[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

CN111144610A - Urban building energy hub optimization method and system considering human body temperature comfort - Google Patents

Urban building energy hub optimization method and system considering human body temperature comfort Download PDF

Info

Publication number
CN111144610A
CN111144610A CN201911151846.4A CN201911151846A CN111144610A CN 111144610 A CN111144610 A CN 111144610A CN 201911151846 A CN201911151846 A CN 201911151846A CN 111144610 A CN111144610 A CN 111144610A
Authority
CN
China
Prior art keywords
energy
power
time
urban building
hub
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201911151846.4A
Other languages
Chinese (zh)
Inventor
范成围
滕予非
陈刚
史华勃
刘畅
刘洋
杜新伟
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
State Grid Sichuan Electric Power Co Ltd
Electric Power Research Institute of State Grid Sichuan Electric Power Co Ltd
Original Assignee
State Grid Sichuan Electric Power Co Ltd
Electric Power Research Institute of State Grid Sichuan Electric Power Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by State Grid Sichuan Electric Power Co Ltd, Electric Power Research Institute of State Grid Sichuan Electric Power Co Ltd filed Critical State Grid Sichuan Electric Power Co Ltd
Priority to CN201911151846.4A priority Critical patent/CN111144610A/en
Publication of CN111144610A publication Critical patent/CN111144610A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Theoretical Computer Science (AREA)
  • General Business, Economics & Management (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Marketing (AREA)
  • Development Economics (AREA)
  • General Physics & Mathematics (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • Quality & Reliability (AREA)
  • Game Theory and Decision Science (AREA)
  • Operations Research (AREA)
  • Health & Medical Sciences (AREA)
  • Educational Administration (AREA)
  • Public Health (AREA)
  • Water Supply & Treatment (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Feedback Control In General (AREA)

Abstract

The invention discloses an urban building energy hub optimization method and system considering human body temperature comfort, which fully consider the experience comfort of a human body to the temperature, then use the minimum operation cost as an optimization target, and adjust the capacity configuration of each device of the urban building energy hub when the operation cost is at the minimum value, thereby ensuring the low-cost operation of the urban building energy hub, effectively ensuring the human body temperature comfort, ensuring the operation economy of the urban building energy hub, and improving the experience of users.

Description

Urban building energy hub optimization method and system considering human body temperature comfort
Technical Field
The invention relates to the technical field of electric power, in particular to an urban building energy hub optimization method and system considering human body temperature comfort.
Background
A multi-energy hub is a multi-source input-output port model formed by energy conversion equipment and energy storage equipment, and comprises an energy system formed by mutually coupling various energy sources of electricity, heat and gas, in the prior art, researches on energy hubs, particularly energy hubs of urban buildings are mainly focused on the aspects of comprehensive demand response, multi-objective optimization operation, model algorithm optimization and the like, but the researches on energy hubs of the urban buildings, such as commercial centers, residential areas, office buildings and other urban buildings are very few, in the occasions, because human bodies move among the energy hubs, the comfort condition of the human bodies during the movement also influences the operation of the energy hubs of the urban buildings, at present, no research is carried out on the combination of the temperature experience state of the human bodies and the energy hubs of the urban buildings, therefore, in the operation of the energy hubs of the urban buildings, the human experience is not considered, but the energy hub is controlled only according to the existing mode, so that the human comfort is poor frequently, and the operation cost of the energy hub is high.
Disclosure of Invention
In order to solve the technical problems of high operation cost and poor comfort of the existing urban building energy hub, the invention provides an urban building energy hub optimization method considering the comfort of human body temperature.
The invention is realized by the following technical scheme:
an urban building energy hub optimization method considering human body temperature comfort degree comprises the following steps:
step S1, obtaining operation parameters of the urban building energy hub;
step S2, obtaining a human body temperature comfort level evaluation index, and determining the output power of an air conditioning system in the energy hub according to the human body temperature comfort level evaluation index;
step S3, constructing an urban building energy hub optimization model based on the parameters obtained in the step S1 and the output power of the air conditioning system obtained in the step S2;
and step S4, solving the optimization model constructed in the step S3 to realize the optimal configuration of the urban building hub.
Preferably, the optimization model constructed in step S3 of the present invention is an objective function with the minimum total operating cost of the urban building energy hub:
Figure BDA0002283747580000021
in the formula, CINFor the installation cost of urban building energy hubs, COMFor the operation and maintenance cost of the energy hub of the urban building, CESEnergy consumption cost for an urban building energy hub; caimFor the total cost of an urban building energy hub, CsIs the installed capacity of the device s;
Figure BDA00022837475800000213
the installation cost per unit capacity of the equipment s; r is a reference discount rate,. lsThe average life of the equipment s, a is the operating and maintenance cost coefficient of the equipment,
Figure BDA00022837475800000214
and
Figure BDA00022837475800000215
respectively the gas purchase price, the electricity purchase price and the electricity sale price at the moment t;
Figure BDA00022837475800000216
and
Figure BDA00022837475800000217
the electricity purchasing power and the electricity selling power at the moment t are respectively; v. ofs.tThe gas rate of the device s at time t; Δ T is the time interval between time T and time T + 1; dnThe number of days for which each scene is typically used in n energy scenes in a year.
Preferably, step S3 of the present invention is further provided with a constraint:
Figure BDA0002283747580000022
Figure BDA0002283747580000023
Figure BDA0002283747580000024
Figure BDA0002283747580000025
Figure BDA0002283747580000026
Figure BDA0002283747580000027
Figure BDA0002283747580000028
Figure BDA0002283747580000029
Figure BDA00022837475800000210
Ws.1＝Ws.T；
Figure BDA00022837475800000211
Figure BDA00022837475800000212
Figure BDA0002283747580000031
in the formula (I), the compound is shown in the specification,
Figure BDA0002283747580000034
respectively the electrical, thermal and cold load demands of the system at time t,
Figure BDA0002283747580000035
and
Figure BDA0002283747580000036
respectively inputting electric power and outputting electric power for the device s at the time t,
Figure BDA0002283747580000037
and
Figure BDA0002283747580000038
respectively representing the thermal power input and thermal power output of the device s at the instant t,
Figure BDA0002283747580000039
indicating that the equipment s outputs cold power at the moment t; pbuy.max、Psell.maxRespectively purchasing power from a power distribution system and selling power to the power distribution system for the EH;
Figure BDA00022837475800000310
respectively 0-1 state variables of the energy hub at the time t for purchasing and selling electricity,
Figure BDA00022837475800000311
the electricity sale is indicated and indicated,
Figure BDA00022837475800000312
it is indicated that the electricity is purchased,
Figure BDA00022837475800000338
are the 0-1 state variables of the device,
Figure BDA00022837475800000313
and
Figure BDA00022837475800000314
respectively indicating that the equipment is not installed and installed;
Figure BDA00022837475800000317
and
Figure BDA00022837475800000318
respectively installing a lower limit and an upper limit of the capacity for the equipment s;
Figure BDA00022837475800000316
and
Figure BDA00022837475800000315
minimum and maximum load rates for the energy conversion device s, respectively; thetas.tIs a 0-1 state variable, θs.t0 and θs.t1 denotes that the device s is not switched on and is switched on at the time t; w is as.tThen represents the power input or output by device s at time t;
Figure BDA00022837475800000319
and
Figure BDA00022837475800000320
respectively the minimum and maximum stored energy requirements of the energy storage device; ws.tStoring energy for the energy storage device s at time t;
Figure BDA00022837475800000321
and
Figure BDA00022837475800000322
respectively charging energy power and discharging energy power for the energy storage device s at the moment t;
Figure BDA00022837475800000325
and
Figure BDA00022837475800000324
respectively charging and discharging multiplying power of the energy storage equipment;
Figure BDA00022837475800000323
and
Figure BDA00022837475800000328
respectively representing the state variable of the energy storage device at the time t,
Figure BDA00022837475800000326
the indication is that the energy is being charged,
Figure BDA00022837475800000327
indicating the discharge energy.
Preferably, step 2 of the present invention specifically comprises the following steps:
step S21, obtaining human body temperature comfort evaluation index
Figure BDA00022837475800000329
And evaluating the index according to the comfort level of the human body
Figure BDA00022837475800000330
Determining the indoor temperature required for maintaining the comfortable temperature of the human body at time t
Figure BDA00022837475800000331
And the indoor temperature required for maintaining the comfortable temperature of the human body at the moment of t +1
Figure BDA00022837475800000332
Step S22, according to the indoor temperature at the time t
Figure BDA00022837475800000333
And indoor temperature at time t +1
Figure BDA00022837475800000334
The output power of an air conditioning system in the energy hub is determined.
Preferably, the temperature comfort evaluation index of the present invention
Figure BDA00022837475800000335
Comprises the following steps:
Figure BDA0002283747580000032
in the formula, TcShowing the skin surface temperature of the human body, M is the energy metabolism rate of the human body, ClτIn the season τ, the thermal resistance of the human body wearing the garment is 1, 2, 3, 1 represents the spring and autumn season, 2 represents the summer season, and 3 represents the winter season.
Preferably, step S22 of the present invention determines the output power of the air conditioning system by:
Figure BDA0002283747580000033
wherein R, C represents the equivalent thermal resistance and equivalent thermal capacity of the building,
Figure BDA00022837475800000336
is the output power of the air-conditioning system,
Figure BDA00022837475800000337
Δ T is the time interval between time T and time T +1, which is the outdoor temperature at time T.
Preferably, in step S4 of the present invention, the total cost of the urban building energy hub is minimized by adjusting each parameter in the optimization objective function of the urban building energy hub, and the optimal configuration of the urban building hub can be realized by adjusting the device capacity of the energy hub model under the condition of minimum total cost and how hot and cold power.
On the other hand, the invention also provides an urban building energy hub optimization system considering the comfort level of the human body temperature, which comprises the following components:
the operation parameter acquisition module is used for acquiring operation parameters of an urban building energy hub; the air conditioning system output power determining module is used for acquiring a human body temperature comfort level evaluation index and determining the output power of the air conditioning system in the energy hub according to the human body temperature comfort level evaluation index; the optimization model building module is used for building an urban building energy junction optimization model according to the operation parameters and the output power of the air conditioning system; and the solving module is used for solving the constructed optimization model so as to output the optimized configuration of the urban building hub.
Preferably, the optimization model constructed by the optimization model construction module is an objective function with the minimum running total cost of the urban building energy hub:
Figure BDA0002283747580000041
in the formula, CINFor the installation cost of urban building energy hubs, COMFor the operation and maintenance cost of the energy hub of the urban building, CESEnergy consumption cost for an urban building energy hub; caimFor the total cost of an urban building energy hub, CsIs the installed capacity of the device s;
Figure BDA0002283747580000046
the installation cost per unit capacity of the equipment s; r is a reference discount rate,. lsThe average life of the equipment s, a is the operating and maintenance cost coefficient of the equipment,
Figure BDA0002283747580000047
and
Figure BDA0002283747580000048
respectively the gas purchase price, the electricity purchase price and the electricity sale price at the moment t;
Figure BDA0002283747580000049
and
Figure BDA00022837475800000410
the electricity purchasing power and the electricity selling power at the moment t are respectively; v. ofs.tFor device s at time tThe gas rate; Δ T is the time interval between time T and time T + 1; dnThe number of days for which each scene is typically used in n energy scenes in a year.
Further, the optimization model building module of the invention is also provided with constraint conditions:
Figure BDA0002283747580000042
Figure BDA0002283747580000043
Figure BDA0002283747580000044
Figure BDA0002283747580000045
Figure BDA0002283747580000051
Figure BDA0002283747580000052
Figure BDA0002283747580000053
Figure BDA0002283747580000054
Figure BDA0002283747580000055
Ws.1＝Ws.T；
Figure BDA0002283747580000056
Figure BDA0002283747580000057
Figure BDA0002283747580000058
in the formula (I), the compound is shown in the specification,
Figure BDA0002283747580000059
respectively the electrical, thermal and cold load demands of the system at time t,
Figure BDA00022837475800000510
and
Figure BDA00022837475800000511
respectively inputting electric power and outputting electric power for the device s at the time t,
Figure BDA00022837475800000512
and
Figure BDA00022837475800000513
respectively representing the thermal power input and thermal power output of the device s at the instant t,
Figure BDA00022837475800000514
indicating that the equipment s outputs cold power at the moment t; pbuy.max、Psell.maxRespectively purchasing power from a power distribution system and selling power to the power distribution system for the EH;
Figure BDA00022837475800000515
respectively 0-1 state variables of the energy hub at the time t for purchasing and selling electricity,
Figure BDA00022837475800000516
the electricity sale is indicated and indicated,
Figure BDA00022837475800000517
it is indicated that the electricity is purchased,
Figure BDA00022837475800000518
are the 0-1 state variables of the device,
Figure BDA00022837475800000519
and
Figure BDA00022837475800000520
respectively indicating that the equipment is not installed and installed;
Figure BDA00022837475800000521
and
Figure BDA00022837475800000522
respectively installing a lower limit and an upper limit of the capacity for the equipment s;
Figure BDA00022837475800000523
and
Figure BDA00022837475800000524
minimum and maximum load rates for the energy conversion device s, respectively; thetas.tIs a 0-1 state variable, θs.t0 and θs.t1 denotes that the device s is not switched on and is switched on at the time t; w is as.tThen represents the power input or output by device s at time t;
Figure BDA00022837475800000526
and
Figure BDA00022837475800000525
respectively the minimum and maximum stored energy requirements of the energy storage device; ws.tStoring energy for the energy storage device s at time t;
Figure BDA00022837475800000528
and
Figure BDA00022837475800000527
respectively charging energy power and discharging energy power for the energy storage device s at the moment t;
Figure BDA00022837475800000529
and
Figure BDA00022837475800000530
respectively charging and discharging multiplying power of the energy storage equipment;
Figure BDA00022837475800000531
and
Figure BDA00022837475800000532
respectively representing the state variable of the energy storage device at the time t,
Figure BDA00022837475800000533
the indication is that the energy is being charged,
Figure BDA00022837475800000534
indicating the discharge energy.
The invention has the following advantages and beneficial effects:
according to the method, for the analysis of the urban building energy hub, the experience comfort of a human body to the temperature is fully considered, then the operation cost is minimized as an optimization target, and the capacity configuration of each device of the urban building energy hub is adjusted when the operation cost is at the minimum value, so that the low-cost operation of the urban building energy hub can be ensured, the human body temperature comfort can be effectively ensured, the operation economy of the urban building energy hub is ensured, and the user experience is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
fig. 1 is a schematic view of a topology of an energy hub model according to the present invention.
FIG. 2 is a flow chart of the method of the present invention.
Detailed Description
Hereinafter, the term "comprising" or "may include" used in various embodiments of the present invention indicates the presence of the invented function, operation or element, and does not limit the addition of one or more functions, operations or elements. Furthermore, as used in various embodiments of the present invention, the terms "comprises," "comprising," "includes," "including," "has," "having" and their derivatives are intended to mean that the specified features, numbers, steps, operations, elements, components, or combinations of the foregoing, are only meant to indicate that a particular feature, number, step, operation, element, component, or combination of the foregoing, and should not be construed as first excluding the existence of, or adding to the possibility of, one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing.
In various embodiments of the invention, the expression "or" at least one of a or/and B "includes any or all combinations of the words listed simultaneously. For example, the expression "a or B" or "at least one of a or/and B" may include a, may include B, or may include both a and B.
Expressions (such as "first", "second", and the like) used in various embodiments of the present invention may modify various constituent elements in various embodiments, but may not limit the respective constituent elements. For example, the above description does not limit the order and/or importance of the elements described. The foregoing description is for the purpose of distinguishing one element from another. For example, the first user device and the second user device indicate different user devices, although both are user devices. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of various embodiments of the present invention.
It should be noted that: if it is described that one constituent element is "connected" to another constituent element, the first constituent element may be directly connected to the second constituent element, and a third constituent element may be "connected" between the first constituent element and the second constituent element. In contrast, when one constituent element is "directly connected" to another constituent element, it is understood that there is no third constituent element between the first constituent element and the second constituent element.
The terminology used in the various embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the various embodiments of the invention. As used herein, the singular forms are intended to include the plural forms as well, unless the context clearly indicates otherwise. Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which various embodiments of the present invention belong. The terms (such as those defined in commonly used dictionaries) should be interpreted as having a meaning that is consistent with their contextual meaning in the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein in various embodiments of the present invention.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
Example 1
The present embodiment provides the topology of the urban building energy hub model as shown in fig. 1, and in fig. 1, a schematic diagram of the topology of the coupling of the three aspects of heat, electricity and gas is given, wherein electricity includes three aspects: distribution network, wind-powered electricity generation, photovoltaic, and thermal power adjustment has two aspects, converts the heat energy into by the natural gas on the one hand, and on the other hand converts the heat energy into by the electric energy.
The embodiment provides an urban building energy hub optimization method considering human body temperature comfort, as shown in fig. 2, the method includes the following steps:
and step S1, acquiring the operation parameters of the urban building energy hub.
And step S2, obtaining the evaluation index of the human body temperature comfort level, and determining the output power of the air conditioning system in the energy hub according to the evaluation index of the human body temperature comfort level.
In this embodiment, the step S2 specifically includes:
step S21, obtaining human body temperature comfort evaluation index
Figure BDA0002283747580000073
And evaluating the index according to the comfort level of the human body
Figure BDA0002283747580000074
Determining the indoor temperature required for maintaining the comfortable temperature of the human body at time t
Figure BDA0002283747580000075
And the indoor temperature required for maintaining the comfortable temperature of the human body at the moment of t +1
Figure BDA0002283747580000076
Wherein, the temperature comfort evaluation index
Figure BDA0002283747580000077
Comprises the following steps:
Figure BDA0002283747580000071
in the formula, TcShowing the skin surface temperature of the human body, M is the energy metabolism rate of the human body, ClτIn the season τ, the thermal resistance of the human body wearing the garment is 1, 2, 3, 1 represents the spring and autumn season, 2 represents the summer season, and 3 represents the winter season. Generally speaking, evaluation index of human body temperature comfort level
Figure BDA0002283747580000078
The feeling of the human body is most comfortable in the following range, and of course, the feeling can be properly adjusted in the above range in different seasons
Figure BDA0002283747580000079
After the value is adjusted, the body surface temperature value T of the human body is obtainedcTo determine the required indoor temperature
Figure BDA00022837475800000710
Step S22, according to the indoor temperature at the time t
Figure BDA00022837475800000712
And t +Indoor temperature at time 1
Figure BDA00022837475800000711
The output power of an air conditioning system in the energy hub is determined. In this embodiment, the output power of the air conditioning system is determined by the following formula:
Figure BDA0002283747580000072
wherein R, C represents the equivalent thermal resistance and equivalent thermal capacity of the building,
Figure BDA00022837475800000713
is the output power of the air-conditioning system,
Figure BDA00022837475800000714
Δ T is the time interval between time T and time T +1, which is the outdoor temperature at time T. Indoor temperature at time t +1
Figure BDA00022837475800000715
As a predicted value, the comfortable temperature sensed by the human body is different according to the season, and thus, the current calculated temperature is used
Figure BDA0002283747580000083
Predict the value and then determine
Figure BDA0002283747580000084
Temperature value
Figure BDA0002283747580000085
Calculating the current predicted value by substituting the predicted value into a calculation model of the human body temperature comfort evaluation index, judging whether the current predicted value meets the requirement of the human body temperature comfort, and if so, judging whether the current predicted value meets the requirement of the human body temperature comfort through calculation
Figure BDA0002283747580000086
To obtain the output power of the air conditioning system to be calculated
Figure BDA0002283747580000087
When in use
Figure BDA0002283747580000088
After the determination, the minimum cost value is calculated by using the following cost optimization model, and the capacity of each device in the energy hub model is configured according to the price relationship between electricity and gas, such as winter: if the price of the natural gas is higher than that of the past natural gas, and the price of the electricity is kept stable or obviously smaller than that of the natural gas, or the price of the natural gas is lower than that of the electricity, in order to maintain the required power, under the constraint of a cost function model, the capacity configuration of the natural gas can be reduced, and the capacity configuration of the electricity can be increased, if the situation is opposite to the situation, the capacity configuration of the natural gas can be increased, and the capacity configuration of the electricity can be reduced, so that the optimal configuration of the energy hub of the urban building can be realized.
And step S3, constructing an urban building energy junction optimization model based on the parameters obtained in the step S1 and the output power of the air conditioning system obtained in the step S2.
In this embodiment, the constructed optimization model is an objective function with the minimum running total cost of the urban building energy hub:
Figure BDA0002283747580000081
in the formula, CINFor the installation cost of urban building energy hubs, COMFor the operation and maintenance cost of the energy hub of the urban building, CESEnergy consumption cost for an urban building energy hub; caimFor the total cost of an urban building energy hub, CsIs the installed capacity of the device s;
Figure BDA0002283747580000089
the installation cost per unit capacity of the equipment s; r is a reference discount rate,. lsThe average life of the equipment s, a is the operating and maintenance cost coefficient of the equipment,
Figure BDA00022837475800000810
and
Figure BDA00022837475800000811
respectively the gas purchase price, the electricity purchase price and the electricity sale price at the moment t;
Figure BDA00022837475800000812
and
Figure BDA00022837475800000813
the electricity purchasing power and the electricity selling power at the moment t are respectively; v. ofs.tThe gas rate of the device s at time t; Δ T is the time interval between time T and time T + 1; dnThe number of days for which each scene is typically used in n energy scenes in a year.
And step S4, solving the optimization model constructed in the step S3 to realize the optimal configuration of the urban building hub.
Adjusting each parameter in the optimization objective function of the urban building energy pivot to enable the total cost C of the urban building energy pivotaimAt a minimum and at a total cost CaimAdjusting the equipment capacity of the energy hub model at the minimum and under the condition of cold and hot load power; by the method, the experience comfort of the human body to the temperature is fully considered, then the operation cost is minimized as an optimization target, and the capacity configuration of each device of the urban building energy hub is adjusted when the operation cost is at the minimum value, so that the low-cost operation of the urban building energy hub can be ensured, and the human body temperature comfort can be effectively ensured, wherein in order to accurately determine the minimum value of the objective function, the following constraint conditions are also included:
Figure BDA0002283747580000082
Figure BDA0002283747580000091
Figure BDA0002283747580000092
Figure BDA0002283747580000093
Figure BDA0002283747580000094
Figure BDA0002283747580000095
Figure BDA0002283747580000096
Figure BDA0002283747580000097
Figure BDA0002283747580000098
Ws.1＝Ws.T；
Figure BDA0002283747580000099
Figure BDA00022837475800000910
Figure BDA00022837475800000911
in the formula (I), the compound is shown in the specification,
Figure BDA00022837475800000912
respectively the electrical, thermal and cold load demands of the system at time t,
Figure BDA00022837475800000913
and
Figure BDA00022837475800000914
respectively inputting electric power and outputting electric power for the device s at the time t,
Figure BDA00022837475800000915
and
Figure BDA00022837475800000916
respectively representing the thermal power input and thermal power output of the device s at the instant t,
Figure BDA00022837475800000917
indicating that the equipment s outputs cold power at the moment t; pbuy.max、Psell.maxRespectively purchasing power from a power distribution system and selling power to the power distribution system for the EH;
Figure BDA00022837475800000918
respectively 0-1 state variables of the energy hub at the time t for purchasing and selling electricity,
Figure BDA00022837475800000919
the electricity sale is indicated and indicated,
Figure BDA00022837475800000920
it is indicated that the electricity is purchased,
Figure BDA00022837475800000921
are the 0-1 state variables of the device,
Figure BDA00022837475800000922
and
Figure BDA00022837475800000923
respectively indicating that the equipment is not installed and installed;
Figure BDA00022837475800000924
and
Figure BDA00022837475800000925
respectively installing a lower limit and an upper limit of the capacity for the equipment s;
Figure BDA00022837475800000926
and
Figure BDA00022837475800000927
minimum and maximum load rates for the energy conversion device s, respectively; thetas.tIs a 0-1 state variable, θs.t0 and θs.t1 denotes that the device s is not switched on and is switched on at the time t; w is as.tThen represents the power input or output by device s at time t;
Figure BDA00022837475800000929
and
Figure BDA00022837475800000928
respectively the minimum and maximum stored energy requirements of the energy storage device; ws.tStoring energy for the energy storage device s at time t;
Figure BDA00022837475800000931
and
Figure BDA00022837475800000930
respectively charging energy power and discharging energy power for the energy storage device s at the moment t;
Figure BDA00022837475800000932
and
Figure BDA00022837475800000933
respectively charging and discharging multiplying power of the energy storage equipment;
Figure BDA00022837475800000934
and
Figure BDA00022837475800000935
respectively representing the state variable of the energy storage device at the time t,
Figure BDA00022837475800000936
the indication is that the energy is being charged,
Figure BDA00022837475800000937
indicating the discharge energy.
This embodiment is further illustrated by a specific example:
there are three scenarios in this example:
scene 1: only three combined supply units are used for supplying energy, so that the requirements of cold, heat and electricity loads are met;
scene 2: the triple generation unit and the heat storage equipment are used for eliminating peaks and filling valleys of heat load requirements;
scene 3: the triple co-generation unit and the heat pump are used for solving the problem of insufficient output during the heat load peak period of the waste heat boiler.
The results of the optimized configuration and the cost comparison for the 3 scenarios are shown in tables 1 and 2:
Figure BDA0002283747580000101
TABLE 1
Figure BDA0002283747580000102
TABLE 2
According to the table, the configuration capacity of the gas turbine and the waste heat boiler in the scene 1 is the highest, the annual cost is the highest, is 964.55 ten thousand yuan/year, and is 23.88% higher than the annual total cost of the scene 3; scene 2 is mainly characterized in that the heat storage equipment is added, the installation capacity of the gas turbine and the exhaust-heat boiler is large, so that the installation cost is the highest, meanwhile, the addition of the energy storage link improves the maximum heat energy absorbed by the absorption refrigerator during heat energy conversion refrigeration in summer, so that the configuration capacity of the absorption refrigerator is the highest, the annual total cost of scene 2 is 950.6 ten thousand yuan/year, and is 22.08% higher than the annual total cost of scene 3; after the heat pump is added in the scene 3, the problem of insufficient output during the peak period of the heat load is effectively solved, the configuration capacity of the gas turbine and the waste heat boiler is the lowest, and the annual total cost is the lowest and is 778.64 ten thousand yuan/year; according to the embodiment, the urban building energy hub is optimally configured by combining human body temperature experience, so that the comfort of the human body temperature can be ensured (no clear data exists because the comfort is the human body experience), and the economy of the urban building energy hub can be ensured after the capacity configuration of the urban building energy hub.
Example 2
Based on above-mentioned embodiment 1, this embodiment has still provided the city building energy pivot optimization system of considering human temperature comfort level, and this system includes:
an operation parameter obtaining module, configured to execute the step S1: and acquiring the operation parameters of the urban building energy hub, wherein the operation parameter acquisition module is used for executing the step S1.
An air conditioning system output power determination module, configured to execute the step S2: obtaining a human body temperature comfort level evaluation index, and determining the output power of an air conditioning system in the energy hub according to the human body temperature comfort level evaluation index;
an optimization model building module, configured to perform the above step S3: constructing an urban building energy hub optimization model according to the operation parameters and the output power of the air conditioning system;
a solving module for executing the step S4: and solving the constructed optimization model to output the optimized configuration of the urban building hub.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (10)

1. An urban building energy hub optimization method considering human body temperature comfort is characterized by comprising the following steps:
step S1, obtaining operation parameters of the urban building energy hub;
step S2, obtaining a human body temperature comfort level evaluation index, and determining the output power of an air conditioning system in the energy hub according to the human body temperature comfort level evaluation index;
step S3, constructing an urban building energy hub optimization model based on the parameters obtained in the step S1 and the output power of the air conditioning system obtained in the step S2;
and step S4, solving the optimization model constructed in the step S3 to realize the optimal configuration of the urban building hub.
2. The method as claimed in claim 1, wherein the optimization model constructed in step S3 is an objective function with minimum total cost for operating the urban building energy hub, and is characterized in that:
Figure FDA0002283747570000011
in the formula, CINFor the installation cost of urban building energy hubs, COMFor the operation and maintenance cost of the energy hub of the urban building, CESEnergy consumption cost for an urban building energy hub; caimFor the total cost of an urban building energy hub, CsIs the installed capacity of the device s;
Figure FDA0002283747570000012
the installation cost per unit capacity of the equipment s; r is a reference discount rate,. lsThe average life of the equipment s, a is the operating and maintenance cost coefficient of the equipment,
Figure FDA0002283747570000013
and
Figure FDA0002283747570000014
respectively the gas purchase price, the electricity purchase price and the electricity sale price at the moment t; pt buyAnd
Figure FDA0002283747570000015
the electricity purchasing power and the electricity selling power at the moment t are respectively; v. ofs.tThe gas rate of the device s at time t; Δ T is the time interval between time T and time T + 1; dnThe number of days for which each scene is typically used in n energy scenes in a year.
3. The method for optimizing an urban building energy hub according to claim 2, wherein the step S3 is further provided with the following constraints:
Figure FDA0002283747570000016
Figure FDA0002283747570000017
Figure FDA0002283747570000018
0≤Pt buy≤ζt buyPbuy.max；
0≤Pt sell≤ζt sellPsell.max；
0≤ζt sell+ζt buy≤1；
Figure FDA0002283747570000021
Figure FDA0002283747570000022
Figure FDA0002283747570000023
Ws.1＝Ws.T；
Figure FDA0002283747570000024
Figure FDA0002283747570000025
Figure FDA0002283747570000026
in the formula (I), the compound is shown in the specification,
Figure FDA0002283747570000027
respectively the electrical, thermal and cold load demands of the system at time t,
Figure FDA0002283747570000028
and
Figure FDA0002283747570000029
respectively inputting electric power and outputting electric power for the device s at the time t,
Figure FDA00022837475700000210
and
Figure FDA00022837475700000211
respectively representing the thermal power input and thermal power output of the device s at the instant t,
Figure FDA00022837475700000212
indicating that the equipment s outputs cold power at the moment t; pbuy.max、Psell.maxRespectively purchasing power from a power distribution system and selling power to the power distribution system for the EH;
Figure FDA00022837475700000213
respectively 0-1 state variables of the energy hub at the time t for purchasing and selling electricity,
Figure FDA00022837475700000214
the electricity sale is indicated and indicated,
Figure FDA00022837475700000215
it is indicated that the electricity is purchased,
Figure FDA00022837475700000216
are the 0-1 state variables of the device,
Figure FDA00022837475700000217
and
Figure FDA00022837475700000218
respectively indicating that the equipment is not installed and installed;
Figure FDA00022837475700000219
and
Figure FDA00022837475700000220
respectively installing a lower limit and an upper limit of the capacity for the equipment s;
Figure FDA00022837475700000221
and
Figure FDA00022837475700000222
minimum and maximum load rates for the energy conversion device s, respectively; thetas.tIs a 0-1 state variable, θs.t0 and θs.t1 denotes that the device s is not switched on and is switched on at the time t; w is as.tThen represents the power input or output by device s at time t;
Figure FDA00022837475700000223
and
Figure FDA00022837475700000224
respectively the minimum and maximum stored energy requirements of the energy storage device; w is as.tStoring energy for the energy storage device s at time t;
Figure FDA00022837475700000225
and
Figure FDA00022837475700000226
respectively charging energy power and discharging energy power for the energy storage device s at the moment t;
Figure FDA00022837475700000227
and
Figure FDA00022837475700000228
respectively charging and discharging multiplying power of the energy storage equipment;
Figure FDA00022837475700000229
and
Figure FDA00022837475700000230
respectively representing the state variable of the energy storage device at the time t,
Figure FDA00022837475700000231
the indication is that the energy is being charged,
Figure FDA00022837475700000232
indicating the discharge energy.
4. The method for optimizing an energy hub of an urban building in consideration of human body temperature comfort as claimed in any one of claims 1 to 3, wherein the step 2 comprises the following steps:
step S21, obtaining human body temperature comfort evaluation index
Figure FDA00022837475700000233
And evaluating the index according to the comfort level of the human body
Figure FDA00022837475700000234
Determining the indoor temperature required for maintaining the comfortable temperature of the human body at time t
Figure FDA00022837475700000235
And the indoor temperature required for maintaining the comfortable temperature of the human body at the moment of t +1
Figure FDA00022837475700000236
Step S22, according to the indoor temperature at the time t
Figure FDA0002283747570000031
And indoor temperature at time t +1
Figure FDA0002283747570000032
The output power of an air conditioning system in the energy hub is determined.
5. The method as claimed in claim 4, wherein the evaluation index of the temperature comfort level is an index of the optimization of the urban building energy hub considering the temperature comfort level of the human body
Figure FDA0002283747570000033
Comprises the following steps:
Figure FDA0002283747570000034
in the formula, TcShowing the skin surface temperature of the human body, M is the energy metabolism rate of the human body, ClτIn the season τ, the thermal resistance of the human body wearing the garment is 1, 2, 3, 1 represents the spring and autumn season, 2 represents the summer season, and 3 represents the winter season.
6. The method for optimizing an urban building energy hub according to claim 4, wherein the step S22 is implemented by determining the output power of the air conditioning system according to the following formula:
Figure FDA0002283747570000035
wherein R, C represents the equivalent thermal resistance and equivalent thermal capacity of the building,
Figure FDA0002283747570000036
is the output power of the air-conditioning system,
Figure FDA0002283747570000037
Δ T is the time interval between time T and time T +1, which is the outdoor temperature at time T.
7. The method as claimed in claim 1, wherein the step S4 is performed by adjusting parameters in the objective function of the urban building energy hub optimization to minimize the total cost of the urban building energy hub, and adjusting the device capacity of the energy hub model according to the minimum total cost and how cold and hot the power condition is, so as to achieve the optimal configuration of the urban building energy hub.
8. Urban building energy hub optimization system considering human body temperature comfort, characterized in that the system comprises:
the operation parameter acquisition module is used for acquiring operation parameters of an urban building energy hub; the air conditioning system output power determining module is used for acquiring a human body temperature comfort level evaluation index and determining the output power of the air conditioning system in the energy hub according to the human body temperature comfort level evaluation index; the optimization model building module is used for building an urban building energy junction optimization model according to the operation parameters and the output power of the air conditioning system; and the solving module is used for solving the constructed optimization model so as to output the optimized configuration of the urban building hub.
9. The method of claim 8, wherein the optimization model constructed by the optimization model construction module is an objective function with minimum total cost for operation of the urban building energy hub, and the optimization model is an objective function with minimum total cost for operation of the urban building energy hub:
Figure FDA0002283747570000038
in the formula, CINFor the installation cost of urban building energy hubs, COMFor the operation and maintenance cost of the energy hub of the urban building, CESEnergy consumption cost for an urban building energy hub; caimFor the total cost of an urban building energy hub, CsIs the installed capacity of the device s;
Figure FDA0002283747570000041
the installation cost per unit capacity of the equipment s; r is a reference discount rate,. lsThe average life of the equipment s, a is the operating and maintenance cost coefficient of the equipment,
Figure FDA0002283747570000042
and
Figure FDA0002283747570000043
respectively the gas purchase price, the electricity purchase price and the electricity sale price at the moment t; pt buyAnd
Figure FDA0002283747570000044
the electricity purchasing power and the electricity selling power at the moment t are respectively; v. ofs.tThe gas rate of the device s at time t; Δ T is the time interval between time T and time T + 1; dnThe number of days for which each scene is typically used in n energy scenes in a year.
10. The method of optimizing an urban building energy hub according to claim 9, wherein the optimization model building module is further configured with constraints:
Figure FDA0002283747570000045
Figure FDA0002283747570000046
Figure FDA0002283747570000047
0≤Pt buy≤ζt buyPbuy.max；
0≤Pt sell≤ζt sellPsell.max；
0≤ζt sell+ζt buy≤1；
Figure FDA0002283747570000048
Figure FDA0002283747570000049
Figure FDA00022837475700000410
Ws.1＝Ws.T；
Figure FDA00022837475700000411
Figure FDA00022837475700000412
Figure FDA00022837475700000413
in the formula (I), the compound is shown in the specification,
Figure FDA00022837475700000414
respectively the electrical, thermal and cold load demands of the system at time t,
Figure FDA00022837475700000415
and
Figure FDA00022837475700000416
respectively inputting electric power and outputting electric power for the device s at the time t,
Figure FDA00022837475700000417
and
Figure FDA00022837475700000418
respectively representing the thermal power input and thermal power output of the device s at the instant t,
Figure FDA0002283747570000051
indicating that the equipment s outputs cold power at the moment t; pbuy.max、Psell.maxRespectively purchasing power from a power distribution system and selling power to the power distribution system for the EH;
Figure FDA0002283747570000052
respectively 0-1 state variables of the energy hub at the time t for purchasing and selling electricity,
Figure FDA0002283747570000053
the electricity sale is indicated and indicated,
Figure FDA0002283747570000054
it is indicated that the electricity is purchased,
Figure FDA0002283747570000055
are the 0-1 state variables of the device,
Figure FDA0002283747570000056
and
Figure FDA0002283747570000057
respectively indicating that the equipment is not installed and installed;
Figure FDA0002283747570000058
and
Figure FDA0002283747570000059
respectively installing a lower limit and an upper limit of the capacity for the equipment s;
Figure FDA00022837475700000510
and
Figure FDA00022837475700000511
minimum and maximum load rates for the energy conversion device s, respectively; thetas.tIs a 0-1 state variable, θs.t0 and θs.t1 denotes that the device s is not switched on and is switched on at the time t; w is as.tThen represents the power input or output by device s at time t;
Figure FDA00022837475700000512
and
Figure FDA00022837475700000513
respectively the minimum and maximum stored energy requirements of the energy storage device; ws.tStoring energy for the energy storage device s at time t;
Figure FDA00022837475700000514
and
Figure FDA00022837475700000515
respectively charging energy power and discharging energy power for the energy storage device s at the moment t;
Figure FDA00022837475700000516
and
Figure FDA00022837475700000517
respectively charging and discharging multiplying power of the energy storage equipment;
Figure FDA00022837475700000518
and
Figure FDA00022837475700000519
respectively representing the state variable of the energy storage device at the time t,
Figure FDA00022837475700000520
the indication is that the energy is being charged,
Figure FDA00022837475700000521
indicating the discharge energy.
CN201911151846.4A 2019-11-22 2019-11-22 Urban building energy hub optimization method and system considering human body temperature comfort Pending CN111144610A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201911151846.4A CN111144610A (en) 2019-11-22 2019-11-22 Urban building energy hub optimization method and system considering human body temperature comfort

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201911151846.4A CN111144610A (en) 2019-11-22 2019-11-22 Urban building energy hub optimization method and system considering human body temperature comfort

Publications (1)

Publication Number Publication Date
CN111144610A true CN111144610A (en) 2020-05-12

Family

ID=70516602

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201911151846.4A Pending CN111144610A (en) 2019-11-22 2019-11-22 Urban building energy hub optimization method and system considering human body temperature comfort

Country Status (1)

Country Link
CN (1) CN111144610A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112417556A (en) * 2020-11-18 2021-02-26 同济大学 BIM forward design method based on image measurable intelligent evaluation
CN118423809A (en) * 2024-07-02 2024-08-02 深圳市金地楼宇科技有限公司 Method for predicting weather to control energy-saving equipment based on AI

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120150509A1 (en) * 2010-12-14 2012-06-14 Patrick Andrew Shiel Continuous optimization energy reduction process in commercial buildings
US20140018971A1 (en) * 2011-03-31 2014-01-16 Energent Incorporated Computer implemented electrical energy hub management system and method
CN107732897A (en) * 2017-09-12 2018-02-23 天津大学 Merge the building microgrid model prediction regulation and control method of virtual energy storage system
US20180341255A1 (en) * 2017-05-25 2018-11-29 Johnson Controls Technology Company Model predictive maintenance system for building equipment
CN109028275A (en) * 2018-06-21 2018-12-18 南瑞集团有限公司 A kind of user side building multiple-energy-source Optimization Scheduling
CN109270841A (en) * 2018-10-11 2019-01-25 东北电力大学 A kind of energy flexibility regulation method of the intelligent building based on Model Predictive Control
CN109523137A (en) * 2018-10-29 2019-03-26 天津大学 Consider the garden comprehensive energy Optimization Scheduling of building thermal load demands response
CN110245878A (en) * 2019-06-27 2019-09-17 华翔翔能电气股份有限公司 The Distributed Integration energy demand of intelligent building group responds cooperative optimization method

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120150509A1 (en) * 2010-12-14 2012-06-14 Patrick Andrew Shiel Continuous optimization energy reduction process in commercial buildings
US20140018971A1 (en) * 2011-03-31 2014-01-16 Energent Incorporated Computer implemented electrical energy hub management system and method
US20180341255A1 (en) * 2017-05-25 2018-11-29 Johnson Controls Technology Company Model predictive maintenance system for building equipment
CN107732897A (en) * 2017-09-12 2018-02-23 天津大学 Merge the building microgrid model prediction regulation and control method of virtual energy storage system
CN109028275A (en) * 2018-06-21 2018-12-18 南瑞集团有限公司 A kind of user side building multiple-energy-source Optimization Scheduling
CN109270841A (en) * 2018-10-11 2019-01-25 东北电力大学 A kind of energy flexibility regulation method of the intelligent building based on Model Predictive Control
CN109523137A (en) * 2018-10-29 2019-03-26 天津大学 Consider the garden comprehensive energy Optimization Scheduling of building thermal load demands response
CN110245878A (en) * 2019-06-27 2019-09-17 华翔翔能电气股份有限公司 The Distributed Integration energy demand of intelligent building group responds cooperative optimization method

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
JORDI SERRA 等: "Smart HVAC control in IoT：energy consumption minimization with user comfort constraints", 《THE SCIENTIFIC WORLD JOURNAL》 *
MOHAMAMD RASTEGAR 等: "Centralized home energy management in multi-carrier energy frameworks", 《2015 IEEE 15TH INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING》 *
崔鹏程: "计及综合需求侧响应的能量枢纽优化配置和综合效益评估", 《中国优秀硕士学位论文全文数据库工程科技II辑》 *
郭尊 等: "计及综合需求响应的商业园区能量枢纽优化运行", 《电网技术》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112417556A (en) * 2020-11-18 2021-02-26 同济大学 BIM forward design method based on image measurable intelligent evaluation
CN118423809A (en) * 2024-07-02 2024-08-02 深圳市金地楼宇科技有限公司 Method for predicting weather to control energy-saving equipment based on AI
CN118423809B (en) * 2024-07-02 2024-10-18 深圳市金地楼宇科技有限公司 Method for predicting weather to control energy-saving equipment based on AI

Similar Documents

Publication Publication Date Title
Xie et al. Operating reserve capacity evaluation of aggregated heterogeneous TCLs with price signals
CN105138847B (en) Convertible frequency air-conditioner load participates in the energy conservation potential appraisal procedure of demand response
CN108646552B (en) Multi-objective optimization method for natural gas distributed energy unit parameters based on genetic algorithm
CN106950840B (en) Power grid peak clipping-oriented hierarchical distributed coordination control method for comprehensive energy system
CN105117557B (en) A kind of building type cooling heating and power generation system Selection of the power plant method
Yang et al. Building electrification and carbon emissions: Integrated energy management considering the dynamics of the electricity mix and pricing
CN114462724B (en) Park aggregator double-layer optimization scheduling method considering multi-energy price incentive comprehensive demand response model
CN105790286A (en) Strategy for central air conditioner load aggregation and participation in distributed power supply output stabilization
CN113339941A (en) Control method of variable frequency air conditioner
CN113566401B (en) Demand side load control method
Chen et al. Day-ahead scheduling of large numbers of thermostatically controlled loads based on equivalent energy storage model
CN116128201A (en) Multi-virtual power plant point-to-point energy trading method based on non-cooperative game
CN111144610A (en) Urban building energy hub optimization method and system considering human body temperature comfort
TW201027014A (en) Method for managing air conditioning power consumption
Tang et al. Multi-objective optimal dispatch for integrated energy systems based on a device value tag
CN111523697A (en) Comprehensive energy service cost allocation and pricing calculation method
CN113885367A (en) Building energy efficiency management control system and method
Chu et al. Capacity determination of renewable energy systems, electricity storage, and heat storage in grid-interactive buildings
CN113240178A (en) Multi-time scale optimization scheduling method and system for electric heating interconnection system
CN117267910B (en) Method, device, equipment and medium for flexibly adjusting load of central air-conditioning refrigeration system
CN114723221B (en) Thermoelectric combined optimization scheduling method for integrated central heating and demand response
CN113159380B (en) Comprehensive energy system operation optimization method considering demand response
Braun Near-optimal control strategies for hybrid cooling plants
CN115682090A (en) Optimization control method and device for central heating system
Lujie et al. The Load Aggregation Strategy of Central Air-conditioning for Smoothing Wind Power Fluctuation

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20200512

RJ01 Rejection of invention patent application after publication