CN115540216A - Energy-saving method for split air conditioner based on causal reasoning cluster scheduling - Google Patents

Energy-saving method for split air conditioner based on causal reasoning cluster scheduling Download PDF

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CN115540216A
CN115540216A CN202210985121.0A CN202210985121A CN115540216A CN 115540216 A CN115540216 A CN 115540216A CN 202210985121 A CN202210985121 A CN 202210985121A CN 115540216 A CN115540216 A CN 115540216A
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air conditioner
heating
capacity
building
air
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姚能伟
李纲
毛进
程非凡
崔友龙
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Wuhan Linsheng Intelligent Equipment Co ltd
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
    • F24F11/46—Improving electric energy efficiency or saving
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/50—Control or safety arrangements characterised by user interfaces or communication
    • F24F11/61—Control or safety arrangements characterised by user interfaces or communication using timers
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
    • F24F11/63—Electronic processing
    • F24F11/64—Electronic processing using pre-stored data
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
    • F24F11/63—Electronic processing
    • F24F11/65—Electronic processing for selecting an operating mode
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    • G06N5/04—Inference or reasoning models
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2110/00—Control inputs relating to air properties
    • F24F2110/10—Temperature
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2110/00—Control inputs relating to air properties
    • F24F2110/10—Temperature
    • F24F2110/12—Temperature of the outside air

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Abstract

The invention relates to the technical field of split air conditioner control, in particular to a method for realizing energy conservation by designing a split air conditioner based on causal reasoning cluster scheduling, which comprises the following steps: s1, acquiring environmental temperature information, air conditioner configuration information, building information and user configuration information; s2, calculating the optimal heating temperature of the building space
Figure DDA0003801793480000011
Optimum refrigeration temperature
Figure DDA0003801793480000012
The heating quantity/cooling quantity Q required to be provided is adjusted in time and space; s3, calculating the time h for the air conditioner to operate when the building space reaches the optimal refrigerating/heating temperature c (ii) a S4, calculating and setting the air conditioner running time h s An operation mode within hours, S5, obtaining an optimal air conditioner operation strategy according to calculation; according to the invention, through design, the heat change trend of the building space can be well predicted through the building space environment information in combination with an empirical formula and an AI intelligent algorithm, and an optimal air conditioner operation strategy is formulated in combination with the heat change trend, so that the energy consumption of the air conditioner is reduced to the greatest extent under the condition of ensuring the comfort degree of a user.

Description

Energy-saving method for split air conditioner based on causal reasoning cluster scheduling
Technical Field
The invention relates to the technical field of energy-saving control of split air conditioners, in particular to a method for realizing energy saving based on causal reasoning cluster scheduling of a split air conditioner.
Background
With the rapid development of national economy and the continuous improvement of the living standard of people in China, the high-speed development of the building industry and the continuous increase of building energy consumption, the building energy conservation becomes a focus of attention of the whole society. According to the results of a great deal of investigation, the energy consumption per unit area of the large public building is higher than that of the common public building by times. The large public buildings have the characteristics of high energy consumption and large energy-saving potential and are always used as the key point of building energy saving, wherein the power consumption of air conditioners in the public buildings always accounts for a large proportion of the energy consumption of the buildings, and split air conditioners are frequently used for heating in winter and cooling in summer in some public buildings such as office buildings and ordinary schools. Due to the arrangement dispersity of the split air conditioners, energy management is difficult to perform, and the operation of the split air conditioners cannot be controlled through building space environment information, regional weather information, the number of the split air conditioners, configuration information and the like, so that the overall energy consumption is increased, and the energy consumption is wasted.
In summary, the present invention solves the existing problems by designing a method for energy saving based on causal inference cluster scheduling of a split air conditioner.
Disclosure of Invention
The invention aims to provide a method for realizing energy conservation based on causal inference cluster scheduling of a split air conditioner, which aims to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
a method for realizing energy conservation based on causal inference cluster scheduling of a split air conditioner comprises the following steps:
s1, obtaining environment temperature information, air conditioner configuration information, building information and user configuration information, wherein the environment temperature information comprises indoor environment temperature Temp room And outdoor ambient temperature Temp out And the outdoor ambient temperature TEMP of n hours in the future j (ii) a The air conditioner configuration information comprises the number num of air conditioners in the building space and the running information of the air conditioners in different modes: including cooling power for fixed frequency air conditioners
Figure BDA0003801793460000021
Heating power
Figure BDA0003801793460000022
Refrigerating capacity
Figure BDA0003801793460000023
Heating capacity
Figure BDA0003801793460000024
For inverter air conditioner, high-frequency refrigeration power is included
Figure BDA0003801793460000025
Low frequency refrigeration power
Figure BDA0003801793460000026
High frequency heating power
Figure BDA0003801793460000027
Low frequency heating power
Figure BDA0003801793460000028
High frequency refrigerating capacity
Figure BDA0003801793460000029
Low frequency refrigerating capacity
Figure BDA00038017934600000210
High frequency heating capacity
Figure BDA00038017934600000211
Low frequency heat production
Figure BDA00038017934600000212
The building information comprises a building volume V and a building wall surface area S j And heat transfer coefficient C of building wall surface j (ii) a The user configuration information comprises the optimal heating temperature
Figure BDA00038017934600000213
Optimum refrigeration temperature
Figure BDA00038017934600000214
Set operating time h of air conditioner s The air conditioner sets an operation mode;
s2, calculating the optimal heating temperature of the building space
Figure BDA00038017934600000215
Optimum refrigeration temperature
Figure BDA00038017934600000216
The heating capacity/cooling capacity Q required to be provided by the air-conditioning is specifically represented by the following formula:
Q＝Q n +Q s ，
wherein Q n Cooling/heating capacity, Q, required for optimal cooling/heating temperature of a building space s Heat dissipation in the process;
further, Q n ＝(Temp room -Temp best )×V×C air ，
Wherein V is the building volume, C air Is the specific heat capacity of the air,
Figure BDA00038017934600000217
further, Q s ＝Q c +Q a ，
Wherein Q c For heat dissipation, Q, calculated from the area of the building wall a Heat dissipation due to other factors;
further, the air conditioner is characterized in that,
Figure BDA00038017934600000218
wherein S i Is the area of the wall surface of the building C i I =1, 2, i.
Further, Q a ＝f(P num ,H air ,K room ,Temp room ,Temp out )，
Wherein P is num Number of persons in the building space, H air To the air humidity, K room For building space ventilation coefficient, temp room Is the indoor temperature, temp out Is outdoor temperature, Q a During calculation, historical data is collected, and the AI intelligent algorithm is combined to fit the functional relationship between the heat dissipation capacity of the building space and relevant key influence factors, so that the partial heat dissipation capacity which cannot be calculated through a formula is calculated, and the Q is improved s Accuracy of the heat dissipation value;
s3, calculating the time h for the air conditioner to operate when the building space reaches the optimal refrigerating/heating temperature c The formula is as follows:
Figure BDA0003801793460000031
wherein Q is the refrigerating capacity/heating capacity required by the air conditioner, P is the refrigerating/heating power of the air conditioner, and E is the energy efficiency ratio of the refrigerating/heating of the air conditioner;
s4, calculating and setting air conditioner operation time h s The operation mode in hours comprises the calculation steps ofThe following:
s41, when h is c ≥h s When the air conditioner is operated, namely the time of the air conditioner operation is longer than the set air conditioner operation time when the building space reaches the optimal refrigerating/heating temperature, the air conditioner operation only needs to keep the refrigerating/heating mode;
s42, when h c <h s When the air conditioner is running h s The ambient temperature of the building space reaches the optimal refrigerating/heating temperature after hours, and the operation h of the air conditioner needs to be calculated at the moment c An hourly mode of operation;
s43, air conditioner operation h c After hours, the ambient temperature of the building space reaches the optimal cooling/heating temperature, at which time the ambient temperature of the building space needs to be maintained at the optimal cooling/heating temperature, and the cooling capacity/heating capacity Q provided by the air conditioner needs to be provided j ＝[q 1 ,q 2 ,......,q k ]，q k For the kth hour, the air conditioning cooling capacity/heating capacity is k =1, 2, ·., and n, n = h s -h c Wherein the cooling capacity/heating capacity of the air conditioner is not less than the heat dissipation capacity in the process, so that the ambient temperature of the building space can be maintained at the optimal cooling/heating temperature, i.e. the air conditioner
Figure BDA0003801793460000032
Figure BDA0003801793460000041
S44, obtaining Q according to the calculation j I.e. the amount of cooling/heating that the air conditioner needs to provide per hour, in combination with the current air conditioning operation mode, and the high-frequency cooling power of each air conditioner in the building space
Figure BDA0003801793460000042
Low frequency refrigeration power
Figure BDA0003801793460000043
High frequency heating power
Figure BDA0003801793460000044
Low frequency heating power
Figure BDA0003801793460000045
High frequency refrigerating capacity
Figure BDA0003801793460000046
Low frequency refrigerating capacity
Figure BDA0003801793460000047
High frequency heating capacity
Figure BDA0003801793460000048
Low frequency heat production
Figure BDA0003801793460000049
And (4) information, calculating the starting and stopping states and the running modes of all air conditioners in the building in the k hours in the future. And satisfy
Figure BDA00038017934600000410
Wherein R is i In order to start and stop the air conditioner,
Figure BDA00038017934600000411
P i the operation power corresponding to different operation modes of the air conditioner; i is the running time of the air conditioner; num is the number of air conditioners in the building space; the sum of the refrigerating capacity/heating capacity of each air conditioner obtained by calculation needs to meet the requirement of not less than the refrigerating capacity/heating capacity required by the air conditioner per hour, and the refrigerating capacity/heating capacity which is equal to or closest to the refrigerating capacity/heating capacity required by the air conditioner per hour is the optimal operation strategy of the air conditioner;
s45, obtaining an optimal air conditioner operation strategy according to a genetic algorithm, wherein the starting and stopping states of all air conditioners in the building space corresponding to the kth hour are
Figure BDA00038017934600000412
The starting and stopping states of an ith air conditioner in the building space at the kth hour are set to be i =1, 2, i. All air-conditioning operation modes
Figure BDA00038017934600000413
For ith station in the k hour building spaceThe air conditioner operating power is i =1, 2, and num, wherein num is the number of air conditioners in the building space;
and S5, setting a timing task according to the calculated optimal air conditioner operation strategy, and controlling the start and stop of each air conditioner in the building air conditioner and the corresponding operation mode in a timing mode.
As a preferable aspect of the present invention, the indoor ambient temperature Temp in the ambient temperature information in S1 is room And outdoor ambient temperature Temp out Acquiring data through a temperature sensor, and obtaining the outdoor environment temperature TEMP of n hours in the future j Acquired through a regional API interface provided by the weather station, wherein the outdoor ambient temperature TEMP is n hours in the future j ＝[Temp 1 ,Temp 2 ,......,Temp i ]，Temp i For the temperature value of the ith hour, i =1, 2, ·.
As a preferred scheme of the present invention, in the air conditioner configuration information in S1, the number num of air conditioners in the building space is a user-defined value according to an actual scene, the operation information of the air conditioners in different modes is a user-defined value according to actual configuration of the air conditioners, and the high-frequency refrigeration power is
Figure BDA0003801793460000051
Figure BDA0003801793460000052
For the ith air conditioner high frequency cooling power (constant frequency air conditioner cooling power), i =1, 2, ·.. · num; low frequency refrigeration power
Figure BDA0003801793460000053
Figure BDA0003801793460000054
For the ith air conditioner low frequency cooling power (the constant frequency air conditioner low frequency cooling power is 0), i =1, 2, ·.. Once, num; high frequency refrigerating capacity
Figure BDA0003801793460000055
For the ith air conditioning high frequency cooling capacity (constant frequency air conditioning cooling capacity), i =1, 2, ·.. Num; low frequency systemCold quantity
Figure BDA0003801793460000056
For the ith air conditioner low-frequency refrigerating capacity (the constant-frequency air conditioner low-frequency refrigerating capacity is 0), i =1, 2, ·; high frequency heating power
Figure BDA0003801793460000057
Figure BDA0003801793460000058
For the ith air conditioner high frequency heating power (constant frequency air conditioner heating power), i =1, 2, ·.. Num; low frequency heating power
Figure BDA0003801793460000059
Figure BDA00038017934600000510
For the ith air conditioner low frequency heating power (the constant frequency air conditioner low frequency heating power is 0), i =1, 2, ·.. Su.., num; high frequency heating capacity
Figure BDA00038017934600000511
I =1, 2, ·.. Num for the ith air-conditioning high-frequency heating amount (fixed-frequency air-conditioning heating amount); low frequency heat production
Figure BDA00038017934600000512
For the ith air conditioner low-frequency heating amount (the fixed-frequency air conditioner low-frequency heating amount is 0), i =1, 2, ·.
As a preferable embodiment of the present invention, the building volume V and the building wall surface area S in the building information in S1 j And heat transfer coefficient C of building wall surface j Defining a value for a user according to an actual scene, wherein the area S of the wall surface of the building is defined j ＝[s 1 ,s 2 ,......,s i ]，s i The method comprises the following steps of (1) setting the area of the ith wall surface, wherein i =1, 2 and n is the number of the wall surfaces; heat transfer coefficient of building wall surface C j ＝[c 1 ,c 2 ,......,c i ]，c i For the heat transfer coefficient of the ith wall surface, i =1, 2, n。
As a preferred embodiment of the present invention, in S1, the optimal heating temperature in the user configuration information
Figure BDA0003801793460000061
Optimum refrigeration temperature
Figure BDA0003801793460000062
Set operating time h of air conditioner s And setting an operation mode of the air conditioner to be a numerical value defined by a user according to an actual scene.
As a preferable embodiment of the present invention, in the above-mentioned S43
Figure BDA0003801793460000063
Is the h th c Outdoor temperature, temp. of + k hours best For optimum cooling/heating temperature, S i Is the area of the wall surface of the building C i I =1, 2, n is the number of wall surfaces,
Figure BDA0003801793460000064
the heat dissipation caused by other factors in the kth hour.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, by designing a method for realizing energy conservation based on causal inference cluster scheduling of the split air conditioner, the heat change trend of the building space can be well predicted according to the environment information of the building space, the weather information of the area where the split air conditioner is located, the quantity and configuration information of the split air conditioner and the like, and an empirical formula and an AI (artificial intelligence) algorithm are combined, and the optimal air conditioner operation strategy is formulated according to the heat change trend, so that the energy consumption of the air conditioner is reduced to the greatest extent under the condition of ensuring the comfort level of a user.
Drawings
FIG. 1 is a schematic view of the process structure of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments, and all other embodiments obtained by a person of ordinary skill in the art without any creative work based on the embodiments of the present invention belong to the protection scope of the present invention.
While several embodiments of the present invention will be described more fully hereinafter with reference to the accompanying drawings, in order to facilitate an understanding of the invention, the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather should be construed to provide a more complete disclosure of the invention.
It will be understood that when an element is referred to as being "secured to" another element, it can be directly on the other element or intervening elements may also be present, that when an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present, and that the terms "vertical", "horizontal", "left", "right" and the like are used herein for descriptive purposes only.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs, and the terms used herein in the specification of the present invention are for the purpose of describing particular embodiments only and are not intended to limit the present invention, and the term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
In an embodiment, referring to fig. 1, the present invention provides a technical solution:
s1, obtaining environment temperature information, air conditioner configuration information, building information and user configuration information. The environment temperature information comprises indoor environment temperature Temp room And outdoor ambient temperature Temp out Outdoor ambient temperature TEMP of n hours in the future j (ii) a The air conditioner configuration information comprises the number num of air conditioners in a building space and the running information of the air conditioners in different modes: including cooling power for fixed frequency air conditioner
Figure BDA0003801793460000071
Heating power
Figure BDA0003801793460000072
Refrigerating capacity
Figure BDA0003801793460000073
Heating capacity
Figure BDA0003801793460000074
For inverter air conditioner, high-frequency refrigeration power is included
Figure BDA0003801793460000075
Low frequency refrigeration power
Figure BDA0003801793460000076
High frequency heating power
Figure BDA0003801793460000077
Low frequency heating power
Figure BDA0003801793460000078
High frequency refrigerating capacity
Figure BDA0003801793460000079
Low frequency refrigerating capacity
Figure BDA00038017934600000710
High frequency heating capacity
Figure BDA00038017934600000711
Low frequency heat production
Figure BDA00038017934600000712
The building information comprises a building volume V and a building wall surface area S j And heat transfer coefficient C of building wall surface j (ii) a The user configuration information comprises the optimal heating temperature
Figure BDA0003801793460000081
Optimum refrigeration temperature
Figure BDA0003801793460000082
Set operating time h of air conditioner s Setting an operation mode by the air conditioner;
further, the indoor ambient temperature Temp in the ambient temperature information room And outdoor ambient temperature Temp out Acquiring data through a temperature sensor, and obtaining the outdoor environment temperature TEMP of n hours in the future j Acquired through a regional API interface provided by the weather station, wherein the outdoor ambient temperature TEMP is n hours in the future j ＝[Temp 1 ,Temp 2 ,......,Temp i ]，Temp i Is a temperature value for the ith hour, i =1, 2, ·.., n;
further, the number num of the air conditioners in the building space in the air conditioner configuration information is a user-defined numerical value according to an actual scene, the operation information of the air conditioners in different modes is a user-defined numerical value according to actual configuration of the air conditioners, and the high-frequency refrigeration power
Figure BDA0003801793460000083
For the ith air-conditioning high-frequency cooling power (fixed-frequency air-conditioning cooling power), i =1, 2, ·.., num; low frequency refrigeration power
Figure BDA0003801793460000084
For the ith air conditioner low frequency cooling power (the fixed frequency air conditioner low frequency cooling power is 0), i =1, 2, ·. · num; high frequency refrigerating capacity
Figure BDA0003801793460000085
For the ith air conditioning high frequency capacity (constant frequency air conditioning capacity), i =1, 2, ·.. Su, num; low frequency refrigerating capacity
Figure BDA0003801793460000086
Figure BDA0003801793460000087
For the ith air conditioner low frequency refrigeration capacity (the fixed frequency air conditioner low frequency refrigeration capacity is 0), i =1, 2, ·.... Once.num; high frequency heating power
Figure BDA0003801793460000088
I =1, 2, ·. · num for the ith air conditioner high frequency heating power (fixed frequency air conditioner heating power); low frequency heating power
Figure BDA0003801793460000089
Figure BDA00038017934600000810
For the ith air conditioner low frequency heating power (the fixed frequency air conditioner low frequency heating power is 0), i =1, 2, ·. · num; high frequency heating capacity
Figure BDA0003801793460000091
I =1, 2, ·.. Num for the ith air-conditioning high-frequency heating amount (fixed-frequency air-conditioning heating amount); low frequency heat production
Figure BDA0003801793460000092
Figure BDA0003801793460000093
For the ith air conditioner low frequency heating amount (the fixed frequency air conditioner low frequency heating amount is 0), i =1, 2, ·.. Num;
further, the building volume V and the building wall surface area S in the building information j And heat transfer coefficient C of building wall surface j Defining a value for a user according to an actual scene, wherein the area S of the building wall surface j ＝[s 1 ,s 2 ,......,s i ]，s i The area of the ith wall surface is defined as i =1, 2, n, and n is the number of the wall surfaces; heat transfer coefficient of building wall surface C j ＝[c 1 ,c 2 ,......,c i ]，c i I =1, 2, n is the number of wall surfaces;
further, the optimal heating temperature in the user configuration information
Figure BDA0003801793460000094
Optimum refrigeration temperature
Figure BDA0003801793460000095
Set operating time h of air conditioner s Setting an operation mode of the air conditioner as a user-defined numerical value according to an actual scene;
s2, calculating the optimal heating temperature of the building space
Figure BDA0003801793460000096
Optimum refrigeration temperature
Figure BDA0003801793460000097
The heating quantity/cooling quantity Q required to be provided is adjusted in time and space;
Q＝Q n +Q s ，
wherein Q n Cooling/heating capacity, Q, required for optimal cooling/heating temperature of a building space s Heat dissipation in the process;
further, Q n ＝(Temp room -Temp best )×V×C air ，
Wherein V is the building volume, C air Is the specific heat capacity of the air,
Figure BDA0003801793460000098
further, Q s ＝Q c +Q a ，
Wherein Q c For heat dissipation, Q, calculated from the area of the building wall a Heat dissipation due to other factors.
Further, the air conditioner is provided with a fan,
Figure BDA0003801793460000101
wherein S i Is the area of the wall surface of the building C i I =1, 2, i.
Further, Q a ＝f(P num ,H air ,K room ,Temp room ,Temp out )，
Wherein P is num For building purposesNumber of persons in space, H air Air humidity, K room As ventilation coefficient of building space, temp room Is the indoor temperature, temp out Is the outdoor temperature, Q a During calculation, historical data is collected, and the AI intelligent algorithm is combined to fit the functional relationship between the heat dissipation capacity of the building space and relevant key influence factors, so that the partial heat dissipation capacity which cannot be calculated through a formula is calculated, and the Q is improved s Accuracy of the heat dissipation value;
s3, calculating the time h for the air conditioner to operate when the building space reaches the optimal refrigerating/heating temperature c The formula is as follows:
Figure BDA0003801793460000102
wherein Q is the refrigerating capacity/heating capacity required by the air conditioner, P is the refrigerating/heating power of the air conditioner, and E is the energy efficiency ratio of the refrigerating/heating of the air conditioner;
s4, calculating and setting air conditioner running time h s The operation mode in hours comprises the following calculation steps:
when h c ≥h s When the air conditioner is operated, namely the time of the air conditioner operation is longer than the set air conditioner operation time when the building space reaches the optimal refrigerating/heating temperature, the air conditioner operation only needs to keep the refrigerating/heating mode operation;
(II) when h c <h s When the air conditioner is running h s After hours, the ambient temperature of the building space reaches the optimal refrigerating/heating temperature, and the operation h of the air conditioner needs to be calculated at the moment c An hourly mode of operation;
(III) operation of air conditioner h c After hours, the ambient temperature of the building space reaches the optimal cooling/heating temperature, at which time the ambient temperature of the building space needs to be maintained at the optimal cooling/heating temperature, and the cooling capacity/heating capacity Q provided by the air conditioner needs to be provided j ＝[q 1 ,q 2 ,......,q k ]，q k For the kth hour, the air conditioning cooling capacity/heating capacity is k =1, 2, ·., and n, n = h s -h c Wherein the cooling capacity/heating capacity of the air conditionerMaintaining the ambient temperature of the building space at the optimum cooling/heating temperature by not less than the heat dissipated during the process, i.e. maintaining the ambient temperature of the building space at the optimum cooling/heating temperature
Figure BDA0003801793460000111
Figure BDA0003801793460000112
Further, the air conditioner is characterized in that,
Figure BDA0003801793460000113
is the h th c + k hours of outdoor temperature, temp best For optimum cooling/heating temperature, S i Is the area of the wall surface of the building, C i I =1, 2, n is the number of wall surfaces,
Figure BDA0003801793460000114
heat dissipation capacity caused by other factors in the kth hour;
(IV) Q obtained by calculation j I.e. the amount of cooling/heating that the air conditioner needs to provide per hour, in combination with the current air conditioning operation mode, and the high-frequency cooling power of each air conditioner in the building space
Figure BDA0003801793460000115
Low frequency refrigeration power
Figure BDA0003801793460000116
High frequency heating power
Figure BDA0003801793460000117
Low frequency heating power
Figure BDA0003801793460000118
High frequency refrigerating capacity
Figure BDA0003801793460000119
Low frequency refrigerating capacity
Figure BDA00038017934600001110
High frequency heating capacity
Figure BDA00038017934600001111
Low frequency heat generation
Figure BDA00038017934600001112
Information, calculating the starting and stopping states and running modes of all air conditioners in the building in the k hours in the future, and meeting the requirements
Figure BDA00038017934600001113
Wherein R is i In order to start and stop the air conditioner,
Figure BDA00038017934600001114
P i the operation power corresponding to different operation modes of the air conditioner; i is the running time of the air conditioner; num is the number of air conditioners in the building space; the sum of the refrigerating capacity/heating capacity of each air conditioner obtained by calculation needs to meet the requirement of not less than the refrigerating capacity/heating capacity required by the air conditioner per hour, and the refrigerating capacity/heating capacity which is equal to or closest to the refrigerating capacity/heating capacity required by the air conditioner per hour is the optimal operation strategy of the air conditioner;
(V) obtaining an optimal air conditioner operation strategy according to a genetic algorithm, wherein the starting and stopping states of all air conditioners in the building space corresponding to the kth hour are
Figure BDA00038017934600001115
The starting and stopping states of an ith air conditioner in the building space at the kth hour are i =1, 2 and num, wherein num is the number of the air conditioners in the building space; all air-conditioning operation modes
Figure BDA00038017934600001116
The operating power of the ith air conditioner in the building space at the kth hour is i =1, 2 and num, wherein num is the number of the air conditioners in the building space;
s5, setting a timing task according to the calculated optimal air conditioner operation strategy, and controlling the start and stop of each air conditioner in the building air conditioner and the corresponding operation mode in a timing mode;
therefore, the method for achieving energy conservation based on causal inference cluster scheduling of the split air conditioner is designed, the building space environment information, the area weather information, the split air conditioner number, the configuration information and the like can be well used, the experience formula and the AI intelligent algorithm are combined, the building space heat change trend is predicted, the optimal air conditioner operation strategy is formulated according to the heat change trend, and the air conditioner energy consumption is reduced to the greatest extent under the condition that the user comfort level is guaranteed.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (6)

1. A method for realizing energy conservation based on causal inference cluster scheduling of a split air conditioner comprises the following steps:
s1, obtaining environment temperature information, air conditioner configuration information, building information and user configuration information, wherein the environment temperature information comprises indoor environment temperature Temp room And outdoor ambient temperature Temp out Outdoor ambient temperature TEMP of n hours in the future j (ii) a The air conditioner configuration information comprises the number num of air conditioners in the building space and the running information of the air conditioners in different modes: including cooling power for fixed frequency air conditioner
Figure FDA0003801793450000011
Heating power
Figure FDA0003801793450000012
Refrigerating capacity
Figure FDA0003801793450000014
Heating capacity
Figure FDA0003801793450000015
For inverter air conditioner, high-frequency refrigeration power is included
Figure FDA0003801793450000016
Low frequency refrigeration power
Figure FDA0003801793450000017
High frequency heating power
Figure FDA0003801793450000018
Low frequency heating power
Figure FDA0003801793450000019
High frequency refrigerating capacity
Figure FDA00038017934500000110
Low frequency refrigerating capacity
Figure FDA00038017934500000111
High frequency heating capacity
Figure FDA00038017934500000112
Low frequency heat generation
Figure FDA00038017934500000113
The belonged building information comprises a building volume V and a building wall surface area S j And heat transfer coefficient C of building wall surface j (ii) a The user configuration information includes the optimal heating temperature
Figure FDA00038017934500000116
Optimum refrigeration temperature
Figure FDA00038017934500000115
Set operating time h of air conditioner s Setting an operation mode by the air conditioner;
s2, calculating the optimal heating temperature of the building space
Figure FDA00038017934500000117
Optimum refrigeration temperature
Figure FDA00038017934500000118
The heating capacity/cooling capacity Q required to be provided by the air-conditioning is specifically represented by the following formula:
Q＝Q n +Q s ，
wherein Q n Refrigerating capacity/heating capacity, Q, required for achieving an optimum refrigerating/heating temperature for a building space s Heat dissipation capacity in the process;
further, Q n ＝(Temp room -Temp best )×V×C air ，
Wherein V is the building volume, C air Is the specific heat capacity of the air,
Figure FDA0003801793450000013
further, Q s ＝Q c +Q a ，
Wherein Q c For heat dissipation, Q, calculated from the area of the building wall a Heat dissipation due to other factors;
further, the air conditioner is provided with a fan,
Figure FDA0003801793450000022
wherein S i Is the area of the wall surface of the building C i For the heat transfer coefficient of the building wall surface, i =1, 2, n is the number of the wall surfaces;
further, Q a ＝f(P num ,H air ,K room ,Temp room ,Temp out )，
Wherein P is num Number of people in the building space, H air Air humidity, K room For building space ventilation coefficient, temp room Is the indoor temperature, temp out Is outdoor temperature, Q a During calculation, historical data is collected, and the AI intelligent algorithm is combined to fit the functional relation between the heat dissipation capacity of the building space and relevant key influence factors, so that the partial heat dissipation capacity which cannot be calculated through a formula is calculated, and the Q is improved s Accuracy of the heat dissipation value;
s3, calculating the time h for the air conditioner to operate when the building space reaches the optimal refrigerating/heating temperature c The formula is as follows:
Figure FDA0003801793450000021
wherein Q is the refrigerating capacity/heating capacity required by the air conditioner, P is the refrigerating/heating power of the air conditioner, and E is the energy efficiency ratio of the refrigerating/heating of the air conditioner;
s4, calculating and setting air conditioner operation time h s The operation mode in hours comprises the following calculation steps:
s41, when h is c ≥h s When the air conditioner is operated, namely the time of the air conditioner operation is longer than the set air conditioner operation time when the building space reaches the optimal refrigerating/heating temperature, the air conditioner operation only needs to keep the refrigerating/heating mode operation;
s42, when h is c <h s When the air conditioner is running h s The ambient temperature of the building space reaches the optimal refrigerating/heating temperature after hours, and the operation h of the air conditioner needs to be calculated at the moment c An hourly mode of operation;
s43, air conditioner operation h c After hours, the ambient temperature of the building space reaches the optimal cooling/heating temperature, at which time the ambient temperature of the building space needs to be maintained at the optimal cooling/heating temperature, and the cooling capacity/heating capacity Q provided by the air conditioner needs to be provided j ＝[q 1 ,q 2 ,......,q k ]，q k For the kth hour, the air conditioning cooling capacity/heating capacity is k =1, 2, ·., and n, n = h s -h c Wherein the cooling capacity/heating capacity of the air conditioner is not less than the heat dissipation capacity in the process, so as to maintain the environment temperature of the building space at the optimal cooling/heating temperature, i.e. the air conditioner
Figure FDA00038017934500000312
Figure FDA00038017934500000313
S44, according to the calculationQ out of j I.e. the amount of cooling/heating that the air conditioner needs to provide per hour, in combination with the current air conditioning operation mode, and the high-frequency cooling power of each air conditioner in the building space
Figure FDA0003801793450000032
Low frequency refrigeration power
Figure FDA0003801793450000033
High frequency heating power
Figure FDA0003801793450000034
Low frequency heating power
Figure FDA0003801793450000035
High frequency refrigerating capacity
Figure FDA0003801793450000036
Low frequency refrigerating capacity
Figure FDA0003801793450000037
High frequency heating capacity
Figure FDA0003801793450000038
Low frequency heat production
Figure FDA0003801793450000039
Information, calculating the starting, stopping and running modes of all air conditioners in the building in the k hours in the future, and meeting the requirements
Figure FDA00038017934500000310
Wherein R is i In order to start and stop the air conditioner,
Figure FDA0003801793450000031
P i the operation power corresponding to different operation modes of the air conditioner; i is the running time of the air conditioner; num is the number of air conditioners in the building space; the calculated cooling/heating capacity of each air conditionerAnd the refrigerating/heating quantity which is not less than the refrigerating/heating quantity required to be provided by the air conditioner per hour needs to be met, and the refrigerating/heating quantity which is equal to or closest to the refrigerating/heating quantity required to be provided by the air conditioner per hour is the optimal operation strategy of the air conditioner;
s45, obtaining an optimal air conditioner operation strategy according to a genetic algorithm, wherein the starting and stopping states of all air conditioners in the building space corresponding to the kth hour are
Figure FDA00038017934500000314
Figure FDA00038017934500000315
The starting and stopping states of an ith air conditioner in the building space at the kth hour are set to be i =1, 2, i. All air-conditioning operation modes
Figure FDA00038017934500000311
The operation power of an ith air conditioner in the building space at the kth hour is i =1, 2, i.... And num, wherein num is the number of the air conditioners in the building space;
and S5, setting a timing task according to the calculated optimal air conditioner operation strategy, and controlling the start and stop of each air conditioner in the building air conditioner and the corresponding operation mode in a timing mode.
2. The method for realizing energy conservation based on causal inference cluster scheduling of the split air conditioner as claimed in claim 1, wherein: the indoor environment temperature Temp in the environment temperature information in S1 room And outdoor ambient temperature Temp out Acquiring data through a temperature sensor, and obtaining the outdoor environment temperature TEMP for n hours in the future j Acquired through a regional API interface provided by the weather station, wherein the outdoor ambient temperature TEMP is n hours in the future j ＝[Temp 1 ,Temp 2 ,......,Temp i ]，Temp i I =1, 2,... N, is the temperature value for the ith hour.
3. Method for achieving energy conservation based on causal inference cluster scheduling of split type air conditioner according to claim 2The method is characterized in that: in the S1, the number num of the air conditioners in the building space in the air conditioner configuration information is a user-defined numerical value according to an actual scene, the running information of the air conditioners in different modes is a user-defined numerical value according to actual configuration of the air conditioners, and the high-frequency refrigerating power
Figure FDA0003801793450000041
Figure FDA0003801793450000042
For the ith air conditioner high frequency cooling power (constant frequency air conditioner cooling power), i =1, 2, ·.. · num; low frequency refrigeration power
Figure FDA0003801793450000043
Figure FDA0003801793450000044
For the ith air conditioner low frequency cooling power (the fixed frequency air conditioner low frequency cooling power is 0), i =1, 2, ·. · num; high frequency refrigerating capacity
Figure FDA0003801793450000045
For the ith air conditioning high frequency cooling capacity (constant frequency air conditioning cooling capacity), i =1, 2, ·.. Num; low frequency refrigerating capacity
Figure FDA0003801793450000046
For the ith air conditioner low frequency refrigeration capacity (the fixed frequency air conditioner low frequency refrigeration capacity is 0), i =1, 2, ·.... Once.num; high frequency heating power
Figure FDA0003801793450000047
Figure FDA0003801793450000048
For the ith air conditioner high frequency heating power (constant frequency air conditioner heating power), i =1, 2, ·.. Num; low frequency heating power
Figure FDA0003801793450000049
Figure FDA00038017934500000410
For the ith air conditioner low frequency heating power (the fixed frequency air conditioner low frequency heating power is 0), i =1, 2, ·. · num; high frequency heating capacity
Figure FDA0003801793450000056
I =1, 2, ·.. Num for the ith air-conditioning high-frequency heating amount (fixed-frequency air-conditioning heating amount); low frequency heat generation
Figure FDA0003801793450000055
For the ith air conditioner low frequency heating value (the fixed frequency air conditioner low frequency heating value is 0), i =1, 2, ·.
4. The method for realizing energy conservation based on causal inference cluster scheduling of split air conditioners according to claim 3, wherein: in the S1, the building volume V and the building wall surface area S in the building information j And heat transfer coefficient C of building wall surface j Defining a value for a user according to an actual scene, wherein the area S of the wall surface of the building is defined j ＝[s 1 ,s 2 ,......,s i ]，s i The area of the ith wall surface is defined as i =1, 2, n, and n is the number of the wall surfaces; heat transfer coefficient of building wall surface C j ＝[c 1 ,c 2 ,......,c i ]，c i For the ith wall surface heat transfer coefficient, i =1, 2, and.
5. The method for realizing energy conservation based on causal inference cluster scheduling of split air conditioners according to claim 4, wherein: the optimal heating temperature in the user configuration information in the S1
Figure FDA0003801793450000054
Optimum refrigeration temperature
Figure FDA0003801793450000053
Set operating time h of air conditioner s And setting an operation mode of the air conditioner to be a numerical value defined by a user according to an actual scene.
6. The method for realizing energy conservation based on causal inference cluster scheduling of split air conditioners according to claim 1, wherein: in said S43
Figure FDA0003801793450000052
Is the h th c Outdoor temperature, temp. of + k hours best For optimum cooling/heating temperature, S i Is the area of the wall surface of the building C i I =1, 2, the.
Figure FDA0003801793450000051
The heat dissipation capacity caused by other factors in the k hour.
CN202210985121.0A 2022-08-17 2022-08-17 Energy-saving method for split air conditioner based on causal reasoning cluster scheduling Pending CN115540216A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117628664A (en) * 2023-12-15 2024-03-01 广州市赛科自动化控制设备有限公司 Indoor temperature and humidity control method and system based on purifying air conditioner

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117628664A (en) * 2023-12-15 2024-03-01 广州市赛科自动化控制设备有限公司 Indoor temperature and humidity control method and system based on purifying air conditioner

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