heat pump
power capacity. The second operation capacity for the supplemental heating or
cooling
equipment can comprise at least one of: one or more of hours of operation for
the cooling or
heating units, or power capacity for the cooling or heating units. The method
can also include
determining a borehole requirement, wherein the borehole requirement is
comprised of the
number of boreholes and length per borehole. In addition, the method can
include
automatically adjusting the borehole requirement based on the amount to be
directed to a
supplemental cooling or heating component. Here, the supplemental heating or
cooling
component is comprised of one or more of: a cooling tower, fluid cooler,
chiller, boiler, furnace,
hot water heater, and secondary ground loop.
[00015]In another aspect of the disclosure described herein, a method of
simulating a hybrid
ground geothermal heat pump system is disclosed. Here, the method can include
receiving a
geographical location, receiving temperature data based on the geographical
location, wherein
the temperature data comprises a plurality of ambient temperature values for
each of the 8760
hours in a year, receiving a building type, receiving an operating schedule
for the building type,
wherein the operating schedule is comprised of operating hours for the
building type for one or
more days in a week, and receiving one or more zones for the building type.
The method can
further include receiving a geothermal heat pump system type for the one or
more zones,
receiving an amount to be directed to a cooling or heating component comprised
of at least of
one of: a cooling tower, fluid cooler, chiller, boiler, furnace, hot water
heater, or secondary
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ground loop. In addition, the method can also include receiving one or more
internal heat
conditions for each of the one or more zones, receiving a block heating or
cooling load
condition for each of the one or more zones, determining a plurality of zone
load conditions for
each of the one or more zones from the block heating or cooling load
condition, wherein the
plurality of zone load conditions are determined for each of the ambient
temperature values
based on the operating hours in the operating schedule. Further, the method
can include
applying the internal heat conditions to the plurality of zone load
conditions, and determining a
condition wherein the plurality of zone load conditions for each of the
ambient temperature
values based on the operating hours in the operating schedule are at least
partially split
between the geothermal heat pump system and the cooling or heating component,
wherein the
condition is further based on the received amount to be directed to the
supplemental cooling
or heating component. Also, the method can include determining a first
operation capacity for
the geothermal heat pump system and a second operation capacity for the
heating or cooling
component.
[00016]The method can further include wherein the condition can be comprised
of a calculated
or pre-defined entering water temperature to the geothermal heat pump system.
In addition,
the condition can be comprised of a calculated or pre-defined amount of heat
transfer to the
geothermal heat pump system. Here, the first operation capacity for the
geothermal heat pump
system comprises at least one of: a borehole length, number of boreholes, pipe
length, or heat
pump power capacity. Further, the second operation capacity for the
supplemental heating or
cooling equipment comprises at least one of: one or more of hours of operation
for the cooling
or heating units, or power capacity for the cooling or heating units. The
method can further
include determining a borehole requirement, wherein the borehole requirement
is comprised of
the number of boreholes and length per borehole. In addition, the method can
include
automatically adjusting the borehole requirement based on the amount to be
directed to a
supplemental cooling or heating component.
[00017]In another aspect of the disclosure described herein, a method of
simulating a ground
geothermal heat pump design is disclosed. Here, the method can include
receiving a first array
having a plurality of temperature data values each assigned to plurality of
keys, receiving a
second array having a plurality of heat pump data values each assigned to a
plurality of keys,
determining the last key in the first array having the highest temperature
data value; receiving a
first temperature input variable, defining a first variable to be the first
temperature input
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variable, and determining if the first variable or the first temperature input
variable is greater
than or equal to the last key from the first array. The method can further
include re-defining the
first variable, wherein the re-defined first variable is the number one
subtracted from the last
key from the first array, subtracting the re-defined first variable from the
last key in the first
array and determining if the result is greater than or equal to zero,
assigning a second variable
with a key to a value from the second array having the same key, assigning a
third variable with
a key to a value from first array having the same key, assigning a fourth
variable to a last value
from the second array, and assigning a fifth variable to the last key from the
first array. The
method can further include interpolating or extrapolating the received first
temperature input
variable, the assigned second variable, the assigned third variable, the
assigned fourth
variable, and the assigned fifth variable to calculate a sixth variable.
[00018]The method can also include executing a loop operation, wherein the
loop operation is
comprised of re-assigning the last key from the first array with the highest
temperature value
that resulted in subtracting the re-defined first variable from the re-
assigned last key not being
greater than or equal to zero. In addition, the loop operation can further
comprise assigning a
last value from the second array with the highest heat pump value that
resulted in subtracting
the re-defined first variable from the re-assigned last key not being greater
than or equal to
zero. Here, the plurality of temperature data values in the first array are
comprised of entering
water temperatures. Further, the plurality of heat pump data values in the
second array are
comprised of heat pump capacity. In addition, the plurality of heat pump data
values in the
second array are comprised of heat pump power.
[00019]In another aspect of the disclosure described herein, a method of
simulating a ground
geothermal heat pump design is disclosed. Here, the method can include
receiving a first array
having a plurality of temperature data values each assigned to plurality of
keys, receiving a
second array having a plurality of heat pump data values each assigned to a
plurality of keys,
determining the last key in the first array having the highest temperature
data value, and
receiving a first temperature input variable. The method can further include
defining a first
variable to be the first temperature input variable, determining if the first
variable or the first
temperature input variable is greater than or equal to the last key from the
first array,
determining if the first temperature input variable is less than or equal to
the value assigned to
the starting key in the first array, and subtracting the first variable from
the last key in the first
array and determining if the result is greater than or equal to zero. The
method can further
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include assigning a second variable with a key to a value from the second
array having the
same key, assigning a third variable with a key to a value from first array
having the same key,
assigning a fourth variable to a value from the second array, assigning a
fifth variable to a value
from the first array, and interpolating or extrapolating the received first
temperature input
variable, the assigned second variable, the assigned third variable, the
assigned fourth
variable, and the assigned fifth variable to calculate a sixth variable.
[00020]The method can further include executing a loop operation, wherein the
loop operation
is comprised of re-assigning the last key from the first array with the
highest temperature value
that resulted in subtracting the first variable from the re-assigned last key
not being greater
than or equal to zero. In addition, the loop operation can further comprise
assigning a last
value from the second array with the highest heat pump value that resulted in
subtracting the
first variable from the re-assigned last key not being greater than or equal
to zero. Here, the
plurality of temperature data values in the first array are comprised of
entering water
temperatures, and the plurality of heat pump data values in the second array
can be comprised
of heat pump capacity. In addition, the plurality of heat pump data values in
the second array
can be comprised of heat pump power.
[000211In another aspect of the disclosure described herein, a method of
simulating a ground
geothermal heat pump design is disclosed. The method can include receiving a
first array
having a plurality of temperature data values each assigned to plurality of
keys, receiving a
second array having a plurality of heat pump data values each assigned to a
plurality of keys,
determining the last key in the first array having the highest temperature
data value, receiving a
first temperature input variable, defining a first variable to be the first
temperature input
variable, determining if the first variable or the first temperature input
variable is greater than or
equal to the last key from the first array, determining if the first
temperature input variable is
less than or equal to the value assigned to the starting in the first array,
and re-defining the first
variable, wherein the re-defined first variable is the number one added to the
starting key from
the first array. The can also include subtracting the re-defined first
variable from the last key in
the first array and determining if the result is greater than or equal to
zero, executing a loop
operation, wherein the loop operation is comprised of re-assigning the last
key from the first
array with the highest temperature value that resulted in subtracting the re-
defined first variable
from the re-assigned last key not being greater than or equal to zero,
assigning a second
variable with a key to a value from the second array having the same key,
assigning a third
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variable with a key to a value from first array having the same key, assigning
a fourth variable
to a value from the second array, assigning a fifth variable to the re-
assigned last key value
from the first array, and interpolating or extrapolating the received first
temperature input
variable, the assigned second variable, the assigned third variable, the
assigned fourth
variable, and the assigned fifth variable to calculate a sixth variable.
[00022]The method can further include wherein the loop operation can further
comprise
assigning a last value from the second array with the highest heat pump data
value that
resulted in subtracting the re-defined first variable from the re-assigned
last key not being
greater than or equal to zero. In addition, the plurality of temperature data
values in the first
array are comprised of entering water temperatures, and the plurality of heat
pump data values
in the second array are comprised of heat pump capacity. The the plurality of
heat pump data
values in the second array can be comprised of heat pump power.
[00023]The above summary is not intended to describe each and every disclosed
embodiment
or every implementation of the disclosure. The Description that follows more
particularly
exemplifies the various illustrative embodiments.
BRIEF DESCRIPTION OF THE DRAWINGS
[00024]The following description should be read with reference to the
drawings, in which like
elements in different drawings are numbered in like fashion. The drawings,
which are not
necessarily to scale, depict selected embodiments and are not intended to
limit the scope of
the disclosure. The disclosure may be more completely understood in
consideration of the
following detailed description of various embodiments in connection with the
accompanying
drawings, in which:
[00025]FIG. 1A illustrates one non-limiting embodiment of a general network
architecture
system for the GHP application.
[00026]FIG. 1 illustrates one non-limiting embodiment of a flow chart diagram
illustrating a
process for simulating and modeling within the GHP application.
[00027]FIG. 2 illustrates a more detailed flow chart diagram of the embodiment
of FIG. 1,
further illustrating the transmitting to and/or reading of received data from
various databases
and to and from building zone module 2160.
[00028]FIG. 3 illustrates a more detailed flow chart diagram of FIG. 1,
further illustrating the
process for processing and calculating borehole resistance at step 2152.
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[00029]FIG. 4 illustrates a more detailed flow chart diagram of FIG. 1,
further illustrating the
process for processing and calculating ground resistance at step 2154.
[00030]FIG. 5 illustrates a more detailed flow chart diagram of FIG. 1,
further illustrating the
process for inputting the building cooling and heating loads for each zone at
step 2180.
[000311FIG. 5A illustrates a more detailed flow chart diagram of FIG. 5,
further illustrating one
non-limiting embodiment for processing, standardizing, and correcting
individual zone heat
pump performance data for a GHP design.
[00032]FIG. 5B further illustrates the embodiments of FIG. 5 and 5A flow chart
for processing
individual zone heat pump performance for maximum building zone thermal loads
and
standardizing the flow rate.
[00033]FIG. 6 illustrates a more detailed flow chart diagram of FIG. 1,
further illustrating the
process for calculating heat pump capacity and demand data at step 2178.
[00034]FIG. 6A illustrates one non-limiting embodiment of a flow chart for
processing,
standardizing, and correcting individual zone heat pump performance data in
each step for the
building zone thermal loads, further based on FIG. 6.
[00035]FIG. 7 illustrates a more detailed flow chart diagram of FIG. 1,
further illustrating the
process for calculating the zone monthly operating rate and process the
building hourly
operating schedule.
[00036]FIG. 8 illustrates a flow chart diagram continuation of FIG. 7, further
illustrating the
process for calculating the zone operation cost and BTUs transferred to and
from the ground.
[00037]FIG. 9 illustrates one non-limiting embodiment and example scenario for
calculated and
simulated cooling operating costs for one zone, incorporating the operating
hours scheduled
within each discreet temperature increment for the building in a given year.
[000381FIG. 9A illustrates one non-limiting embodiment and example scenario
for calculated
and simulated heating operating costs for one zone, incorporating the
operating hours
scheduled within each discreet temperature increment for the building in a
given year.
[00039]FIG. 10 illustrates one non-limiting embodiment and example scenario
for calculated
and simulated cooling operating costs for one zone for a GHP benchmark having
no hybrid
design, incorporating the hourly operating schedule within each discreet
temperature
increment for the building in a given year.
[00040]FIG. 11 illustrates one non-limiting embodiment and example scenario of
a chart for
calculated and simulated cooling operating costs for one zone for GHP design
having a 20%
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hybrid design, incorporating the number of hours spent within each discreet
temperature
increment for the building in a given year.
[00041]FIG. 12 further illustrates a flow chart diagram of the process for
calculating the total
building's monthly operating rate and process the building's hourly operating
schedule for
each iteration step.
[00042]FIG. 13 illustrates one non-limiting embodiment and example scenario
for calculated
and simulated cooling total building energy requirements (BTUs) for a GHP
design having no
hybrid design, incorporating the hourly operating schedule within each
discreet temperature
increment for the building in a given month and in a given year.
[00043]FIGS. 14 and 15 illustrate one non-limiting embodiment of detailed flow
charts for
processing and calculating the GHP design simulation and modeling.
[00044]FIG. 16 illustrates one non-limiting embodiment of a detailed flow
chart for processing
and calculating a GHP benchmark simulation and modeling.
[00045]FIG. 17 illustrates a detailed flow chart for one non-limiting
embodiment for processing
and calculating EER and COP data and one non-limiting embodiment for
calculating and
modeling a GHP hybrid design.
[00046]FIG. 18 illustrates one non-limiting embodiment for a user interface
device display
screen 12 of detailed simulation and model for a GHP design for both cooling
and heating
having no hybrid design and including GHP benchmark data.
[00047]FIG. 19 illustrates one non-limiting embodiment for a user interface
device display
screen 12a and user device screen 14a of detailed simulation and model for a
GHP design for
both cooling and heating and having a GHP hybrid design.
[00048]FIG. 20 illustrates one non-limiting embodiment of a flow chart for a
process of
extracting array elements and processing universal interpolation and
extrapolation data.
[00049]FIG. 20A illustrates one example scenario flow chart and non-limiting
embodiment for
the interpolation, iteration, or extrapolation method of FIG. 20.
[00050]FIG. 20B illustrates another example scenario flowchart and non-
limiting embodiment
for the interpolation, iteration, or extrapolation method of FIG. 20.
[00051]FIG. 20C illustrates another example scenario flowchart and non-
limiting embodiment
for the interpolation, iteration, or extrapolation method of FIG. 20.
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[00052]FIG. 21 illustrates one non-limiting embodiment of a user interface
device display
screen 1, another non-limiting embodiment of user interface device display
screen la, and one
non-limiting embodiment of sample data within a Table 1.
[00053]FIG. 22 illustrates one non-limiting embodiment of a user interface
device display
screen 2, one non-limiting embodiment of a user interface device display
screen 3, and one
non-limiting embodiment of sample data within a Table 2.
[00054]FIG. 23 illustrates one embodiment of non-limiting sample data within
Table 3, and one
embodiment of non-limiting sample data within a Table 4.
[00055]FIG. 24 illustrates one non-limiting embodiment of a user interface
device display
screen 4, and one non-limiting embodiment of sample data within a Table 5.
[00056]FIG. 25 illustrates one non-limiting embodiment of a user interface
device display
screen 5, and one non-limiting embodiment of sample data within a Table 6.
[00057]FIG. 26 illustrates one embodiment of non-limiting sample data within a
Table 7, one
embodiment of non-limiting sample data within a Table 8, and one non-limiting
embodiment of
sample data within a Table 9.
[00058]FIG. 27 illustrates one non-limiting embodiment of a user interface
device display
screen 6, and one non-limiting embodiment of sample data within a Table 10.
[00059]FIG. 28 illustrates one non-limiting embodiment of a user interface
device display
screen 7, and one non-limiting embodiment of sample data within a Table 11.
[00060]FIG. 29 illustrates one non-limiting embodiment of a user interface
device display
screen 8, and one non-limiting embodiment of a user interface display screen
9.
[00061]FIG. 30 illustrates one non-limiting embodiment of a user interface
device display
screen 10, one non-limiting embodiment of sample data within a Table 12, and
one non-
limiting embodiment of sample data within a Table 13.
[00062]FIG. 31 illustrates one non-limiting embodiment of sample data within a
Table 14, and
one non-limiting embodiment of sample data within a Table 15.
[00063]FIG. 32 illustrates one non-limiting embodiment of sample data within a
Table 16, and
one non-limiting embodiment of sample data within a Table 17.
[00064]FIG. 33 illustrates one non-limiting embodiment of a user interface
device display
screen 11, and one non-limiting embodiment of sample data within a Table 18.
[00065]FIG. 34 illustrates one non-limiting embodiment of sample data within a
Table 19.
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[00066]FIG. 35 illustrates one non-limiting embodiment of the user interface
device display
screen 12 without populated data.
[000671FIG. 36 illustrates one non-limiting embodiment of the user interface
device display
screen 12a without populated data.
[00068]FIG. 37 illustrates one non-limiting embodiment of a user interface
device display
screen 13, and one non-limiting embodiment of sample data within a Table 20.
[00069]FIG. 38 illustrates one non-limiting embodiment of a user interface
device display
screen 14, and one non-limiting embodiment of sample data within a Table 21.
DETAILED DESCRIPTION
[00070]In the Brief Summary of the present disclosure above and in the
Detailed Description of
the Disclosure described herein, and the claims below, and in the accompanying
drawings,
reference is made to particular features (including method steps) of the
disclosure described
herein. It is to be understood that the disclosure of the disclosure described
herein in this
specification includes all possible combinations of such particular features.
For example,
where a particular feature is disclosed in the context of a particular aspect
or embodiment of
the disclosure described herein, or a particular claim, that feature can also
be used, to the
extent possible, in combination with and/or in the context of other particular
aspects and
embodiments of the disclosure described herein, and in the disclosure
described herein
generally. Further, it is contemplated within the scope of the disclosure
described herein that
certain processes, methods, and steps described herein may be performed in any
order and
may include all steps, some steps, or omit others.
[00071]The embodiments set forth below represent the necessary information to
enable those
skilled in the art to practice the disclosure described herein and illustrate
the best mode of
practicing the disclosure described herein. In addition, the disclosure
described herein does
not require that all the advantageous features and all the advantages need to
be incorporated
into every embodiment of the disclosure described herein.
[00072]Video displays may include devices upon which information may be
displayed in a
manner perceptible to a user, such as, for example, a computer monitor,
cathode ray tube,
liquid crystal display, light emitting diode display, touchpad or touch-screen
display, and/or
other means known in the art for emitting a visually perceptible output. Video
displays may be
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electronically connected to a mobile device according to hardware and software
known in the
art.
[00073]In one implementation of the disclosure described herein, a display
page may include
information residing in the mobile device's memory, which may be transmitted
from the mobile
device over a network to a central center and vice versa. The information may
be stored in
memory at each of the mobile device, a data storage resided at the edge of the
network, or on
the servers at the central center. A server, computing device, or mobile
device may receive
non-transitory computer readable media, which may contain instructions, logic,
data, or code
that may be stored in persistent or temporary memory of the mobile device, or
may somehow
affect or initiate action by a mobile device. Similarly, one or more servers
may communicate
with one or more mobile devices across a network, and may transmit computer
files residing in
memory. The network, for example, can include the Internet, wireless
communication network,
or any other network for connecting one or more mobile devices to one or more
servers.
[00074]Any discussion of a server, computing, or mobile device may also apply
to any type of
networked device, including but not limited to phones such as cellular phones
(e.g., an
iPhone0, Android , Blackberry , or any 'smart phone'), a personal computer,
iPadO, server
computer, or laptop computer; personal digital assistants (PDAs) such as a
Palm-based device
or Windows CE device; a roaming device, such as a network-connected roaming
device; a
wireless device such as a wireless email device or other device capable of
communicating
wireless with a computer network; or any other type of network device that may
communicate
over a network and handle electronic transactions. Any discussion of any
mobile device
mentioned may also apply to other devices for operating, processing, using, or
executing the
GHP application.
[00075]On a server, computing, or mobile device, the display page may be
interpreted by
software residing on a memory of the device, causing the computer file to be
displayed on a
video display in a manner perceivable by a user. The display pages described
herein may be
created using a software language known in the art such as, for example, the
hypertext mark
up language ("HTML"), the dynamic hypertext mark up language ("DHTML"), the
extensible
hypertext mark up language ("XHTML"), the extensible mark up language ("XML"),
Java,
C/C#/C++, or another software language that may be used to create a computer
file
displayable on a video display in a manner perceivable by a user. Any computer
readable
media with logic, code, data, instructions, may be used to implement any
software or process
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flow or steps or methodology. Where a network comprises the Internet, a
display page may
comprise a webpage of a type known in the art. Further, the computing device
can operate
with or work in conjunction with any content management software (CMS) or
customer
relations software (CRM) which can include but not limited to WordPress, any
Java based
software, Microsoft ASP.NET software, Perl based software, PHP based software,
Python
based software, Ruby on Rails based software, ColdFusion Markup Language
(CFML), or other
Software as a Service (SaaS) based software.
[00076]A display page according to the disclosure described herein may include
embedded
functions comprising software programs stored on a memory, for example, Cocoa,
VBScript
routines, JScript routines, JavaScript routines, Java applets, ActiveX
components, ASP.NET,
AJAX, PHP, Flash applets, Silverlight applets, or AIR routines. A display page
may comprise
well-known features of graphical user interface technology, for example,
frames, windows,
tabs, scroll bars, buttons, icons, menus, fields, and hyperlinks, and well-
known features such
as a touchscreen interface. Pointing to and touching on a graphical user
interface button, link,
icon, menu option, or hyperlink also is known as "selecting" the button, link,
icon, option, or
hyperlink. Additionally, a "point and gesture" interface may be utilized, such
as a hand-gesture
driven interface. Any other interface for interacting with a graphical user
interface may be
utilized, such as haptic feedback interfaces. A display page according to the
disclosure
described herein also may incorporate multimedia features.
[00077]Phrases and terms similar to "software", "application", and "firmware"
may include any
non-transitory computer readable medium storing thereon a program or
algorithm, which when
executed by a computer, causes the computer to perform a method, process, or
function.
[00078]Phrases and terms similar "network" may include one or more data links
that enable
the transport of electronic data between computer systems and/or modules. When
information
is transferred or provided over a network or another communications connection
(either
hardwired, wireless, or a combination of hardwired or wireless) to a computer,
the computer
uses that connection as a computer-readable medium. Thus, by way of example,
and not
limitation, computer-readable media can also comprise a network or data links
which can be
used to carry or store desired program code means in the form of computer-
executable
instructions or data structures and which can be accessed by a general purpose
or special
purpose computer.
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[00079]Phrases and terms similar to "portal" may include an intranet page,
internet page,
locally residing software or application, or digital presentation for a user
of the present
disclosure described herein. The portal may also be any graphical user
interface for accessing
various modules, features, options, and/or attributes of the present
disclosure described
herein. For example, the portal can be a web page accessed with a web browser,
mobile
device application, or any application or software residing on a computing
device.
[00080]FIG. 1A illustrates an overview diagram of one non-limiting embodiment
of the in-
ground GHP design program (referred to hereinafter as "GHP application" or
"GHP program")
of the disclosure described herein for designing, analyzing, modeling, and
simulating an in-
ground GHP system, including a ground loop design and simulation. The GHP
application
system can include one or more central servers 100 or computing devices in bi-
directional
communication with one or more administrator 110, data source 120, user
terminal 130, user
terminal 140, and user terminal 150. Here, in one embodiment, central server
100 can have the
GHP application residing thereon, wherein any users of users 130-150 can
access and interact
with from their computing device via a network, using one or more portals
(such as a web
browser). Here, terminals 130-150 can have various access levels, privileges,
and
functionalities within the GHP application, and can also share data among each
other or with
server 100. It is contemplated within the scope of the disclosure described
herein that there
may be any number of terminals or clients having various access privileges and
functionalities
within GHP application network. Administrator 110 can have various access
functionalities to
the GHP application residing on server 100, for example, modifying various
parameters and
settings of the GHP application and adding/deleting/editing users of the GHP
application.
Server 100 can further communicate with one or more data sources, such as data
source 120,
for either download/uploading third party data from one or more servers. For
example, this
data can include but is not limited to: geographic data, climate data, weather
data,
environmental data, building data, location data, heat pump performance data,
heat pump
technical data, statistical data, ground data, soil data, piping data, HVAC
data, HVAC device
data, HVAC component data, efficiency data, tool data, heat pump/exchanger
data,
manufacturer data, and geothermal design data, among others.
[00081]FIG. 1 illustrates a general overview of a flowchart for one embodiment
of the GHP
application. For example, at step 2000, a user can visit a portal for the GHP
application and be
prompted to login or register with the GHP application network. If the user is
not yet a
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registered user, then they can create a user profile having a username and
password. Once
registered, the user can enter their username and password for authentication
with the GHP
application. If authentication is successful at step 2020, then the process
can proceed to step
2040. At step 2040, the user can select one or more geographical or location
data for a
building design site. Here, the location data can be retrieved from anywhere
in the world, or
any map data available on Google or online mapping or geographical service
and the data
can be retrieved from, read from, saved to, or written to database 2042. Here,
this
geographical or location data can include weather data, temperature data,
temperature profile
data, climate data, environmental data, soil data, borehole data, ground
condition, earth
related data, and statistical data, among others. It is contemplated within
the scope of the
disclosure described herein that the GHP application can retrieve this from a
database which
can be residing locally on a server or retrieve this data from third party
source either in real-
time or previously downloaded at another time. Once geographical data from
step 2040 has
been received, then the process can proceed to step 2060. At step 2060, the
user can be
prompted to either manually input or select one or more types of buildings
that the user will be
designing. For example, these can include commercial, residential, house,
office, retail, school,
warehouse, high-rise, mid-rise, condominium, single family home, townhome,
building
capacity, building dimensions, building size, among others. The user also has
the option to go
back to step 2040 to make any changes. Once a building type data is received,
then the
process can then proceed to step 2080.
[00082]At step 2080, the user can be prompted to manually input or select
operating schedule
data for the building, which can be retrieved from, read from, written to, or
saved to database
2082. For example, the operating schedule data can include but is not limited
to operating
months/days/hours/minutes, open business months/days/hours/minutes, closed
months/days/hours/minutes, peak or off peak months/days/hours/minutes. In
addition, the
schedule data can be provided in database of the GHP application or retrieved
via network
from one or more remote sources. Once the operating schedule data is received
by the GHP
application, the process can then proceed to step 2100. At anytime, the user
also has the
option to go back to step 2080. At step 2100, the user can manually input or
select design
temperature and flow rate data (GPM/ton) for the building design which can be
retrieved from,
read from, saved to, or written to database 2102. Alternatively, the design
temperature and/or
flow rate data can be automatically pre-populated by the GHP application based
on the prior
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received location and climate data. The building design temperature and flow
rate data can
include but is not limited to: design entering water and air temperatures for
heating and
cooling, thermostat inside of building for heating and cooling, flow rate
(GPM/ton),
type/quantity of antifreeze additive, and circulating water freeze point,
among others. Once the
building design temperature and flow rate data is received, the process can
proceed to step
2120. At anytime, the user also has the option to go back to step 2100.
[00083]In addition, prior to proceeding to step 2120, the process can
automatically detect or
ask the user if this is the first time they are inputting the design
parameters of step 2100. If this
is the first time, then the process can proceed to step 2120, if not, then the
process can
automatically direct the user to step 216. Alternatively, the user can
manually move to step
2160 or proceed to step 2120. At step 2120, the user can select or manually
input borehole
and grout data for the building design, including but not limited to: borehole
diameter, HDPE
pipe diameter, HDPE resin, SDR ratio, ground conductivity, and configurations
for u-tube
piping in the boreholes, among others. Once the borehole and grout data is
received by the
GHP application, then the process can then proceed to step 2140. At step 2140,
the user can
manually input or select ground conditions, such as ground thermal resistance
data. The
ground conditions can include but is not limited to: ground conductivity,
ground diffusivity,
thermal resistance, undisturbed earth temperature, ground density, ground
moisture, long term
ground effect forecast years, distance between boreholes, and loopfield grid
layout, among
others. Once the ground conditions or ground thermal resistance data is
received at step 2140,
then the process can process all prior inputted/selected and received data in
combination with
the borehole resistance data at step 2152 and ground resistance data at step
2154 and direct
the user to the building zone module at step 2160, wherein the user can select
or input data for
individual zones 2180. Alternatively, the user may manually select to go to
building zone
module step 2160.
[00084]At step 2160, the user can be presented with a building zone module
hub, page, or
portal, wherein one or more of the aforementioned user selected data and/or
calculated and
computer data can also be presented to the user for review, selection, or
input. Further the
building zone module 2160 allows the user to enter, select, and input a
variety of attributes
related to a zone within the building. Here, zones can be a floor, room, open
space, closed
space, or any area in or around the building. For example, the building zone
module data can
include, but is not limited to: individual zone display loads, type of zone
area (i.e. general office,
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conference, utility room, etc.), square footage of the zone, heat pump
type/number, zone
capacity, and electric operating costs, among others. Further, there can be
any number of
independent zones, such as from 1-1,000 zones. If this is the first time that
the user is
inputting data for a particular zone, then they can automatically be directed
to step 2170.
[00085]At step 2170, the user may input or select the internal heat gain data
or accept the
estimated heat gain data generated by the GHP application. Heat gain data can
include but is
not limited to: heat gain parameters such heat generated from light, people,
number and type
of appliances, electronics, and heat dissipating devices in use, percentage of
area comprised
of windows/glass, type of building and use, lighting wattage/square footage,
square footage
occupied per person, and BTUs per person, among others. Once the internal heat
gain data is
received at step 2170, then the process will go step 2180, via module 2160.
[00086]At step 2180, which can be performed within the building zone module
portal 2160, the
user can optionally revise prior input (such as prior heat gain parameters
from step 2170) or
enter new input for the zones in addition to inputting or selecting various
other parameters,
including but not limited to type of zone, square footage of the zone, heat
pump type, make, or
model, a hybrid design percentage, the building zone's current or anticipated
peak/block
cooling and heating loads, and the building zone's internal heat gain
parameters such heat
generated from light, people, number and type of appliances, electronics, and
heat dissipating
devices in use, percentage of area comprised of windows/glass, type of
building and use,
lighting wattage/square footage, square footage occupied per person, and BTUs
per person,
among others. Once the parameters are selected or inputted, then the process
can proceed
back to step 2160.
[00087]More specifically, at step 2182, which can also be within the building
zone module
portal, the user can input and select one or more types of heat pumps for the
selected zone,
and the GHP application can later determine and simulate the quantity of the
selected heat
pumps are required for the GHP design and at what operating capacity they are
to run, such as
part, full, or variable capacity. The heat pump types can be include the
brand, model, and
series, wherein the model or series can indicate the heat pump's
capacity/tonnage, among
others, and wherein the brands can be from a variety of manufacturers
including but not limited
to Carrier , Bosch , ClimateMaster , DaikinApplied , FHP_mfg, GeoComfort ,
GeoExcel ,
HydronModule , Tetco8, WaterFurnace , among others. Further, the technical
specifications
and performance data for each heat pump type, model, and series can be saved
and retrieved
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from one or more tables within database 2176. Further, the heat pump technical
and
performance data within database 21 76 can be also be automatically updated
when new heat
pump types and/or performance data is available. The heat pump performance
data can
include but is not limited to size, power, capacity, flow rate, airflow data,
entering water
temperatures, air temperatures, anti-freeze type, and freeze points, among
others. More
specifically, the heat pump performance data can include minimum and
suggested/recommended loop flow rate for capacity (BTU/hr) and power (kW) over
a range or
increments of entering water temperatures for cooling (i.e. 60, 70, 80, 90,
and 100 deg. F) and
heating (i.e. 30, 40, 50, and 60 deg. F) for heating. Further, the
aforementioned published heat
performance data is later standardized and corrected by the GHP application
for motor type,
airflow, air temperature, anti-freeze type, and freeze points based on the GHP
design
parameters for the building's zone, which will be described in more detailed
in the disclosure
described herein.
[00088]Still referring to step 2182, the user is prompted or required to input
or select a
maximum or peak/block BTU heating and cooling loads for the selected zone,
more
specifically, the maximum or peak load conditions for the heat pump(s). In
addition, the user
can input or select an internal average heat gain. Alternatively, the GHP
application can provide
an estimated heat gain value for the individual selected zone that is based on
prior received
data about the building, zone, and GHP design. Further, it is noted that the
internal heat gain
values should be entered independently of the heating and cooling loads. The
entered and
received maximum heating, cooling, and internal heat gain parameters are then
written and
saved to database 2172, where they will be retrieved by the GHP application
for further
processing.
[00089]Referring back to step 2180, the previously received zone data can be
stored to and/or
retrieved from tables within database 2172, wherein step 2180 can also store
data to and/or
retrieve data from database 2176 and further send this data to step 2174 and
21 78 for
processing (or back to zone module 2160), wherein the processed data of steps
21 74 and
21 78 can be transmitted back to the building zone module at step 2160,
thereby providing
updated GHP design data for the selected zone. Regarding hybrid design, the
user has the
option of running a hybrid GHP design simulation. If the hybrid design
simulation selected from
the building zone module, such as 1%-99% of the GHP system design being
hybrid, then the
GHP application can calculate and simulate a hybrid design at step 2220 and
present the
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hybrid design data model and simulation at step 2240. Alternatively, if no
hybrid design is
selected (0% hybrid) then the process can calculate and simulate benchmark
parameter
design parameters entered at step 2250 and model at step 2200 and present this
data to the
simulation and model step 2240. Here, it is contemplated within the scope of
the disclosure
described herein that the hybrid design can be for heating or cooling. For
example, for hybrid
cooling, one or more of a cooling tower, fluid cooler, condenser, or chiller,
alone or in
combination, may be incorporated into the GHP simulation. For hybrid heating,
a boiler,
furnace, hot water heater, or secondary ground loop, alone or in combination,
may be
incorporated into the GHP simulation. Here, the one or more hybrid heating or
cooling
apparatuses can be activated at a pre-defined operating schedule or pre-set
temperature
threshold, when a maximum heat pump load is reached, or when an entering water
temperature threshold is reached, or combination of the one or more
aforementioned
conditions. Here, the hybrid apparatuses can work in combination, and/or
simultaneously, with
the GHP heat pumps and system, thereby handling a percentage of the overage
load/capacity
that has exceeded the threshold maximum load/capacity for the ground loop.
[00090]Regarding step 2250, the user can optionally select or manually input
benchmark or
comparison data at step 2250, including but not limited to benchmark inputting
or selecting
entering water temp for cooling and heating, a cost for ground loop or
borehole installation,
and utility electric rate, among others. Once the benchmark data is received
at step 2250, then
process can proceed to step 2200 and subsequently step 2240 for simulating and
modeling
the GHP system with the benchmark data. Alternatively, if the user selects the
previously
aforementioned hybrid design (step 2220), then the user can select or input
various hybrid
design parameters including but not limited to the type of hybrid apparatus
(i.e. cooling tower,
fluid cooler, chiller, boiler, furnace, water heater, etc.) including its
brand and model, hybrid
entering water temperature, condenser type, fan size, fan efficiency, pump
size, and pump
efficiency, among others. Once the hybrid design data is received, the process
can then
proceed to step 2240 for modeling and simulating the GHP system having a
hybrid design,
such as a GHP system in combination with one or more cooling or heating
systems, as
previously described.
[00091]At simulation and modeling step 2240, the user can be presented with
one or more
portals, user interfaces, or screens for illustrating one or more models and
simulations based
on the computations and/or calculations performed using the one or more user
selected data
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in one or more of steps 2040-2220. For example, the simulation data can
include but is not
limited to borehole length, borehole length for a 5-25 year period, number of
boreholes, length
per borehole, long term ground effect, borehole length for a 1 year period,
design heat pump
inlet, design heat pump outlet, all zones building Btu load, total heat pump
capacity, hybrid
design data, all zones peak demand, all zones flow rate, annual EER/COP,
electric operating
costs, benchmark heat pump inlet, excess length, excess length payout,
undisturbed earth
temperature, ground conductivity, ground diffusivity, pipe diameter, borehole
diameter, grout
conductivity, borehole resistance, ground moisture, building operational
schedule/hours,
distance between boreholes, grid across field, and grid down, among others. In
addition, once
at step 2240, the user further has the option to go back to any one or more of
steps 2040,
2060, 2080, 2100, 2120, 2140, 2160, 2170, 2180, 2182, 2200, 2200, and 2250,
among others,
in order to modify, add, or remove selections or data, thus instantly,
simultaneously, or in real-
time modifying and updating the design simulation at step 224. For example, in
one
embodiment, all of the portals or screen for steps 2040, 2060, 2080, 2100,
2120, 2140, 2160,
2170, 2180, 2182, 2200, 2200, 2250, and 2240 can be presented to the user on
one display
screen, tab, page, web page, or user interface wherein the user can move,
scroll, or swipe up,
down, left, or right in order to simply switch from one portal or screen to
another, thus allowing
the user to run several simulations without much effort in a simple and easy
use user interface.
[00092]FIG. 2 illustrates a more detailed flow chart diagram of the embodiment
of FIG. 1,
further illustrating the transmitting to and/or reading of data from databases
2042, 2062, 2082,
and 2102 to and from zone summary portal 2160. In addition, FIG. 2 also
further illustrates the
transmitting to and/or reading of user selected data from data selection input
portals 2062,
2084, and 2104 to and from building zone module portal 2160 for each zone
within the
building.
[00093]FIG. 3 illustrates a more detailed flow chart diagram of FIG. 1,
further illustrating the
process for processing and calculating borehole resistance at step 2152. More
specifically,
once borehole grout and ground condition data is received at steps 2120 and
2140, the
process of the GHP application can extract data from a plurality of array
tables, such as Tables
7, 8, 9 (which receive data from table 6), and received from steps 2120 and
2140. Here, at step
2152, for the borehole resistance data, the process will begin by extracting
elements and
values for the pipe, resin, u-tube geometry coefficients. Next, the process
can set inside pipe
diameter data variable (Inside Diameter = outside diameter - (min wall *2)),
and a configuration
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factor variable (Configuration Factor = geometry1 coeff * power((bore dia /
outside dia),
geometry2 coeff)). Next, the pipe resistance data using high-density
polyethylene (HDPE) for a
single u-tube (U-Tube = (1 /(2 *3.14159* .40)) * (log (outside dia / inside
dia)) / 2) and double-u
tube configurations (Double U-Tube = (1 /( 2 *3.14159 * .40)) * (log (outside
dia / inside dia)) /4)
will be set with graphite data or without graphite additive. Next, the process
will set the grout
resistance variable (Grout Resistance = 1 / (Configuration Factor * Grout
Conductivity)). Finally,
the process can then add the calculated pipe resistance and grout resistance
data in order to
set a borehole resistance variable (Borehole Resistance = Pipe Resistance +
Grout Resistance).
The calculated borehole resistance variable and data can be then be sent to
the building zone
module 2160.
[00094]FIG. 4 illustrates a more detailed flow chart diagram of FIG. 1,
further illustrating the
process for processing and calculating ground resistance at step 2154. More
specifically, once
borehole grout and ground condition data is received at steps 2120 and 2140,
the process of
the GHP application can extract data from one or more array tables, such as
Tables 10 and 11,
and received data from steps 2120 and 2140. More specifically, the process
will calculate
ground resistance elements or variables years, months, and 1/4 of a day for
three separate
solutions for the temporal variations in heat flux by superposition of
incremental integral
expressions for when each interval of the time elements began or ended. First,
a dimensionless
value or number can be calculated related to time, bore diameter, and ground
thermal
diffusivity; (Zyears = (4 * ground diffusivity *3680.25) / power (bore dia,
2); Zmonth = (4 *
ground diffusivity *30.25) / power (bore dia, 2)); Z.25day (4 * ground
diffusivity * 0.25) / power
(bore dia, 2)). Next, G-cylindrical value for each increment at first step is
calculated and set;
(Lyears = Log10(Zyears ); L month = Log10(Zmonth); L .25day = Log10(Z.25day)).
Next, a
Gvalue for each increment is calculated and set at a second step; (Nyears = -
.89129+((0.3608*Lyears)-(0.05508 * (Lyears * Lyears))+(3.5917 * (power(10,-3)
* (Lyears * Lyears
* Lyears)))); Nmonth = -.89129+((0.3608*Lmonth)-(0.05508 * (Lmonth *
Lmonth))+(3.5917 *
(power(10,-3)* (Lmonth * Lmonth * Lmonth)))); N.25day = -.89129+((0.3608 *
L.25day)-(0.05508
* (L.25day * L.25day))+(3.5917* (power(10,-3)*(L.25day * L.25day "
L.25day))))). Then, a G
value for each increment is calculated and set at a third step is set; (Gyears
= power(10,Nyears)
Gmonth = power(10,Nmonth)G.25day = power(10,N.25day)). Finally, ground
resistance value
are calculated and set for the prior calculated data and elements; (Ra =
(Gyears - Gmonth) /
ground conductivity; Rm = (Gmonth - G.25day) / ground conductivity; Rd =
G.25day / ground
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conductivity). The processed and calculated ground resistance values are then
sent to the
building zone module 2160.
[00095]FIG. 5 illustrates a more detailed flow chart diagram of FIG. 1,
further illustrating the
process for inputting the maximum peak/block building cooling and heating
loads for each
zone at step 2180. More specifically, step 2180, which can be performed within
the building
zone module 2160, can receive the internal heat gain data and heat pump
equipment data.
Here, the process can determine if the received heat pump equipment data is a
single, dual, or
variable capacity heat pump and standardizing/iterating the manufacturer
published
performance data for the various capacity heat pumps based on cooling and
heating inlet
temperatures and flow rate. Here, if the heat pump is a single or dual
capacity, then the heat
pump performance data within database 2176, and more specifically database
2176A for full
capacity operation will be retrieved. The performance data will then be
processed for the
received maximum peak/block heat pump load for that particular zone.
[00096]Still referring to FIG. 5, the description for the processing and heat
pump performance
data and standardizing flow rate for GPM/ton for single or dual capacity or
stage heat pump at
full capacity can include the following process: Applying GPM/ton from a table
array of data
and extract the adjacent elements for Cooling & Heating design temperature and
flow rate;
then interpolating the elements for capacity and power (kW) and correcting the
manufacturer
published capacity and power (kW) data for air flow, air temperature,
antifreeze in circulating
water; and finding the number of heat pumps that meet the loads. Here, Tables
13, 14, 15, 16,
and 17 show sample data, elements, and units for the heat pump data retrieved
from a
database, such as database 2176, for the aforementioned heat pump performance,
correction,
and standardization process. Once the standardized or corrected single or dual
capacity heat
pump at full capacity data is processed for the maximum load, then it can be
sent back to the
building zone module 2160.
[00097]Still referring to FIG. 5, if a variable capacity heat pump data is
received, then the heat
pump performance data for full capacity will be retrieved from database 2176A
and calculated
similar to how it was performed for the dual or single capacity heat pump (as
described
previously) to obtain a variable maximum capacity data. In addition, the heat
pump
performance data for nominal capacity will be retrieved from database 2176B
and calculated to
obtain a variable nominal capacity data, and more specifically, an embodiment
for the
obtaining the variable nominal capacity data in one embodiment can include the
following
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process: Applying GPM/ton from a table array of data and extract the adjacent
elements for
Cooling & Heating design temperature and flow rate; then interpolating the
elements for
capacity and power (kW) and correcting the manufacturer published capacity and
power (kW)
data for air flow, air temperature, antifreeze in circulating water.
[00098]Still referring to FIG. 5, once the variable maximum and variable
nominal data is
calculated, these data sets will then be interpolated/iterated to obtain
another set of data that
includes corrected and standardized heat pump performance data, such as
capacity and
power. Here, Tables 13, 14, 15, 16, and 17 show sample data, elements, and
units for the heat
pump data retrieved from a database, such as database 2176, for the
aforementioned heat
pump performance, correction, and standardization process. Here, once the
variable capacity
is interpolated for the variable full capacity (maximum) and nominal capacity
(nominal) for the
maximum load, then the standardized data can be sent back to the building
summary module
2160. For a more detailed process flow chart for processing the heat pump
performance data
for the maximum load and standardize the flow rate for GPM/ton we can refer to
FIG. 5A and
5B, wherein FIG. 5A and 5B will later be described in detail in the disclosure
described herein.
[00099]Here, in one embodiment, the GHP application process must perform the
heat pump
performance correction and standardization processes for a maximum peak/block
heat pump
load for the particular zone first before running the same process again
(performing the heat
pump performance, correction, and standardization) according to the hourly
building operating
schedule data in order to obtain the most accurate data, which will be
described later in the
disclosure described herein. However, it is contemplated within the scope of
the disclosure
described herein that heat pump performance correction and standardization
processes can
also be incorporated in lieu of or in combination with the aforementioned
processes.
[000100]FIG. 6 illustrates a more detailed flow chart diagram of FIG. 1,
further illustrating the
process for calculating heat pump capacity and demand data at step 2178, and
more
specifically an iteration process for calculating, normalizing, standardizing,
or correcting the
heat pump performance data in each step for the building zone thermal loads
based on the
hourly building operating schedule data. The process flow illustrated in FIG.
6 follows a similar
methodology as illustrated in FIGS. 5, 5A, and 5B, with the exception of the
processing of the
heat pump data for each iteration step for the hourly building operating
schedule data and
additional processing for variable capacity heat pumps. In addition, FIG. 6A
illustrates a more
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detailed flow chart process for the embodiment illustrated in FIG. 6, wherein
FIG. 6A will later
be described in detail in the disclosure described herein.
[0001011Referring to FIG. 6, once the heat pump data has been processed,
standardized, and
corrected using the maximum load data (FIGS. 5, 5A, 5B), then at FIG. 6 the
GHP application
process will again determine which heat pump capacity was selected by the
user, or received
by the GHP application, and whether the received heat pump data is a single,
dual, or variable
speed. The process will retrieve corresponding heat pump data from database
2176. More
specifically, if a single capacity heat pump is selected, then full capacity
data will only be
retrieved from database 2176, and the process proceed to step 2178, wherein
the heat pump
performance data is processed, corrected, and standardized for full capacity
at each step for
each hourly building operating schedule data for an individual zone. If a dual
speed or dual
capacity heat pump is selected, then full capacity and part capacity data are
retrieved from
database 21 76 and the process proceeds to step 2178, wherein the heat pump
performance
data is processed, corrected, and standardized for part capacity at each step
for each hourly
building operating schedule data for an individual zone. More specifically,
each iteration step is
calculated and for each iteration step load (i.e. the zone BTU/hr) if the
calculated step load
value is less than the part capacity value, then the process will send the
calculated step load
value to the building zone module 2160 for the heat pump operating at part
capacity. If the
calculated step load value is greater than the party capacity, then the
calculated step load
value is sent to the building zone module 2160 for the heat pump operating and
full capacity.
[000102]Still referring to FIG. 6, if a variable capacity heat pump is
selected, then full capacity,
nominal capacity, and minimum capacity data is retrieved from database 2176,
and the
process will then proceed to step 2178, wherein the full capacity, nominal
capacity, and
minimum capacity data is iterated, interpolated, and standardized. More
specifically, the
process can first interpolate/iterate the full and nominal heat pump capacity
and power (kW)
data. The process can then determine if the calculated step load value is
greater than the
nominal capacity value and send the heat pump data for full and nominal
capacity to building
zone module 2160 for each calculated step data for each hourly building
operating schedule
for the heat pump operating at full and nominal capacity. Further, the process
can interpolate
and iterate the nominal and minimum heat pump capacity and power (kW) data.
The process
can then determine if the calculated step load value is less than the
interpolated nominal and
minimum capacity value and send the heat pump data for nominal minimum
capacity to
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building zone module 2160 for each calculated iteration step data for each
hourly building
operating schedule for the heat pump operating at nominal and minimum
conditions.
[000103]FIG. 7 illustrates a more detailed flow chart diagram of FIG. 1,
further illustrating the
process for calculating the zone monthly operating rate and processing the
building hourly
operating schedule. More specifically, the GHP application will process the
building hourly
operating schedule for each zone and set iteration steps by transposing the
received hourly
climate data by each degree of ambient temperature, wherein the process will
iterate each step
by each degree of temperature. Here, the process will start by applying
internal heat gain for
each building zone thermal loads (Beginning Step Temp = design air temp -
(zone internal gain
/ ((zone bldg loads - zone internal gain)/(design max temp - design inside
temp))). Next, the
process can process/calculate either or both the heating and cooling monthly
BTU operating
rate by applying the building hour operating schedule data for the
hottest/warmest month (for
cooling design/mode) and the coldest month (for heating design/mode) in steps
for each zone
of the building, or building zone thermal load, which in one embodiment for a
cooling design
can include: Step Zone Btu/hr = zone design loads btu/hr / (design max temp -
beginning step
temp)* (step temp - beginning step temp); Step Btu Load = each step operating
month hours *
step zone btu/hr; Month Btu Load = summarize the step btu loads; Zone Cooling
Monthly
Operating Rate (%) = month btu load / (zone design loads btu/hr* 744).
[000104]Still referring to FIG. 7, the process can then proceed to balance
each zone ground
heat exchanger length and reset the entering water temperature if required. In
one embodiment
for a cooling design, the calculation can include: Zone Heat Rate = ((zone
loads + (3.412*heat
pump power))* borehole resistance + (monthly operating rate * monthly ground
resistance) +
.25day ground resistance); Cooling Length Heat Exch. = (zone heat
rate/((entering water temp
+ 2.2) - undisturbed earth temp) heating length; Zone Heat Rate = ((zone loads
- (3.412*heat
pump power))* (borehole resistance + (monthly operating rate* monthly ground
resistance) +
.25day ground resistance); Heating Length Heat Exch. = (zone heat
rate/(undisturbed earth
temp - (entering water temp -3.5)); Shortest Cooling or Heating Length = zone
cooling length -
heating length; Reset Heating Entering Water Temp = undisturbed earth temp -
(zone heat rate
/ heating length). The process continues on FIG. 8 further illustrating the
process for calculating
the zone monthly operating rate and processing the building hourly operating
schedule, and
BTUs transferred to and from the ground.
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[000105]Referring now to FIG. 8, for each iteration step temperature in the
ambient range
beginning with the highest temperature, the process applies the hours of the
operating
schedule data at each step temperature. Next, the process will calculate the
zone (BTU/hr) for
each step, wherein in one embodiment for a cooling design can include: Step
Zone Btu/hr =
Design zone btu/hr / (design max temp - beginning step temp)* (step temp -
beginning step
temp). Next the process will calculate the entering water temperature for each
step, wherein in
one embodiment for a cooling design can include: Step Entering Water Temp =
design entering
water temp - ((design max temp - step temp)/ (design max temp - design inside
temp)*
(design entering water temp - undisturbed earth temp)); or an alternate method
- general form
including Step Entering Water Temp = ((step zone btu/hr* ((borehole + ground
resistance) +
monthly operating rate* ground resistance)* g-function)/ length)+ undisturbed
earth temp.
Next, the process will calculate the zone heat pump equipment for the step
zone thermal loads
with the appropriate heat pump capacity type that adapts the BTU/hr capacity
and Power (kW)
for each step. Next, the process will calculate the kilowatt hours for each
step, wherein in one
embodiment for a cooling design can include: Step Kilowatt Hours = step zone
btu/hr / step
heat pump Btu/hr / (1-.25*(1- step zone btu/hr / step heat pump btu/hr)) *
step heat pump kW*
step operating hours. The process will then proceed to calculate the BTUs
transferred to and
from the ground for each step, wherein in one embodiment for a cooling design
can include:
Step Ground Btu Transfer = (-step heat pump Btu/hr - (step heat pump kW *
3412))*(step zone
btu/hr / step heat pump Btu/hr / 1-.10 * (1 - step zone btu/hr / step heat
pump btu/hr)) * step
operating hours). Finally, the process will iterate all the steps and
summarize the kilowatt hours
and ground BTUs transferred to and from the ground and multiply the total
kilowatt hours by
the electric utility rate for the zone operating cost, wherein this data is
sent to the simulation
module/portal or simulation step 2240.
[000106]FIG. 9 illustrates one example scenario and output/simulation for
calculated and
simulated cooling operating costs for one zone and FIG. 9A for heating, both
incorporating the
operating hours scheduled within each discreet temperature increment for the
building in a
given year. More specifically, FIG. 9 and 9A illustrate one scenario with
sample data for one
location with its corresponding climate data and having pre-defined building
operating hours,
building type, design temperatures and flow rate, borehole/pipe data, ground
conditions, heat
pump data, and thermal heating/cooling loads, among others. Further, this
scenario illustrates
simulated data for a non-hybrid cooling mode GHP design simulation. More
specifically, the
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output includes the total operating zone operating cost and BTUs transferred
to the ground for
one year based on the received user inputted GHP design and calculated values
with respect
to FIGS. 1-8 and 20 and previously described processes within the disclosure
described
herein.
[000107]FIG. 10, illustrates one example scenario for calculated and simulated
output for
cooling operating costs for one zone for a GHP benchmark having no hybrid
design,
incorporating the hourly operating schedule within each discreet temperature
increment for the
building in a given year, wherein the GHP benchmark output data of FIG. 10 can
be compared
to the GHP design output of FIG. 9. Here, in one embodiment, the GHP benchmark
output can
be simulated using a different entering water temperature with respect to the
GHP design
entering water temperature. When comparing the output of FIG. 9 with FIG. 10,
the GHP
design total zone operating cost does not fluctuate much with respect to the
GHP benchmark
total zone operating cost, even though the entering water temperature for the
GHP design is
higher than the entering water temperature for the GHP benchmark. This
illustrates that the
GHP design simulation has about the same or substantially the same efficiency
than the GHP
benchmark having lower entering water temperature but with significant change
in excess
borehole pipe length for the GHP benchmark, further illustrating that a
variation in enter water
temperature does not have much of an effect on the GHP efficiency and in fact
the GHP design
will require much less borehole/piping length than the GHP benchmark (see FIG.
18), thus
reducing the overall cost of the GHP design with respect to the GHP benchmark.
[000108]FIG. 11 illustrates one example scenario for calculated and simulated
cooling
operating costs for one zone for GHP design having a 20% hybrid design,
incorporating the
hourly building operating schedule data for each discreet temperature
increment for the
building in a given year. In particular, the output of FIG. 11 differs from
that of FIG. 9, in that a
percentage of the GHP design is hybrid. In this example, up to 20% of the load
for the GHP
system is transferred to a cooling tower. For example, once a pre-defined or
pre-set threshold
is met, such as temperature, zone BTU/hr, or enter water temperature, the GHP
design can
initiate the hybrid apparatus (in this case the cooling tower) to handle the
excess load. In the
example out of FIG. 11, the GHP design initiates the hybrid apparatus (cooling
tower) when the
ambient or outside temperature reaches 95 degrees Fahrenheit and the GHP
design ground
loop system has reached its maximum design load of 273,600 BTUs/hr for that
zone, wherein
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the GHP heat pump system will continue to operate with the cooling tower
handling the load
over 273,600 BTUs/hr in each iteration step.
[000109]FIG. 12 further illustrates the process for calculating the total
building's monthly
operating rate and process the building's hourly operating schedule for each
iteration step.
More specifically, FIG. 12 follows a similar process and methodology as FIG. 9
for the zones,
whereas FIG. 12 illustrates a process for calculating the total or entire
building's monthly
operate based on the calculated, simulated, and outputted GHP design and the
total year
building BTUs.
[000110]FIG. 13 illustrates one example scenario of output for a total
building's calculated and
simulated cooling total building energy requirements (BTUs) for a GHP design
having no hybrid
design, incorporating the hourly operating schedule data within each discreet
temperature
increment for the building in a given month and in a given year.
[000111]FIGS. 14, 15, and 16 illustrate detailed flow charts for processing
and calculating the
GHP design and benchmark of step 2200 for simulation and modeling. More
specifically, FIGS.
14 and 15 are for a GHP design and FIG. 16 is for a GHP benchmark design.
Referring now to
FIG. 14, one embodiment for simulating at step 2240 additional parameters for
the GHP
design, such as borehole lengths and payouts, among others, can begin by
applying and
calculating the heat pump's outlet temperatures for a total system heat pump
cooling and
heating. Here, in one embodiment for a design with 100% water and no
antifreeze the
calculation can include: Geo Design Outlet Cooling= design entering water temp
cooling-
((((total building cooling btu/hr*-1)-(3.412*total heat pump kW))*1000) /
(500*gpm cooling)); Geo
Design Outlet Heating= design entering water temp heating-((((total building
cooling btu/hr)-
(3.412*total heat pump kW))*1000) / (500*gpm Heating)). Next, the process can
include
calculating a borehole length for the first year. In one embodiment for a
cooling design the
calculation can include: Cooling Load w/ Compression = total cooling
btu/hr+(3.412 *total heat
pump kW); Total Bore Resistance = borehole resistance + (cooling monthly
operating rate *Rm
ground resistance) + (Rd ground resistance *1.04); Total Heat Rate = ((net
ground annual heat
rate * -1) + cooling load w/ compression *total bore resistance))* 1000; Net
Temp Cooling =
(design entering water temp + geo design outlet cooling) / 2) - (undisturbed
earth temp + .1);
Geo Design Borehole Length Cooling 1yr = total heat rate / net temp cooling.
Next, the process
will calculate adjusting the ground conductivity and ground diffusivity for
moisture content. In
one embodiment, the calculation can include: Volumetric heat capacity Begin =
(ground
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conductivity * 24) / ground diffusivity; Soil Specific Heat = (ground moisture
% * 1.0)+((1.0-
ground moisture %)* .21); Soil Begin Density = volumetric heat capacity begin
/ soil specific
heat; Soil Density = (ground moisture % *62.4) + soil begin density; Ground
Conductivity Moist
= (ground diffusivity / 24)* (soil specific heat *soil density); Ground
Diffusivity Moist = (ground
conductivity * 24)! (soil specific heat *soil density); Volumetric Heat
Capacity Moist = (ground
conductivity moist *24)/ ground diffusivity moist. The process will then
continue on FIG. 15.
[000112]Referring to FIG. 15, the process will continue from FIG. 14 by
calculating the long
term temperature ground effect. In one embodiment, this calculation can
include: Net Ground
Btu/hr Annual = (Total Ground Btu's Cooling+Total Ground Btu's Heating) /87601
000;
Boreholes_Each_ft = Design Borehole Length 1 yr / Boreholes_Each; Top_Exposure
= 1 -
((Borehole_Each_ft - 15)/ Borehole_Each_ft); Borefield Layout Exposure = (grid
across *2) +
(grid down *2); Across Exposure = (grid down)* (grid across + 1); Down
Exposure = (grid
across)* (grid down+1); All_Exposures = ((Borefield Layout Exposure! (Across
Exposure +
Down Exposure)) - Top_Exposure); Percent Interference = 1 - All_Exposures.
Next, the
process will calculate the long term thermal interference between adjacent
boreholes (first
step). In one embodiment, this calculation can include: Relate Diffusivity,
Time, and Distance to
the Borehole - Three radii of earth 5 ft thick; Radiusring1 = Distance Between
Boreholes / 2;
Radiusring2 = radius1 + 5Radiusring3 = radius2 +5; Radiusring4 = Radius3 + 5;
Ringsq1 =
(radiusring2 * radiusring2) - (radiusring1 * radiusring1); Ringsq2 =
(radiusring3 * radiusring3) -
(radiusring2 * radiusring2); Ringsq2 = (radiusring4 * radiusring4) -
(radiusring3 * radiusring3);
Radius1avg (radiusring1 + radiusring2) / 2; Radius2avg = (radiusring2 +
radiusring3) / 2;
Radius3avg = (radiusring3 + radiusring4) / 2. Next the process will calculate
a temperature
delta for each radius or radii (second step), wherein the calculation can be
an integral
expression. In one embodiment, which is typical for each radii, this
calculation can include:
Xfunction = Radius1avg / (2 *sqrt(ground diffusivity moist * ground forecast
years * 365));
!expression = (2.303 * log10(1/ xfunction) + (power(xfunction,2)/2) -
(power(xfunction,4)/8)-
.2886; Delta Temp Ring1 = (net ground btu/hr annual * lexpression) / (2
*3.14159 *ground
conductivity moist * geo design borehole length 1yr).
[000113]Still referring to FIG. 15, the process will then calculate heat
storage for each hollow
cylinder (third step). In one embodiment, this calculation can include: Heat
Storage Ring1 =
(3.14159 * ringsq1)* delta temp ring1; Heat Storage Ring2 = (3.14159 *
ringsq2)* delta temp
ring2; Heat Storage Ring3 = (3.14159 * ringsq3)* delta temp ring3; Heat
Storage Total = heat
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storage ring1 + heat storage ring2 * heat storage ring3; Temp Penalty = (heat
storage total /
(distance between borehole^2))* Percent Interference * -1. Next, the process
will calculate and
model/simulate the borehole length for heating and cooling designs based on a
10 year model.
In one embodiment for a cooling design, this calculation can include: Cooling
Load w/
Compression = total cooling btu/hr+(3.412 *total heat pump kW); Total Bore
Resistance =
borehole resistance + (cooling monthly operating rate * Rm ground resistance)
+ (Rd ground
resistance* 1.04); Total Heat Rate = ((net ground annual heat rate* -1) +
cooling load w/
compression *total bore resistance))* 1000; Net Temp Cooling = (design
entering water temp
+ geo design outlet cooling) /2) - (undisturbed earth temp + temp penalty);
Geo Design
Borehole Length Cooling 10yr = total heat rate! net temp cooling. However, it
is contemplated
within the scope of the disclosure described herein that any number of years
may also be used
for simulating and calculated the borehole length, such as from 1-50 years.
[000114]FIG. 16 illustrates a similar process flow methodology for calculating
and simulating a
GHP benchmark using benchmark parameters, such as benchmark entering water
temperature. More specifically, the process can begin by applying and
calculating outlet
temperatures for heating and cooling for the total heat pump system. In one
embodiment for a
benchmark with 100% water and no anti-freeze, this calculation can include:
Benchmark Outlet
Cooling= Benchmark entering water temp cooling-((((total building cooling
btu/hr*-1)-
(3.412*total heat pump kW))*1000)/ (500*gpm cooling)); Benchmark Outlet
Heating=
Benchmark entering water temp heating-((((total building cooling btu/hr)-
(3.412*total heat pump
kW))*1000) / (500*gpm Heating)). Next, the process can calculate ground annual
heat rate,
which can be based on the transfer of BTUs for a cooling and heating GHP
system. In one
embodiment, the calculation can include: Net Ground Annual Heat Rate =
(((Total Ground Btu's
Cooling + Total Ground Btu's Heating)* Ra ground resistance)/ 8760). Here, it
is noted that the
total ground BTU for cooling is a negative value. Next, the process can then
calculate the
borehole length for a first year model or simulation of the GHP benchmark. In
one embodiment
for a cooling benchmark design, this calculation can include: Cooling Load w/
Compression =
total cooling btu/hr+(3.412 *total heat pump kW); Total Bore Resistance =
borehole resistance
+ (cooling monthly operating rate * Rm ground resistance) + (Rd ground
resistance* 1.04);
Total Heat Rate = ((net ground annual heat rate* -1) + cooling load w/
compression *total bore
resistance))* 1000; Net Temp Cooling = (benchmark entering water temp +
benchmark outlet
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cooling) /2) - (undisturbed earth temp + .1); Benchmark Borehole Length
Cooling 1yr = total
heat rate / net temp cooling.
[000115]Still referring to FIG. 16, the process will finally then calculate
both a GHP design and
GHP benchmark operating cost with one or more circulating pump power (kW). In
one
embodiment for a cooling design and benchmark, this calculation can include:
Borehole
Length Difference = geo design borehole Length - benchmark borehole length;
Operating Cost
Difference = abs(geo design operating cost - benchmark operating cost);
Benchmark Payout
Years = (borehole length difference* borehole installed cost per foot)
/operating cost
difference.
[000116]FIG. 17 illustrates a detailed flow chart for processing and
calculating EER and COP
data and GHP hybrid design of step 2220. In particular, in one embodiment, the
EER (Energy
Efficiency Ratio) and COP (Coefficient of Performance) data calculation can
include the
following: Annual EER = total year building cooling btu's / (total building
cooling kw hours +
(pump kw/hr *total hours cooling)); Annual COP = total year building heating
btu's / (3.412
*(total building heating kw hours + (pump kw/hr *total hours heating))).
[000117]Still referring to FIG. 17, a process for modeling and simulating the
GHP design using
a hybrid design will now be discussed. The process can begin by evaluating the
hybrid
percentage inputted by the user and received by the GHP application, such as
from 1%-99%
of the GHP system being hybrid. Next, the process will calculate the heating
and cooling
BTU/hr for each zone by taking into account the hybrid percentage (Geo Zone
Btu/hr = total
zone btu/hr * (1.0 - hybrid percent)). Next, within building zone module 2160,
the process will
calculate the building operating hours schedule data in steps for each zone's
thermal loads at
each degree of outside ambient temperature for the received climate and site
location data.
Here, for each iteration step, the process is the same as discussed with
respect to FIGS. 6, 7,
8, and results from the output of FIG. 11. Here, each iteration step comprises
determining if a
step zone load BTU/hr is greater than a Geo or GHP (ground loop) design zone
load BTU/hr
(Step Zone Btu/hr >Geo Zone Btu/hr) and if the false then the step zone load
BTU/hr calcu led
will be used. If true, then Zone Btu/hr is set to equal Geo Zone Btu/hr and
Hybrid Hours is set
to equal step hours.
[000118]Still referring to FIG. 17, a hybrid cooling capacity and hybrid
heating capacity are
calculated. For hybrid cooling capacity, in one embodiment, this calculation
can include:
Cooling Tower Capacity = (total building cooling Load - total geo load)* 1.25;
or a Fluid Cooler
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Capacity = (total building cooling Load - total geo load); Cooling gpm =
(hybrid cooling
capacity * 1000)/(500 * (outlet temp - inlet Temp)); Design Wet Bulb Temp =
from table 1;
operating hours = summarize hybrid hours. For hybrid heating capacity, in one
embodiment,
this calculation can include: Hybrid Heating Capacity = (total building
Heating load - total geo
load); Water Flow Rate = heating gpm; operating hours = summarize hybrid
hours. Once the
hybrid data is calculated for each degree of ambient temperature according to
the building
operating schedule, then the data can be sent to the simulation module 2240
for
simulating/modeling the GHP design with a hybrid system. As an example, FIG.
11 illustrates
one scenario of output data for a GHP design with a hybrid system (20%
hybrid). FIG. 19 also
illustrates an simulation/model output and portal for GHP design with a hybrid
system (25%
hybrid).
[000119]FIG. 18 illustrates one embodiment for a user interface display of
detailed simulation
and model for one example scenario of a GHP design for both cooling and
heating having no
hybrid design and including benchmark data. More specifically, the GHP design
simulation and
model can include cooling and heating data for parameters and properties
including but not
limited to: borehole length at 10 years; number of boreholes required or
recommended; length
of the boreholes; long term ground effect; borehole length at one (1) year;
design heat pump
inlet and outlet water temperatures; total building BTU loads; GHP design
Building BTU load;
GHP design heat pump capacity; GHP design peak demand; GHP design flow rate;
GHP
design annual EER and COR; GHP design annual electric operating cost; GHP
benchmark heat
pump entering water inlet and outlet temperatures; how much GHP benchmark
exceeds GHP
design based on the extra piping required for the GHP benchmark; excess feet
payback
period; ground conditions; undisturbed earth temperature; ground conductivity
data; ground
diffusivity data; pipe diameter; borehole diameter; grout conductivity;
borehole resistance;
building hourly operating schedule data for the year; ground moisture data;
distance or spacing
between boreholes; grid layout across borefield (rows); and grid down
(columns). For a hybrid
GHP design simulation, as shown in FIG. 19, the simulation model output can
additionally
include hybrid relevant information including but not limited to: cooling
tower capacity; water
flow rate; design wet bulb .4%; and operating hybrid system operating hours.
[000120]Referring back to FIG. 5A, 5B, and 6A, which can be read in relation
to FIG. 20, will be
described in more detail. More specifically, FIG. 20 illustrates a process
flow for the
interpolation and extrapolation of data with respect to the discussion of
FIGS. 5, 5A, 5B, 6, and
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6B. Further, FIGS. 20A, 20B, and 20C each illustrate example scenario
flowcharts and non-
limiting embodiment for the interpolation and extrapolation method of FIG. 20.
[000121 ]Referring now to FIG. 5A, which is a further illustration of FIG. 5
for processing heat
pump correction data for each zone, within step 2174, the process can at step
2174A retrieve
from database 21 76 a table array of data (such as Table 14) of airflow
correction data and
extract the adjacent elements by heat pump model CFM and capacity and
interpolate the CFM
using the process in FIG. 20 for capacity air flow correction. At step 2174B,
the process can
retrieve from database 2176 a table array of data (such as Table 14) of
airflow correction data
and extract the adjacent elements by heat pump model CFM and kW and
interpolate the CFM
using the process in FIG. 20 for power (kW) air flow correction. At step
21740, the process can
retrieve from database 2176 a table array of data (such as Table 15) of air
temperature
correction data and extract the adjacent elements by entering air temp and
capacity and
interpolate the air temp using the process in FIG. 20 for capacity air temp
correction. At step
2174D, the process can then retrieve from database 2176 a table array of data
(such as Table
15) of air temperature correction data and extract the adjacent elements by
entering air temp
and power (kW) and interpolate the air temp using the process in FIG. 20 for
power (kW) air
temp correction. At step 2174E, the process can then retrieve from database 21
76 a table
array of data (such as Table 16) of freeze point percent antifreeze data and
extract the adjacent
elements for type of antifreeze by percent antifreeze from freeze point and
interpolate the
freeze point using the process in FIG. 20 for percent antifreeze. At step
2174F, the process can
then retrieve from database 2176 a table array of data (such as Table 17) of
antifreeze
correction data and extract the adjacent elements by percent antifreeze and
capacity and
interpolate the percent antifreeze using the process in FIG. 20 for capacity
antifreeze. At step
2174G, the process can then retrieve from database 21 76 a table array of data
(such as Table
17) of antifreeze correction data and extract the adjacent elements by percent
antifreeze and
power (kW) and interpolate percent antifreeze using the process in FIG. 20 for
power (kW) and
antifreeze correction.
[000122]Referring now to FIG. 5B, which is a further illustration of FIG. 5
for processing heat
pump performance data for maximum thermal loads for each and standardizing the
flow rate in
GPM/ton, for a cooling GHP design. Here, within step 2174, at step 2174H, the
process can
retrieve from database 2176 a table array of data (such as from Table 13) of
lowest
performance data and extract the lowest closed loop flow rate data (A)
entering water
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temperature (EWT), and capacity and interpolate the design EWT using the
methodology of
FIG. 20 for design capacity. At step 21741, the process can retrieve from
database 21 76 a table
array of data (such as from Table 13) of lowest performance data and extract
the lowest closed
loop flow rate data (A), entering water temperature (EVVT), and power (kW) and
interpolate the
design EWT using the methodology technique of FIG. 20 for design power (kW).
At step 2174J,
the process can then retrieve from database 2176 a table array of data (such
as Table 13) of
highest performance data and extract the highest closed loop flow rate data
(6) entering water
temperature (EWT) and capacity and interpolate the design EWT using the
methodology of FIG.
20 for design capacity. At step 2174K, the process can then retrieve from
database 21 76 a
table array of data (such as from Table 13) of highest performance data and
extract the highest
closed loop flow rate data (B) entering water temperature (EWT) and power (kW)
and
interpolate the design EWT using the methodology of FIG. 20 for design power
(kW).
[000123]Still referring to FIG. 5B, based on the prior calculated and
interpolated data, the
process will then correct the published heat pump capacity and power data.
More specifically,
at step 2174L, the process will correct and standardize the published heat
pump capacity data
using in one embodiment the following calculation: Corrected A capacity = A
data * (FIG. 5A air
flow, air temp, and antifreeze corrections); Corrected B capacity = B data *
(FIG. 5A air flow, air
temp, and antifreeze corrections). At step 2174M, the process will then
correct and standardize
the published heat pump power (kW) data using in one embodiment the following
calculation:
Corrected A pwr kw = A data * (FIG. 5A air flow, air temp, and antifreeze
corrections);
Corrected B pwr kw = B data * (FIG. 5A air flow, air temp, and antifreeze
corrections).
[000124]Still referring to FIG. 5B, at step 2174N, the process can then
retrieve from database
2176 raw lowest and highest GPM data and then calculate or standardize cooling
GPM flow
rate and the cooling capacity BTU/hr data using in one embodiment the
following calculation:
Gpm / Ton B = (corrected B capacity / 12) " gpm per ton input in step 2104;
Cooling Capacity
btu/hr = corrected B capacity - (((raw gpm B - (gpm/ton / (raw gpm B - raw
gpm A)*
(corrected B capacity - corrected A capacity)); Cooling Gpm Flow rate =
(cooling capacity /12)
* gpm per ton input in step 2104. Next, the process can calculate the cooling
power (kW). At
step 21740, the process can calculate the cooling power (kW) at the calculated
cooling GPM
flow rate using in one embodiment the following calculation: cooling power
(kW) = corrected B
pwr kw - (((raw gpm B - (gpm/ton B)) / (raw gpm B - raw gpm A)* (corrected B
pwr kw -
corrected A pwr kw)).
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[000125]FIG. 6A illustrates one embodiment of a flow chart for processing and
standardizing
individual zone heat pump performance data in each step for the building zone
thermal loads,
further based on FIG. 6. More specifically, within step 2178, at step 2178A,
the process can
retrieve from database 2176 a table array of data (such as Table 13) of the
lowest performance
data and extract the lowest closed loop flow rate data (A) by entering water
temperature (EWT)
and capacity and interpolate the step EWT using the methodology of FIG. 20 for
step capacity.
At step 2178B, the process can retrieve from database 2176 a table array of
data (such as
Table 13) of the lowest performance data and extract the lowest closed loop
flow rate data (A)
by entering water temperature (EWT) and power (kW) and interpolate the step
EWT using the
methodology of FIG. 20 for step power (kW). At step 2174C, the process can
then retrieve from
database 21 76 a table array of data (such as Table 13) of the highest
performance data and
extract the highest closed loop flow rate data (B) by entering water
temperature (EWT) and
capacity and interpolate the step EWT using the methodology of FIG. 20 for
step capacity. At
step 2174D, the process can then retrieve from database 2176 a table array of
data (such as
Table 13) of the highest performance data and extract the highest closed loop
flow rate data
(B) by entering water temperature (EWT) and step power (kW) and interpolate
the step EWT
using the methodology of FIG. 20 for step power (kW).
[000126]Still referring to FIG. 6A, based on the prior calculated and
interpolated data, the
process will then correct the published heat pump capacity and power data.
More specifically,
at step 2178E, the process will correct and standardize the published heat
pump capacity data
using in one embodiment the following calculation: Corrected A capacity = A
data * (FIG. 5A air
flow, air temp, and antifreeze corrections)Corrected B capacity = B data "
(FIG. 5A air flow, air
temp, and antifreeze corrections). At step 2178F, the process will then
correct and standardize
the published heat pump power (kW) data using in one embodiment the following
calculation:
Corrected A pwr kw = A data " (FIG. 5A air flow, air temp, and antifreeze
corrections);
Corrected B pwr kw = B data * (FIG. 5A air flow, air temp, and antifreeze
corrections).
[000127]Still referring to FIG. 6A, the process can then retrieve from
database 2176 the raw
lowest and highest GPM data for calculating the cooling step capacity for
BTU/hr and cooling
step power (kW) at cooling flow rate (GPM). More specifically, at step 2178G,
the process can
calculate the cooling step capacity for BTU/hr using in one embodiment the
following
calculation: Gpm / Ton B = ((corrected B capacity / 12) " gpm per ton input in
2104; Cooling
Step Capacity btu/hr = corrected B capacity - (((raw gpm B - (gpm/ton B)) /
(raw gpm B - raw
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gpm A)* (corrected B capacity - corrected A capacity)). At step 2178H, the
process calculate
the cooling step power (kW) at cooling flow rate (GPM) using in one embodiment
the following
calculation: Cooling Step Power kw = corrected B pwr kw - ((( raw gpm B -
(gpm/ton B))/ (raw
gpm B - raw gpm A)* (corrected B pwr kw - corrected A pwr kw)).
[000128]Referring now to FIGS. 20, 20A, 20B, and 20C, which illustrate several
embodiments
for a process of extracting array elements and processing universal
interpolation, iteration,
extrapolation data, a description will be provided for one methodology with
respect to FIG.
20A, which uses sample exemplary data from Table 13. More specifically, the
iteration process
can begin at step 300, wherein data from Table 13 can be used as an example.
Here, the GHP
application is attempting to solve for a variable x2, wherein the x2 can be
GHP design entering
or inlet water temperature (see FIG. 1, step 2100). Further, variable Array A
and Array B can be
obtained from a table, such as Table 13, wherein in this embodiment Array A
can correspond
to manufacturer provided heat pump entering water temperature (EWT) and array
B can
correspond to manufacturer provided heat pump capacity data for each EWT from
array A. At
step 302, the process will find the last key for variable A, and set the
LASTKEY to equal
END(A). At step 304, the process will then set a "Test" variable to equal to
x2. At step 306, the
process will then determine if x2 is greater than or equal to variable
A[LASTKEY], and if false,
then the process proceeds to step 408. However, if at step 306 the decision is
true, then the
process will set at step 410 for Test to equal to "A[LASTKEY] -1". Referring
back to step 408, if
the decision is true, then the process will set at step 412 for Test to equal
to "A[0] + 1". Still
referring to step 408, if the decision is false, then the process will move to
step 414. In
addition, steps 410 and 412 also proceed to step 414.
[000129]Still referring to FIG. 20A, at step 414, the process will loop the
variable Array A Value
from start key to end key (start key = 0; end key = 3). At step 416, the
process will then
determine if the Value from step 414 subtracted from Test is greater than or
equal to zero. If
false, the process will at step 418 set LASTVALUE = B[KEY] and LASTKEY =
A[KEY]. However
if the decision at step 416 is true, then at step 420, the process will set y3
= B[KEY], x3 =
A[KEY], y1 = LASTVALUE, and x1 = LASTKEY. Finally, at step 422, the process
will solve,
interpolate, or extrapolate the value for y2, wherein y2 = y3 - ((x3-x2)/ (x3-
x1)* (y3-y1)). Hence,
for the variable x2, the corresponding iterated y2. In this instance, x2 was
the GHP design heat
pump EWT (95 deg. F) and y2 is the iterated, standardized, and calculated heat
pump capacity
(45.95 MBTU/hr). Here, it is contemplated within the scope of the disclosure
described herein
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that any other variable arrays and data can be used to calculate, solve,
standardize, iterate,
correct data using the process of FIGS. 20, 20A, 20B, and 20C, including but
not limited to:
flow rate, entering/inlet/outlet water and air temperature, power, freeze
points, capacity,
thermal loads, outside and wet bulb temperatures, building operating schedule,
step loads,
hybrid design, conditions, GHP design data, GHP benchmark data, BTUs to and
from the
ground, electric operating costs, ground condition, borehole data, long term
temperature
ground effect, thermal interference between boreholes, borehole length at 1-50
years, among
others, or for any aforementioned calculations with respect to FIGS. 1-19 of
the disclosure
described herein.
[000130]Referring to FIGS. 20, 20A, 20B, and 20C, in another aspect of the
disclosure
described herein, a method of simulating a ground geothermal heat pump design
disclosed.
The method can include receiving or retrieving a first array having a
plurality of temperature
data values each assigned to plurality of keys, receiving or retrieving a
second array having a
plurality of heat pump data values each assigned to a plurality of keys,
determining the last key
in the first array having the highest temperature data value, receiving a
first temperature input
variable, receiving, retrieving, or defining a first variable to be the first
temperature input
variable, determining if the first variable or the first temperature input
variable is greater than or
equal to the last key from the first array, re-defining the first variable,
wherein the re-defined
first variable is the number one subtracted from the last key from the first
array. In addition, the
method can include subtracting the re-defined first variable from the last key
in the first array
and determining if the result is greater than or equal to zero, assigning,
defining, or retrieving a
second variable with a key to a value from the second array having the same
key, assigning,
defining, or retrieving a third variable with a key to a value from first
array having the same key,
assigning, defining, or retrieving a fourth variable to a last value from the
second array,
assigning, defining, or retrieving a fifth variable to the last key from the
first array. In addition,
the method can include calculating, interpolating, or extrapolating the
received first
temperature input variable, the second variable, the third variable, the
fourth variable, and the
fifth variable to calculate a sixth variable.
[000131]In addition, the method can further include executing a loop
operation, wherein the
loop operation is comprised of re-assigning the last key from the first array
with the highest
temperature value that resulted in subtracting the re-defined first variable
from the re-assigned
last key not being greater than or equal to zero. Here, the loop operation
further comprises
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assigning a last value from the second array with the highest heat pump value
that resulted in
subtracting the re-defined first variable from the re-assigned last key not
being greater than or
equal to zero. Further, the plurality of temperature data values in the first
array can include
entering water temperatures. In addition, the plurality of heat pump data
values in the second
array can include heat pump capacity. Further, the plurality of heat pump data
values in the
second array can include heat pump power.
[000132]Referring to FIGS. 20, 20A, 20B, and 20C, another aspect of the
disclosure described
herein can include a method of simulating a ground geothermal heat pump design
or a non-
transitory computer readable-medium storing a program for simulating an in-
ground
geothermal heat pump design, wherein the program is implemented by one or more
processors executing processor instructions. Here, the method or program can
include
receiving a first array having a plurality of temperature data values each
assigned to plurality of
keys, receiving a second array having a plurality of heat pump data values
each assigned to a
plurality of keys, finding or determining the last key in the first array
having the highest
temperature data value, receiving a first temperature input variable, defining
a first variable to
be the first temperature input variable, determining if the first variable or
the first temperature
input variable is greater than or equal to the last key from the first array,
determining if the first
temperature input variable is less than or equal to the value assigned to the
starting key in the
first array. The method or program can further include subtracting the first
variable from the
last key in the first array and determining if the result is greater than or
equal to zero, assigning
a second variable with a key to a value from the second array having the same
key, assigning a
third variable with a key to a value from first array having the same key,
assigning a fourth
variable to a value from the second array, assigning a fifth variable to a
value from the first
array, and interpolating or extrapolating the received first temperature input
variable, the
assigned second variable, the assigned third variable, the assigned fourth
variable, and the
assigned fifth variable to calculate a sixth variable.
[000133]In addition, the method or program can also include wherein the loop
operation is
comprised of re-assigning the last key from the first array with the highest
temperature value
that resulted in subtracting the first variable from the re-assigned last key
not being greater
than or equal to zero. Further, the loop operation can also include assigning
a last value from
the second array with the highest heat pump value that resulted in subtracting
the first variable
from the re-assigned last key not being greater than or equal to zero. In
addition, the plurality
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of temperature data values in the first array can include entering water
temperatures. Also, the
plurality of heat pump data values in the second array can include heat pump
capacity. In
addition, the plurality of heat pump data values in the second array can
include heat pump
power.
[000134]Referring to FIGS. 20, 20A, 20B, and 20C, another aspect of the
disclosure described
herein can include a method of simulating a ground geothermal heat pump design
or a non-
transitory computer readable-medium storing a program for simulating an in-
ground
geothermal heat pump design, wherein the program is implemented by one or more
processors executing processor instructions. Here, the method or program can
include
receiving a first array or list having a plurality of temperature data values
each assigned or
mapped to a plurality of keys, receiving a second array or list having a
plurality of heat pump
data values each assigned or mapped to a plurality of keys, determining the
last key in the first
array having the highest temperature data value, receiving a first temperature
input variable,
defining or assigning a first variable to be the first temperature input
variable, determining if the
first variable or the first temperature input variable is greater than or
equal to the last key from
the first array, determining if the first temperature input variable is less
than or equal to the
value assigned to the starting in the first array, re-defining the first
variable, wherein the re-
defined first variable is the number one added to the starting key from the
first array. In
addition, the method or program can include subtracting the re-defined first
variable from the
last key in the first array and determining if the result is greater than or
equal to zero, executing
a loop operation, wherein the loop operation is comprised of re-assigning the
last key from the
first array with the highest temperature value that resulted in subtracting
the re-defined first
variable from the re-assigned last key not being greater than or equal to
zero. The method or
program can also include assigning a second variable with a key to a value
from the second
array having the same key, assigning a third variable with a key to a value
from first array
having the same key, assigning a fourth variable to a value from the second
array, assigning a
fifth variable to the re-assigned last key value from the first array, and
interpolating or
extrapolating the received first temperature input variable, the assigned
second variable, the
assigned third variable, the assigned fourth variable, and the assigned fifth
variable to calculate
a sixth variable.
[000135]The method or program can also include wherein the loop operation
further includes
assigning or retrieving a last value from the second array with the highest
heat pump data
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value that resulted in subtracting the re-defined first variable from the re-
assigned last key not
being greater than or equal to zero. Here, the plurality of temperature data
values in the first
array can include entering water temperatures. The the plurality of heat pump
data values in
the second array can include heat pump capacity data. In addition, the
plurality of heat pump
data values in the second array can include heat pump power data.
[0001361It is contemplated within the scope of the disclosure described herein
that the GHP
application of the disclosure described herein can be applied for any type of
loop field for an
in-ground geothermal system, including but not limited to closed vertical
ground loops, closed
horizontal ground loops, closed slinky coil ground loops, closed pond ground
loops, and open
geothermal ground loops. For example, with respect to horizontal ground loops
or horizontal
boreholes, horizontal boreholes are similar to vertical boreholes with almost
the same design
parameters except horizontal boreholes are closer to the surface with most of
the borehole
running horizontal to the surface at a depth of about 15 to 45 ft. below the
surface. Generally,
the entry into the ground is at an angle of about 18 and then levels off when
reaching the level
depth and then existing back to the surface with a similar angle. Further, up
to three horizontal
boreholes can be laid near the surface as long as they have a separation
spacing of about 15
ft. Further, the header connections are nearly the same as the vertical
borehole assembly.
Here, horizontal trenches can also be used in the GHP application of the
disclosure described
herein using a flattened circular coil arrangement similar to a "slinky toy."
In addition, extra
length of piping is typically required to offset the climate condition at a
minimum depth of
about 6 ft. below the surface. Other parameters different from the vertical
borehole design
when determining the slinky piping length and the trench length is the width
of the trench or
the diameter of the pipe coil, and the overlap spacing called the "pitch". In
addition, the center-
to-center spacing between the trenches is also considered, along with the
diameter of the
HDPE pipe. Hence, the aforementioned can further be designed and simulated
with the GHP
application of the disclosure described herein.
[000137] In addition, it is contemplated within the scope of the disclosure
described herein
that the GHP application can be for modeling or simulating a GHP design for
any type of
building, including but not limited to: residential, commercial, industrial,
government, office
building, high-rise building, mid-rise building, school building, college or
university building,
dormitory building, apartment/condominium building, manufacturing plant
building, distribution
44
CA 03034210 2019-02-15
WO 2018/048432 PCT/11S2016/051184
building, warehouse, agricultural building, underground building, residential
house, or any other
type of building or enclosure.
