CN113177321A - Air conditioner load modeling method based on heat exchange dynamic process - Google Patents

Air conditioner load modeling method based on heat exchange dynamic process Download PDF

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CN113177321A
CN113177321A CN202110503501.1A CN202110503501A CN113177321A CN 113177321 A CN113177321 A CN 113177321A CN 202110503501 A CN202110503501 A CN 202110503501A CN 113177321 A CN113177321 A CN 113177321A
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air
formula
wall
temperature
conditioning room
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CN113177321B (en
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马英浩
徐吴昊
杨贺钧
刘琛
张梦袁
张大波
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Hefei University of Technology
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/06—Power analysis or power optimisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/08—Thermal analysis or thermal optimisation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/10—The network having a local or delimited stationary reach
    • H02J2310/12—The local stationary network supplying a household or a building
    • H02J2310/14—The load or loads being home appliances
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/222—Demand response systems, e.g. load shedding, peak shaving

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Abstract

The invention discloses an air conditioner load modeling method based on a heat exchange dynamic process, which comprises the following steps: the method comprises the following steps of 1, dynamically modeling the temperature of the inner wall of a room based on a one-dimensional flat-wall heat conduction process; 2, modeling the whole heat exchange process of the room based on a method for calculating heat load; and 3, establishing an air conditioner load model according to the room temperature time change curve. According to the invention, through researching the heat exchange process of a typical room structure, an air conditioner load model based on heat exchange dynamic process modeling is established, a theoretical basis is provided for active management of controllable load of an air conditioner, and a basis and a reference are further provided for actual power grid dispatching operation.

Description

Air conditioner load modeling method based on heat exchange dynamic process
Technical Field
The invention relates to the field of optimal scheduling of an electric power system, in particular to an air conditioner load modeling method based on a heat exchange dynamic process.
Background
The large-scale intermittent type uncontrollable new energy grid connection method has the advantages that higher requirements are provided for the operation flexibility of the power grid, and the operation safety of the power grid faces severe challenges. The distributed new energy access changes the traditional power distribution network operation mode, the active power distribution network technology is enabled to be generated, the communication technology and the innovation of intelligent electronic equipment enable the intelligent control and operation optimization of the active power distribution network to be realized more easily, and the distributed new energy access plays an important role in the aspects of distributed power supply scheduling, load management and the like.
In recent years, many scholars propose a concept of an active network management scheme, namely unified scheduling is carried out on adjustable devices inside a power grid, and power grid operation optimization is achieved. The cold and heat loads of an air conditioner, an electric water heater and the like have high thermal inertia, and the power grid can adjust the temperature of a user through active management, change or delay the power load of the air conditioner and play a role in peak load regulation or load transfer. Meanwhile, in summer, the photovoltaic power generation and the air conditioning load have strong coupling and correlation. Therefore, the air conditioning load is orderly managed aiming at the correlation between the photovoltaic output and the air conditioning load, the photovoltaic consumption can be promoted, the uncertainty of the photovoltaic output is balanced, and the safe and economic operation of the power system is facilitated.
The research on the air conditioner load model is mainly divided into two types: an equivalent parameter model and a computational heat load model. The equivalent parameter model is used for establishing a state space thermodynamic model of a heat transfer process by equivalently using heat transfer objects such as walls, indoor furniture and air as resistance and capacitance, using temperature as voltage and using refrigerating machines such as an air conditioner as a current source, but the model is complex in related parameters and difficult to obtain, and a high-order model is difficult to solve and is not suitable for the scheduling problem of a power system. The heat load calculation method is based on a heat exchange process, changes of building energy are calculated by calculating the difference between the refrigerating capacity of an air conditioner and the heat gain of a building, temperature changes are determined, the model does not consider the heat conduction process and the heat loss of a wall, dynamic changes of the temperature of an inner wall are ignored, and the precision is low.
Disclosure of Invention
The invention provides an air conditioner load modeling method based on a heat exchange dynamic process to avoid the defects of the existing research, which can be used for representing the change of the air conditioner load on a scheduling time scale to obtain the accurate air conditioner load containing thermal inertia information, is convenient for real-time scheduling and use and is beneficial to the safe and stable operation of a power grid.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
the invention relates to an air conditioner load modeling method based on a heat exchange dynamic process, which is characterized by comprising the following steps;
step one, dividing the heat exchange path between the air-conditioning room and the outside into: an outer wall in contact with the outside, an outer window in contact with the outside, and an inner wall in contact with a next room; the heat exchange process of the wall body of the air-conditioning room is regarded as a one-dimensional flat-wall heat conduction process, so that the temperature of the inner wall of the air-conditioning room is dynamically modeled;
step 1.1, regarding the wall body of the air-conditioning room as a one-dimensional flat-wall heat conduction process as shown in the formula (1):
Figure BDA0003057362040000021
in the formula (1), t is the temperature of the wall of the air-conditioning room; kwaThe heat conductivity coefficient of the wall of the air-conditioning room; x is the distance between the current position and the outer surface of the wall body; rhowa、cwaRespectively the density of the wall body of the air-conditioning room and the specific heat capacity of the wall body; τ is time;
obtaining the boundary condition of the outer wall by using the formula (2):
Figure BDA0003057362040000022
formula (2)In, TaIs the outside temperature; t isoutIs the temperature of the inner surface of the outer wall; delta is the thickness of the wall of the air-conditioning room;
obtaining the boundary condition of the inner wall by using the formula (3):
Figure BDA0003057362040000023
in the formula (3), TinThe temperature of the inner surface of the inner wall of the air-conditioning room; t isneIs the temperature of the next room;
step 1.2, simplifying the heat conduction process:
assuming that the wall body of the air-conditioning room is in contact with air at the inner surface to generate heat exchange, under the condition of only considering the temperature of the inner surface of the wall body, the formula (1) is simplified into a thin-wall heat conduction process shown as a formula (4):
Figure BDA0003057362040000024
in the formula (4), T is the air temperature in the air-conditioned room, alphawaThe heat exchange coefficient between the inner surface of the wall body of the air-conditioning room and the air is the heat exchange coefficient; obtaining the boundary condition of the thin-wall heat conduction process by using the formula (5):
Figure BDA0003057362040000025
step two, modeling the whole heat exchange process of the air-conditioning room based on a method for calculating the heat load:
step 2.1, calculating the heat conduction quantity Q passing through the inner wall of the air-conditioning room by using the formula (6)in：
Qin＝KwaAin(Tin-T) (6)
In the formula (6), AinThe inner surface area of the inner wall of the air-conditioning room; kwaThe heat conductivity coefficient of the wall of the air-conditioning room;
step 2.2, calculating the heat conduction quantity Q passing through the outer wall of the air-conditioning room by using the formula (7)out；
Qout＝KwaAout(Tout-T) (7)
In the formula (7), AoutThe inner surface area of the outer wall of the air-conditioning room;
step 2.3, calculating the heat conduction quantity Q through the window by using the formula (8)wi：
Qwi＝KwiAwi(Ta-T) (8)
In the formula (8), KwiThe thermal conductivity of the window of the air-conditioning room; a. thewiThe area of the window of the air-conditioning room;
step 2.4, assuming that the air temperature in the air-conditioning room is uniform, obtaining the change over time of the temperature by using the formula (9):
Figure BDA0003057362040000031
in the formula (9), phi is an air equivalent heat source; rhoin、cinAir density and specific heat capacity;
step 2.5, obtaining the whole heat exchange process of the air-conditioning room by using the formula (10):
Φ·V＝Qout+Qin+Qwi+QAC (10)
in the formula (10), V is the volume of the air-conditioning room; qACThe air conditioning refrigerating capacity of the air conditioning room;
step three, obtaining an indoor temperature change curve in the heat exchange process, determining the starting and stopping time period of the air conditioner according to the room temperature-time change curve, and establishing an air conditioner load model:
step 3.1, substituting formula (4) -formula (9) into formula (10) to obtain formula (11):
Figure BDA0003057362040000032
in the formula (11), C represents an air-conditioning room attribute coefficient and is obtained from the formula (12); f represents the influence function of the outside on the air-conditioning room and is obtained by the formula (13);
C＝AoutKwa+AinKwa+AwiKwi (12)
f(Ta,Tin,Tout)＝AwiKwiTa+AinKwaTin+AoutKwaTout (13)
in formula (13):
Figure BDA0003057362040000033
and 3.2, enabling the operation mode of the air conditioner to be as follows: to reach the set temperature T of the air conditionersetStopping the operation of the air conditioner when delta t is below; when the temperature rises back to the set temperature TsetWhen delta t is above, the air conditioner starts to operate; wherein δ t represents the allowable temperature fluctuation amplitude of the air conditioner;
calculating the start-stop time period of the air conditioner by using the formula (15) and the formula (16) according to the temperature curves expressed by the formula (11) to the formula (14):
Figure BDA0003057362040000034
Figure BDA0003057362040000035
in the formulae (15) and (16), Δ t1、Δt2Respectively as an operating period and a stop period;
step 3.3, obtaining the continuous average power P of the air conditioner by using the formula (17):
Figure BDA0003057362040000041
in the formula (17), PeRated power for the air conditioner;
step 3.4, fitting the continuous average power P to the set temperature by least squaresDegree TsetAnd the outside temperature TaAnd (4) to establish an air conditioning load model.
Compared with the prior art, the invention has the beneficial effects that:
the method of the invention considers the heat conduction process of the wall and the dynamic change of the surface temperature of the wall. Therefore, the thermal inertia information of the room is included, the precision of the air-conditioning load model is improved, the order of the model is reduced, the defect that the high-order air-conditioning load model cannot be applied to a dispatching model is overcome, real-time dispatching and using are facilitated, technical support is provided for balancing the uncertainty of the output of the new energy source by performing active load management, a theoretical basis is provided for active management of controllable loads of the air conditioner, and a basis and a reference are provided for actual power grid dispatching and running.
Drawings
FIG. 1 is a schematic flow chart of an air conditioner load modeling method according to the present invention;
FIG. 2 is a schematic view of an exemplary air conditioned room according to the present invention;
FIG. 3 is a schematic diagram of the least square method for fitting air conditioning load according to the present invention.
Detailed Description
In this embodiment, as shown in fig. 1, an air conditioner load modeling method based on a heat exchange dynamic process is to study a heat exchange process of a wall based on a one-dimensional flat wall heat conduction process, and dynamically model a temperature of an inner wall of a room; secondly, modeling the whole heat flow process of the room based on a heat load calculation method; and thirdly, calculating the continuous average power of the air conditioner according to the typical operation mode of the air conditioner and the temperature-time curve of the room to obtain an air conditioner load control model. Specifically, the method comprises the following steps:
step one, the heat exchange process between the typical air-conditioning room structure shown in fig. 2 and the outside is considered in three ways: an outer wall in contact with the outside, an outer window in contact with the outside, and an inner wall in contact with a next room. Assuming that the materials of all the wall bodies are the same, the heat exchange process of the wall bodies can be regarded as a one-dimensional flat-wall heat conduction process, and the temperature of the inner wall of a room is dynamically modeled;
step 1.1, regarding the wall of a room as a one-dimensional flat-wall heat conduction process as shown in formula (1):
Figure BDA0003057362040000042
in the formula (1), t is the wall temperature; kwaThe wall thermal conductivity coefficient; x is the distance between the current position and the outer surface of the wall body; rhowa、cwaRespectively the density and specific heat capacity of the wall; τ is time;
obtaining the boundary condition of the outer wall by using the formula (2):
Figure BDA0003057362040000051
in the formula (2), TaIs the outside temperature; t isoutThe temperature of the inner surface of the outer wall; delta is the thickness of the wall of the air-conditioning room;
obtaining the boundary condition of the inner wall by using the formula (3):
Figure BDA0003057362040000052
in the formula (3), TinThe temperature of the inner surface of the inner wall of the air-conditioning room; t isneIs the temperature of the room next to the wall;
step 1.2, simplifying the heat conduction process:
assuming that the wall is in contact with air at the inner surface to exchange heat, and the temperature of all places in the wall is not considered, only the temperature of the inner surface of the wall is considered, the formula (1) can be simplified into a thin-wall heat conduction process shown as a formula (4):
Figure BDA0003057362040000053
in the formula (4), T is the indoor air temperature, alphawaThe heat exchange coefficient between the inner surface of the wall and the air;
obtaining the boundary condition of the thin-wall heat conduction process by using the formula (5):
Figure BDA0003057362040000054
step two, based on a method for calculating heat load, considering the dynamic process of heat exchange between the indoor and the outdoor, and modeling the whole heat exchange process of the room:
step 2.1, calculating the heat conduction quantity Q passing through the inner wall by using the formula (6)in：
Qin＝KwaAin(Tin-T) (6)
In the formula (6), AinIs the inner surface area of the inner wall; kwaThe wall thermal conductivity coefficient;
step 2.2, calculating the heat conduction quantity Q passing through the outer wall by using the formula (7)out；
Qout＝KwaAout(Tout-T) (7)
In the formula (7), AoutThe area of the inner surface of the outer wall;
step 2.3, calculating the heat conduction quantity Q through the window by using the formula (8)wi：
Qwi＝KwiAwi(Ta-T) (8)
In the formula (8), KwiWindow thermal conductivity; a. thewiWindow area;
step 2.4, assuming that the indoor air temperature is uniform, the temperature variation equation with time is obtained by using equation (9):
Figure BDA0003057362040000061
in the formula (9), phi is an air equivalent heat source; rhoin、cinAir density and specific heat capacity;
step 2.5, calculating the inner wall surface temperature and the outer wall surface temperature according to the outdoor temperature by using a differential equation formed by the formula (4) and the formula (5), and further calculating the heat exchange quantity between the indoor space and the outside, wherein the heat exchange process of the whole room shown as the formula (10) can be constructed by combining the formula (8) and the formula (9) as shown in the formula (6) and the formula (7):
Φ·V＝Qout+Qin+Qwi+QAC (10)
in the formula (10), V is the room volume; qACThe air conditioning refrigerating capacity.
Step three, obtaining an indoor temperature change curve in the heat exchange process, determining the starting and stopping time period of the air conditioner according to the room temperature-time change curve, and establishing an air conditioner load model:
and 3.1, substituting the formula (6) -formula (9) into the formula (10) to obtain a formula (11), wherein the temperatures of the outer wall and the inner wall of the inner wall are obtained by the formulas (4) and (5), and the temperature of the next room is assumed to be kept unchanged, so that the real-time temperature in the room is only related to the external temperature:
Figure BDA0003057362040000062
in the formula (11), C represents an air-conditioning room attribute coefficient and is obtained from the formula (12); f represents the influence function of the outside on the air-conditioning room and is obtained by the formula (13);
C＝AoutKwa+AinKwa+AwiKwi (12)
f(Ta,Tin,Tout)＝AwiKwiTa+AinKwaTin+AoutKwaTout (13)
in formula (13):
Figure BDA0003057362040000063
step 3.2, the operation mode of the air conditioner is as follows: reaches a set temperature TsetStopping the operation when the temperature is increased back to the set temperature T at 0.5 DEG CsetThe run was started at 0.5 ℃ above δ t. Where δ t represents the allowable temperature fluctuation range of the air conditioner.
Calculating the start-stop time period of the air conditioner by using the formula (15) and the formula (16) according to the temperature curves expressed by the formula (11) to the formula (14):
Figure BDA0003057362040000064
Figure BDA0003057362040000065
in the formulae (15) and (16), Δ t1、Δt2Respectively as an operating period and a stop period;
and 3.3, when a plurality of air conditioners run simultaneously, the fluctuation of the superposed load of the air conditioners is relatively smooth, and the average power can be regarded as the total load of the air conditioners. According to the air conditioner start-stop time period obtained by the expressions (15) and (16), the continuous average power P of the air conditioner can be calculated by the expression (17):
Figure BDA0003057362040000071
in the formula (17), PeRated power for the air conditioner;
step 3.4, fitting the continuous average power P to the set temperature T by least squaressetAnd the outside temperature TaTo establish an air conditioning load model, as shown in fig. 3.

Claims (1)

1. An air conditioner load modeling method based on a heat exchange dynamic process is characterized by comprising the following steps;
step one, dividing the heat exchange path between the air-conditioning room and the outside into: an outer wall in contact with the outside, an outer window in contact with the outside, and an inner wall in contact with a next room; the heat exchange process of the wall body of the air-conditioning room is regarded as a one-dimensional flat-wall heat conduction process, so that the temperature of the inner wall of the air-conditioning room is dynamically modeled;
step 1.1, regarding the wall body of the air-conditioning room as a one-dimensional flat-wall heat conduction process as shown in the formula (1):
Figure FDA0003057362030000011
in the formula (1), t is the temperature of the wall of the air-conditioning room; kwaThe heat conductivity coefficient of the wall of the air-conditioning room; x is the distance between the current position and the outer surface of the wall body; rhowa、cwaRespectively the density of the wall body of the air-conditioning room and the specific heat capacity of the wall body; τ is time;
obtaining the boundary condition of the outer wall by using the formula (2):
Figure FDA0003057362030000012
in the formula (2), TaIs the outside temperature; t isoutIs the temperature of the inner surface of the outer wall; delta is the thickness of the wall of the air-conditioning room;
obtaining the boundary condition of the inner wall by using the formula (3):
Figure FDA0003057362030000013
in the formula (3), TinThe temperature of the inner surface of the inner wall of the air-conditioning room; t isneIs the temperature of the next room;
step 1.2, simplifying the heat conduction process:
assuming that the wall body of the air-conditioning room is in contact with air at the inner surface to generate heat exchange, under the condition of only considering the temperature of the inner surface of the wall body, the formula (1) is simplified into a thin-wall heat conduction process shown as a formula (4):
Figure FDA0003057362030000014
in the formula (4), T is the air temperature in the air-conditioned room, alphawaThe heat exchange coefficient between the inner surface of the wall body of the air-conditioning room and the air is the heat exchange coefficient;
obtaining the boundary condition of the thin-wall heat conduction process by using the formula (5):
when the value of tau is equal to 0,
Figure FDA0003057362030000015
step two, modeling the whole heat exchange process of the air-conditioning room based on a method for calculating the heat load:
step 2.1, calculating the heat conduction quantity Q passing through the inner wall of the air-conditioning room by using the formula (6)in：
Qin＝KwaAin(Tin-T) (6)
In the formula (6), AinThe inner surface area of the inner wall of the air-conditioning room; kwaThe heat conductivity coefficient of the wall of the air-conditioning room;
step 2.2, calculating the heat conduction quantity Q passing through the outer wall of the air-conditioning room by using the formula (7)out；
Qout＝KwaAout(Tout-T) (7)
In the formula (7), AoutThe inner surface area of the outer wall of the air-conditioning room;
step 2.3, calculating the heat conduction quantity Q through the window by using the formula (8)wi：
Qwi＝KwiAwi(Ta-T) (8)
In the formula (8), KwiThe thermal conductivity of the window of the air-conditioning room; a. thewiThe area of the window of the air-conditioning room;
step 2.4, assuming that the air temperature in the air-conditioning room is uniform, obtaining the change over time of the temperature by using the formula (9):
Figure FDA0003057362030000021
in the formula (9), phi is an air equivalent heat source; rhoin、cinAir density and specific heat capacity;
step 2.5, obtaining the whole heat exchange process of the air-conditioning room by using the formula (10):
Φ·V＝Qout+Qin+Qwi+QAC (10)
in the formula (10), V is the volume of the air-conditioning room; qACThe air conditioning refrigerating capacity of the air conditioning room;
step three, obtaining an indoor temperature change curve in the heat exchange process, determining the starting and stopping time period of the air conditioner according to the room temperature-time change curve, and establishing an air conditioner load model:
step 3.1, substituting formula (4) -formula (9) into formula (10) to obtain formula (11):
Figure FDA0003057362030000022
in the formula (11), C represents an air-conditioning room attribute coefficient and is obtained from the formula (12); f represents the influence function of the outside on the air-conditioning room and is obtained by the formula (13);
C＝AoutKwa+AinKwa+AwiKwi (12)
f(Ta,Tin,Tout)＝AwiKwiTa+AinKwaTin+AoutKwaTout (13)
in formula (13):
Figure FDA0003057362030000023
and 3.2, enabling the operation mode of the air conditioner to be as follows: to reach the set temperature T of the air conditionersetStopping the operation of the air conditioner when delta t is below; when the temperature rises back to the set temperature TsetWhen delta t is above, the air conditioner starts to operate; wherein δ t represents the allowable temperature fluctuation amplitude of the air conditioner;
calculating the start-stop time period of the air conditioner by using the formula (15) and the formula (16) according to the temperature curves expressed by the formula (11) to the formula (14):
Figure FDA0003057362030000031
Figure FDA0003057362030000032
in the formulae (15) and (16), Δ t1、Δt2Respectively as an operating period and a stop period;
step 3.3, obtaining the continuous average power P of the air conditioner by using the formula (17):
Figure FDA0003057362030000033
in the formula (17), PeRated power for the air conditioner;
step 3.4, fitting the continuous average power P to the set temperature T by least squaressetAnd the outside temperature TaAnd (4) to establish an air conditioning load model.
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113901590A (en) * 2021-11-17 2022-01-07 中国飞机强度研究所 Large aircraft climate environment laboratory temperature rise and fall transient load analysis method
CN115032906A (en) * 2022-05-30 2022-09-09 青岛海尔科技有限公司 Digital twin room temperature prediction method, intelligent household equipment control method and device

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106524353A (en) * 2016-11-25 2017-03-22 国网河南省电力公司电力科学研究院 Method for air-conditioner load actively controlling and participating in peak regulation of electric power
CN109146268A (en) * 2018-08-07 2019-01-04 东南大学 Consider the data network load modeling method of combined optimization data dispatch and hot energy storage
CN109284576A (en) * 2018-10-29 2019-01-29 东北电力大学 A kind of distributing electric heating load scheduling method and its modeling based on measured data
EP3708925A1 (en) * 2019-03-15 2020-09-16 Carrier Corporation Control method for air conditioning system and associated air conditioning system

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106524353A (en) * 2016-11-25 2017-03-22 国网河南省电力公司电力科学研究院 Method for air-conditioner load actively controlling and participating in peak regulation of electric power
CN109146268A (en) * 2018-08-07 2019-01-04 东南大学 Consider the data network load modeling method of combined optimization data dispatch and hot energy storage
CN109284576A (en) * 2018-10-29 2019-01-29 东北电力大学 A kind of distributing electric heating load scheduling method and its modeling based on measured data
EP3708925A1 (en) * 2019-03-15 2020-09-16 Carrier Corporation Control method for air conditioning system and associated air conditioning system

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
A. MIGLIOLI等: "Load matching in residential buildings through the use of thermal energy storages", 《IEEE XPLORE》 *
XING HE等: "Distributed Energy ManagemWith Wind Forecasting in Multimicrogrids Systement Strategy for Reaching Cost-Driven Optimal Operation Integrated", 《IEEE XPLORE》 *
洪阳等: "基于Modelica风机盘管空调系统动态控制过程仿真平台的开发与验证", 《建筑科学》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113901590A (en) * 2021-11-17 2022-01-07 中国飞机强度研究所 Large aircraft climate environment laboratory temperature rise and fall transient load analysis method
CN113901590B (en) * 2021-11-17 2022-03-01 中国飞机强度研究所 Large aircraft climate environment laboratory temperature rise and fall transient load analysis method
CN115032906A (en) * 2022-05-30 2022-09-09 青岛海尔科技有限公司 Digital twin room temperature prediction method, intelligent household equipment control method and device

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