Master-slave game scheduling method, system, device, medium and product for air conditioning aggregators

Abstract

The present invention relates to the technical field of power systems and discloses a master-slave game scheduling method, system, device, medium, and product for air conditioning aggregator. The method constructs a user willingness model for participating in the air conditioning aggregator based on user expenditure satisfaction and temperature comfort, and constructs an air conditioning user participation scheduling optimization model with minimizing the expenditure costs of all users and minimizing the sum of the discomfort levels of all users as a first optimization goal. The method constructs an air conditioning aggregator scheduling model with maximizing the total benefits of the air conditioning aggregator participating in the reserve market and energy market as a second optimization goal, and constructs a master-slave game model between the air conditioning aggregator and the user. Based on the user willingness model for participating in the air conditioning aggregator, the master-slave game model is optimized and solved to obtain an optimal air conditioning control strategy, thereby fully considering user willingness, resolving the conflict of interest between the air conditioning aggregator and the user, and improving the robustness of the air conditioning aggregator scheduling.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a master-slave game scheduling method, system, equipment, medium and product for air conditioning aggregators. Background Art

[0002] During peak summer electricity demand, air conditioning loads can account for 30%-50% of the total grid load, posing a significant challenge to the power system. However, as a typical temperature-controlled load, air conditioning loads have excellent regulation characteristics. This makes them an ideal demand response resource, capable of providing upward or downward regulation when needed by the grid, effectively alleviating the imbalance between power supply and demand.

[0003] As a flexible and controllable resource, large-scale air conditioning loads must be aggregated and regulated by air conditioning aggregators to participate in the electricity market. This allows them to reduce electricity demand during peak periods and moderately increase load during off-peak periods. This approach, while shaving peaks and filling valleys, promotes safe and stable grid operation, and generates economic benefits for users while reducing electricity costs. Air conditioning aggregators, acting as a bridge between users and distribution network operators, participate in distribution network dispatching and operation, helping to improve distribution network performance and provide the power system with more competitive regulation capabilities.

[0004] At present, although existing studies have explored the issue of interest coordination between air-conditioning aggregators and users through methods such as game theory, they generally ignore the impact of changes in user participation willingness on the aggregation ability of aggregators, which leads to poor robustness of air-conditioning aggregator scheduling. Summary of the Invention

[0005] In view of this, the present invention provides a master-slave game scheduling method, system, device, medium and product for air-conditioning aggregators, which solves the technical problem that the existing air-conditioning aggregator scheduling ignores the impact of changes in user participation willingness on the aggregator's aggregation ability, which leads to poor robustness of air-conditioning aggregator scheduling.

[0006] A first aspect of the present invention provides a master-slave game scheduling method for air conditioning aggregators, comprising:

[0007] Based on users' spending satisfaction and temperature comfort, a model of users' willingness to participate in air conditioning aggregators is constructed;

[0008] Taking the minimization of all users' expenditure costs and the minimization of the sum of all users' discomfort levels as the first optimization goal, and the balanced operation of air conditioning as the first constraint, an air conditioning user participation scheduling optimization model is constructed;

[0009] Taking the maximization of the total revenue of air-conditioning aggregators participating in the reserve market and energy market as the second optimization objective and the electricity price limit of air-conditioning aggregators as the second constraint, a scheduling model for air-conditioning aggregators is constructed.

[0010] According to the air-conditioning user participation scheduling optimization model and the air-conditioning aggregator's scheduling model, a master-slave game model between the air-conditioning aggregator and the user is constructed. Based on the user's willingness model to participate in the air-conditioning aggregator, the master-slave game model is optimized and solved to obtain the optimal air-conditioning control strategy.

[0011] Preferably, the step of constructing a user willingness model for participating in an air conditioning aggregator based on the user's spending satisfaction and temperature comfort level includes:

[0012] Determining the user's discomfort level based on the user's air-conditioning indoor temperature and the initial value of the air-conditioning temperature; wherein the discomfort level is used to represent the user's temperature comfort;

[0013] Determining the user's expenditure satisfaction based on the user's expenditure costs before and after participating in the air conditioning aggregator's scheduling;

[0014] Normalizing the discomfort level and the expenditure satisfaction respectively to obtain a normalized discomfort level and a normalized expenditure satisfaction;

[0015] A weighted calculation is performed on the normalized discomfort level and the normalized expenditure satisfaction to obtain a model of the user's willingness to participate in air conditioning aggregators.

[0016] Preferably, the first objective function corresponding to the first optimization objective is:

[0017]

[0018] Where, The benefits for users to participate in the air conditioning aggregator scheduling, Cost to users, The user's discomfort level;

[0019] in,

[0020] Where, The electricity cost for users; The income obtained by users from participating in the scheduling of air conditioning aggregators;

[0021]

[0022] Where N is the number of users, i is the user index, t is the time, is the initial time, T is the total time period, for The electricity price of user i at the moment, for The air conditioning power of user i at the moment;

[0023]

[0024] Where, 、 They are The upper and lower reserve power generation capacities provided by user i to the air conditioning aggregator at the moment; 、 for The compensation price for upper and lower backup provided by the air conditioning aggregator to user i at that moment;

[0025]

[0026] Where, for The indoor temperature of user i's air conditioner at the moment; The initial value of the air conditioning temperature set by user i.

[0027] Preferably, the first constraint condition includes an air-conditioning power balance constraint, an air-conditioning indoor temperature limit constraint, an air-conditioning power limit constraint, and an air-conditioning standby power generation capacity limit constraint.

[0028] Preferably, the second objective function corresponding to the second optimization objective is:

[0029]

[0030] Where, For the benefits of air conditioning aggregators, represents the revenue earned by air conditioning aggregators from providing backup generation capacity to the reserve market, represents the revenue of air-conditioning aggregators from selling electricity to users, represents the cost of electricity purchased from the grid by AC aggregators; The income obtained by users from participating in the scheduling of air conditioning aggregators;

[0031] in,

[0032]

[0033]

[0034] Where, The electricity cost for users, It represents the electricity price given by the power grid to the air-conditioning aggregator. for The air conditioning power of user i at the moment; is the initial moment, 、 are the upper and lower standby compensation prices that the air-conditioning aggregator gives to all users at time t; 、 They are The upper and lower reserve power generation capacity provided by all users to the air conditioning aggregator at all times;

[0035] The second constraint condition includes the upper and lower standby compensation price limit constraints given by the air conditioning aggregator.

[0036] Preferably, the method of constructing a master-slave game model between air conditioner aggregator and user based on the air conditioner user participation scheduling optimization model and the air conditioner aggregator scheduling model, and optimizing and solving the master-slave game model based on the user willingness model to participate in the air conditioner aggregator to obtain the optimal air conditioner control strategy includes:

[0037] With the air conditioner aggregator as the leader in the game and the user as the follower, a master-slave game model between the air conditioner aggregator and the user is constructed based on the air conditioner user participation scheduling optimization model and the air conditioner aggregator scheduling model. The master-slave game model between the air conditioner aggregator and the user is:

[0038]

[0039] Where G is the master-slave game model between air-conditioning aggregators and users, For the game player, Strategies for AC aggregators, For user strategies, For the benefits of air conditioning aggregators, Profits for users who participate in air conditioning aggregator scheduling;

[0040] in,

[0041]

[0042]

[0043] Where, For air conditioning aggregators, For air-conditioning users; 、 They are The upper and lower reserve power generation capacities provided by user i to the air conditioning aggregator at the moment; 、 for The compensation price for upper and lower backup provided by the air conditioning aggregator to user i at that moment;

[0044] Initializing and setting an initial value of the standby compensation price provided by the air conditioner user formulated by the air conditioner aggregator, and using the initial value of the standby service compensation price as the current standby compensation price;

[0045] Inputting the current reserve compensation price into the air conditioning user participation scheduling optimization model, optimizing and solving the air conditioning user participation scheduling optimization model to obtain the temperature adjustment strategy for each time period of the air conditioning cluster and the reserve power generation capacity regulated by the air conditioning users participating in the air conditioning aggregator;

[0046] Determining the user's willingness to participate in the air conditioning aggregator's regulation based on the user's willingness model to participate in the air conditioning aggregator's regulation according to the temperature regulation strategy and the spare power generation capacity of the air conditioning user participating in the air conditioning aggregator's regulation;

[0047] According to the user's willingness to participate in the regulation of the air conditioning aggregator, the spare power generation capacity of the air conditioning user participating in the regulation of the air conditioning aggregator is corrected to obtain the actual spare power generation capacity of the air conditioning user participating in the regulation of the air conditioning aggregator;

[0048] Inputting the actual reserve power generation capacity of the air conditioner user participating in the air conditioner aggregator's regulation into the air conditioner aggregator's dispatch model, optimizing the dispatch model of the air conditioner aggregator, and obtaining an optimized reserve compensation price;

[0049] The optimized standby compensation price is updated to the current standby compensation price, and the current standby compensation price is input into the air-conditioning user participation scheduling optimization model, the air-conditioning user participation scheduling optimization model is optimized and solved, and the steps of obtaining the temperature regulation strategy of the air-conditioning cluster for each time period and the standby power generation capacity regulated by the air-conditioning users participating in the regulation of the air-conditioning aggregator are iterated until the preset iteration condition is reached, the iteration stops, and the temperature regulation strategy of the air-conditioning cluster for each time period and the standby power generation capacity regulated by the air-conditioning users participating in the regulation of the air-conditioning aggregator are output.

[0050] In a second aspect, the present invention further provides a master-slave game scheduling system for air-conditioning aggregators, comprising:

[0051] The willingness model building module is used to build a model of users' willingness to participate in air conditioning aggregators based on their spending satisfaction and temperature comfort;

[0052] The user model building module is used to build an air conditioning user participation scheduling optimization model with the minimization of all user expenditure costs and the minimization of the sum of all user discomfort levels as the first optimization goal and the balanced operation of the air conditioning as the first constraint condition;

[0053] an aggregator model building module, which is used to build a dispatch model for air conditioning aggregators, taking maximizing the total revenue of air conditioning aggregators participating in the reserve market and energy market as the second optimization objective and taking the electricity price limit of air conditioning aggregators as the second constraint;

[0054] The control optimization module is used to construct a master-slave game model between air-conditioning aggregators and users based on the air-conditioning user participation scheduling optimization model and the air-conditioning aggregator's scheduling model, and to optimize and solve the master-slave game model based on the user's willingness model to participate in the air-conditioning aggregator to obtain the optimal air-conditioning control strategy.

[0055] In a third aspect, the present invention further provides an electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor executes the steps of the master-slave game scheduling method for air-conditioning aggregators as described in the first aspect.

[0056] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the steps of the master-slave game scheduling method for air-conditioning aggregators as described in the first aspect.

[0057] In a fifth aspect, the present invention also provides a computer program product, comprising a computer program stored on a non-transitory computer-readable storage medium, wherein the computer program comprises program instructions, wherein when the program instructions are executed by a computer, the computer executes the steps of the master-slave game scheduling method for air-conditioning aggregators as described in the first aspect.

[0058] As can be seen from the above technical solutions, the present invention constructs a user willingness model for participating in air conditioning aggregators based on user expenditure satisfaction and temperature comfort, and takes minimizing the expenditure costs of all users and the sum of the discomfort levels of all users as the first optimization goal, and takes balanced air conditioning operation as the first constraint condition, to construct an air conditioning user participation scheduling optimization model, takes maximizing the total benefits of air conditioning aggregators participating in the reserve market and energy market as the second optimization goal, and takes the electricity price limit of the air conditioning aggregator as the second constraint condition, to construct an air conditioning aggregator scheduling model, and constructs a master-slave game model between air conditioning aggregators and users based on the air conditioning user participation scheduling optimization model and the air conditioning aggregator scheduling model. Based on the user willingness model for participating in the air conditioning aggregator, the master-slave game model is optimized and solved to obtain the optimal air conditioning control strategy, thereby fully considering user willingness and resolving the conflict of interest between air conditioning aggregators and users. By constructing the master-slave game model between air conditioning aggregators and users, the economic efficiency of air conditioning aggregators and air conditioning users can be improved, the robustness of air conditioning aggregator scheduling can be improved, and the economic operation of the power grid can be promoted. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0060] Figure 1 This is a diagram illustrating an application environment of a master-slave game scheduling method for air-conditioning aggregators provided by an embodiment of the present invention;

[0061] Figure 2 A flowchart of a master-slave game scheduling method for air-conditioning aggregators provided by an embodiment of the present invention;

[0062] Figure 3 A schematic diagram of a Stackelberg game model provided by an embodiment of the present invention;

[0063] Figure 4 A flowchart for solving the master-slave game model provided by an embodiment of the present invention;

[0064] Figure 5 A schematic diagram of the structure of a master-slave game scheduling system for air-conditioning aggregators provided by an embodiment of the present invention;

[0065] Figure 6 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0066] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0067] The master-slave game scheduling method for air-conditioning aggregators provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal 101 communicates with the server 102 through the network. The data storage system can store the data that the server 102 needs to process. The data storage system can be integrated on the server 102, or it can be placed on the cloud or other network servers. The terminal 101 or the server 102 constructs a user willingness model for participating in the air conditioning aggregator based on the user's expenditure satisfaction and temperature comfort; takes the minimization of all user expenditure costs and the minimization of the sum of all user discomfort levels as the first optimization goal, and takes the balanced operation of the air conditioning as the first constraint condition, to construct an air conditioning user participation scheduling optimization model; takes the maximization of the total profit of the air conditioning aggregator participating in the reserve market and energy market as the second optimization goal, and takes the electricity price limit of the air conditioning aggregator as the second constraint condition, to construct an air conditioning aggregator scheduling model; based on the air conditioning user participation scheduling optimization model and the air conditioning aggregator scheduling model, a master-slave game model of the air conditioning aggregator and the user is constructed, and based on the user's willingness model for participating in the air conditioning aggregator, the master-slave game model is optimized and solved to obtain the optimal air conditioning control strategy.

[0068] The terminal 101 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and the like.

[0069] The server 102 may be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services.

[0070] like Figure 2 As shown, the embodiment of the present application provides a master-slave game scheduling method for air-conditioning aggregators, which is applied to Figure 1 The terminal 101 or the server 102 in the example is used to illustrate the method, which includes the following steps S1 to S4.

[0071] Step S1: Construct a user willingness model for participating in air conditioning aggregators based on the user's spending satisfaction and temperature comfort.

[0072] Expenditure satisfaction refers to a user's acceptance of the electricity bill after participating in load regulation, and this can be measured by setting a satisfaction threshold. Temperature comfort refers to a user's perception of indoor temperature, and this can be assessed by setting a temperature comfort threshold. When building a model to measure user willingness to participate in air conditioning aggregators, comprehensively considering both expenditure satisfaction and temperature comfort can more comprehensively reflect users' actual needs, enhance their enthusiasm for load regulation, and enhance the effectiveness of scheduling strategies.

[0073] Step S2: Taking minimizing the expenditure costs of all users and minimizing the sum of the discomfort levels of all users as the first optimization goal and taking the balanced operation of the air conditioner as the first constraint condition, an air conditioner user participation scheduling optimization model is constructed.

[0074] The first optimization goal is to minimize both user electricity bills and discomfort by rationally scheduling air conditioner users' electricity usage, while ensuring user comfort and proper air conditioning operation. This not only meets user needs but also helps improve the overall scheduling efficiency of air conditioner aggregators.

[0075] The first constraint, balanced air conditioning operation, requires the air conditioning system to maintain a stable operating state to avoid damage to the equipment due to over-adjustment or frequent starts and stops. This constraint ensures the feasibility and safety of the scheduling strategy in practical applications.

[0076] Step S3: maximizing the total revenue of the air-conditioning aggregator from participating in the reserve market and the energy market is taken as the second optimization objective, and the electricity price limit of the air-conditioning aggregator is taken as the second constraint condition to construct a scheduling model for the air-conditioning aggregator.

[0077] The second optimization goal is to maximize the total revenue of air conditioning aggregators by optimizing their participation strategies in the reserve market and energy market, which helps improve the economic benefits and market competitiveness of air conditioning aggregators.

[0078] The second constraint, the price limit for AC aggregators, requires them to adhere to certain rules or restrictions when setting electricity prices, such as government-guided prices and market competition. This constraint ensures that dispatch strategies are implemented legally and in compliance with regulations, avoiding market disputes and policy risks arising from unreasonable electricity prices.

[0079] Step S4: Based on the air-conditioning user participation scheduling optimization model and the air-conditioning aggregator's scheduling model, a master-slave game model between the air-conditioning aggregator and the user is constructed. Based on the user's willingness model to participate in the air-conditioning aggregator, the master-slave game model is optimized and solved to obtain the optimal air-conditioning control strategy.

[0080] Among them, the air-conditioning aggregator, as the leader in the game, first formulates the pricing strategy, and the air-conditioning users, as followers, quantify the backup power generation capacity according to the price incentives given by the air-conditioning aggregator, and realize the update of backup power generation capacity for different pricing strategies; the air-conditioning aggregator optimizes pricing based on the backup power generation capacity feedback provided by the air-conditioning users, and re-formulates the backup compensation price strategy, thereby constructing a master-slave game model between the air-conditioning aggregator and the user.

[0081] It should be noted that the embodiment of the present application constructs a model of the user's willingness to participate in air conditioning aggregators based on the user's expenditure satisfaction and temperature comfort, and takes minimizing the expenditure costs of all users and minimizing the sum of the discomfort levels of all users as the first optimization goal, and takes the balanced operation of air conditioning as the first constraint condition, to construct an air conditioning user participation scheduling optimization model, takes maximizing the total benefits of the air conditioning aggregator's participation in the reserve market and energy market as the second optimization goal, and takes the electricity price limit of the air conditioning aggregator as the second constraint condition, to construct an air conditioning aggregator scheduling model, and according to the air conditioning user participation scheduling optimization model and the air conditioning aggregator scheduling model, constructs a master-slave game model of the air conditioning aggregator and the user, and based on the user's willingness model to participate in the air conditioning aggregator, seeks the best solution for the master-slave game model to obtain the optimal air conditioning control strategy, thereby fully considering the user's willingness and resolving the conflict of interest between the air conditioning aggregator and the user, and by constructing the master-slave game model of the air conditioning aggregator and the user, it is possible to improve the economic efficiency of the air conditioning aggregator and the air conditioning user, improve the robustness of the air conditioning aggregator scheduling, and promote the economic operation of the power grid.

[0082] In some embodiments, a user willingness model for participating in an air conditioning aggregator is constructed based on the user's spending satisfaction and temperature comfort, including:

[0083] Step S101: Determine the user's discomfort level based on the user's air-conditioning indoor temperature and the initial value of the air-conditioning temperature; wherein the discomfort level is used to represent the user's temperature comfort.

[0084] Specifically, the Fanger thermal comfort model can be used to quantify the user's discomfort. Since discomfort is mainly related to indoor temperature, the discomfort level of a single user can be expressed as:

[0085] Where, Represents the user's discomfort level; represent Moment The indoor temperature of each user; Representative The initial value of the air conditioning temperature set by the user.

[0086] Step S102: Determine the user's expenditure satisfaction based on the user's expenditure costs before and after participating in the air conditioning aggregator's scheduling.

[0087] Among them, the user's expenditure satisfaction is related to the user's expenditure cost after participating in the air conditioning aggregator's scheduling. The higher the expenditure satisfaction, the more the user's expenditure cost is reduced after participating in the scheduling compared to before the scheduling. When the user's expenditure cost after participating in the scheduling is higher than before the scheduling, the user's expenditure satisfaction is 0, that is:

[0088]

[0089] Where, Represents user spending satisfaction; represent Moment The expenditure cost of each air conditioner before it participates in the dispatch of air conditioner aggregators; represent Moment The expenditure cost of each air conditioner after it participates in the scheduling of the air conditioner aggregator.

[0090] Step S103: normalize the discomfort level and the expenditure satisfaction respectively to obtain a normalized discomfort level and a normalized expenditure satisfaction.

[0091] Among them, due to the differences in the dimensions and meanings of discomfort level and expenditure satisfaction, they need to be normalized first, and the result is:

[0092]

[0093]

[0094] Where, Represents the normalized user discomfort level; Represents the maximum value of the user's discomfort level; Represents the minimum value of the user's discomfort level; Represents the normalized user's spending satisfaction; Represents the maximum value of the user's spending satisfaction; Represents the minimum value of user's spending satisfaction.

[0095] Step S104: Perform weighted calculation on the normalized discomfort level and the normalized expenditure satisfaction to obtain a model of the user's willingness to participate in air conditioning aggregators.

[0096] Based on the user expenditure satisfaction model and the temperature comfort model, we comprehensively measure user psychology from the perspective of user economy and comfort, and establish a model of user willingness to participate in the regulation of air conditioning aggregators. The higher the user's discomfort level, the lower the user's willingness; the higher the user's expenditure satisfaction, the higher the user's willingness. Therefore, we establish a model of user willingness to participate in air conditioning aggregators. The user willingness model for participating in air conditioning aggregators is:

[0097]

[0098] Where, For users' willingness to participate in air conditioning aggregators, 、 are the weights of user economy and comfort respectively.

[0099] In some embodiments, the air conditioning user participation scheduling optimization model comprehensively considers two objectives: minimizing the expenditure costs of all users and minimizing the sum of the discomfort levels of all users. The first objective function corresponding to the first optimization objective is:

[0100]

[0101] Where, The benefits for users to participate in the air conditioning aggregator scheduling, Cost to users, The user's discomfort level;

[0102] in,

[0103] Where, The electricity cost for users; The income obtained by users from participating in the scheduling of air conditioning aggregators;

[0104]

[0105] Where N is the number of users, i is the user index, t is the time, is the initial time, T is the total time period, for The electricity price of user i at the moment, for The air conditioning power of user i at the moment;

[0106]

[0107] Where, 、 They are The upper and lower reserve power generation capacities provided by user i to the air conditioning aggregator at the moment; 、 for The compensation price for upper and lower backup provided by the air conditioning aggregator to user i at that moment;

[0108] The upper and lower backup power generation capacities provided to air-conditioning aggregators are additional power generation capabilities that can be called upon in the event of a sudden increase in system load. This refers to the upward (increase in power supply or decrease in electricity demand) reserve capacity that can be adjusted by the user's air-conditioning side, and requires subsequent optimization to determine.

[0109]

[0110] Where, for The indoor temperature of user i's air conditioner at the moment; The initial value of the air conditioning temperature set by user i.

[0111] Among them, the first constraint condition includes air conditioning power balance constraint, air conditioning indoor temperature limit constraint, air conditioning power limit constraint and air conditioning standby power generation capacity limit constraint.

[0112] The air conditioning power balance constraint refers to the power balance state that the air conditioning system must maintain during actual operation. Specifically, the input power and output power of the air conditioning system must be equal to ensure stable operation. Setting this constraint helps prevent overload or failure of the air conditioning system due to power imbalance.

[0113] The air conditioning system's indoor temperature limit constraint means the system must maintain the indoor temperature within the user-defined temperature range to ensure user comfort. If the indoor temperature exceeds the set range, the air conditioning system must adjust accordingly to meet the user's desired indoor temperature.

[0114] Air conditioning power limits ensure that the system's power output remains within its rated power range, preventing damage to the system or reduced cooling performance due to excessive or insufficient power. This constraint helps maintain the system's normal operation and extend its service life.

[0115] The air conditioning system's backup generation capacity limit constraint requires that the backup generation capacity provided by the air conditioning system, when participating in dispatch, should be within a certain range to ensure that the system can respond normally to dispatch instructions in an emergency. This constraint helps improve the reliability and stability of the air conditioning system and ensure the safe operation of the power system.

[0116] Among them, the air conditioning power balance constraint, air conditioning indoor temperature limit constraint, and air conditioning power limit constraint are:

[0117]

[0118]

[0119]

[0120] Where, express The air conditioning power of user i at the moment; represents the energy efficiency ratio of the air conditioner of user i; 、 denote the equivalent thermal resistance and heat capacity of the air conditioner of user i respectively; 、 Indicates the maximum and minimum indoor temperature that user i can accept; 、 represents the maximum and minimum values ​​of the air conditioning power of user i, is the outdoor temperature; is the indoor temperature that household i can accept at time t+1; is the outdoor temperature at time t+1; for +1 is the air conditioning power of user i at time 1.

[0121] The air conditioning standby power generation capacity limit constraint is:

[0122]

[0123]

[0124]

[0125] Where, and It is a 0-1 variable, indicating the usage status of the upper and lower reserve power generation capacities respectively. The upper and lower reserve power generation capacities cannot be used at the same time.

[0126] In some embodiments, the scheduling model of the air conditioning aggregator takes maximizing the total revenue from participating in the reserve market and the energy market as the optimization goal, and the second objective function corresponding to the second optimization goal is:

[0127]

[0128] Where, For the benefits of air conditioning aggregators, represents the revenue earned by air conditioning aggregators from providing backup generation capacity to the reserve market, represents the revenue of air-conditioning aggregators from selling electricity to users, represents the cost of electricity purchased from the grid by AC aggregators; The income obtained by users from participating in the scheduling of air conditioning aggregators;

[0129] in,

[0130]

[0131]

[0132] Where, The electricity cost for users, It represents the electricity price given by the power grid to the air-conditioning aggregator. for The air conditioning power of user i at the moment; is the initial moment, 、 are the upper and lower standby compensation prices that the air-conditioning aggregator gives to all users at time t; 、 They are The upper and lower reserve power generation capacity provided by all users to the air conditioning aggregator at all times;

[0133] The second constraint includes the upper and lower standby compensation price limit constraints given by the air conditioning aggregator.

[0134] Among them, the upper and lower standby compensation price limits given by air conditioning aggregators are:

[0135]

[0136]

[0137] Where, and Indicates the upper and lower limits of the standby compensation price given by the air conditioning aggregator; and Indicates the upper and lower limits of the standby compensation price given by the air conditioning aggregator.

[0138] In some embodiments, as Figure 3~Figure 4 As shown in the figure, based on the air conditioning user participation scheduling optimization model and the air conditioning aggregator scheduling model, a master-slave game model between the air conditioning aggregator and the user is constructed. Based on the user willingness model for participating in the air conditioning aggregator, the master-slave game model is optimized and solved to obtain the optimal air conditioning control strategy, including:

[0139] Step S401: With the air conditioner aggregator as the leader in the game and the user as the follower, a master-slave game model between the air conditioner aggregator and the user is constructed based on the air conditioner user participation scheduling optimization model and the air conditioner aggregator's scheduling model;

[0140] Among them, such as Figure 3 As shown in the figure, the AC aggregator, as the leader in the game, first formulates the pricing strategy. AC users, as followers, quantify their reserve generation capacity based on the price incentives provided by the AC aggregator, thus updating the reserve generation capacity for different pricing strategies. The AC aggregator optimizes pricing based on the reserve generation capacity feedback provided by the AC users, and re-formulates the reserve compensation pricing strategy. Therefore, a Stackelberg game model of the master-slave game is established, that is, the master-slave game model between AC aggregators and users is:

[0141]

[0142] Where G is the master-slave game model between air-conditioning aggregators and users, For the game player, Strategies for AC aggregators, For user strategies, For the benefits of air conditioning aggregators, Profits for users who participate in air conditioning aggregator scheduling;

[0143] in,

[0144]

[0145]

[0146] Where, For air conditioning aggregators, For air-conditioning users; 、 They are The upper and lower reserve power generation capacities provided by user i to the air conditioning aggregator at the moment; 、 for The upper and lower backup compensation prices given by the air conditioning aggregator to user i at this moment.

[0147] Users make optimal decisions based on the load aggregator's strategy, and the load aggregator optimizes pricing based on user feedback, ultimately reaching a Stackelberg equilibrium. The equilibrium satisfies the following conditions:

[0148]

[0149] Where, is the optimal strategy of the air-conditioning aggregator, The optimal strategy for the user, is the revenue of the air-conditioning aggregator under the control of the optimal strategy of the air-conditioning aggregator and the optimal strategy of the user, is the revenue of the air-conditioning aggregator under the control of the air-conditioning aggregator's strategy and the user's optimal strategy, The benefits of users participating in the air conditioning aggregator's scheduling under the control of the air conditioning aggregator's optimal strategy and the user's strategy.

[0150] Step S402: Initialize and set the initial value of the standby compensation price provided by the air conditioner user formulated by the air conditioner aggregator, and use the initial value of the standby service compensation price as the current standby compensation price.

[0151] Step S403: Input the current standby compensation price into the air-conditioning user participation scheduling optimization model, and seek an optimal solution for the air-conditioning user participation scheduling optimization model to obtain the temperature adjustment strategy for each time period of the air-conditioning cluster and the standby power generation capacity regulated by the air-conditioning user participation in the air-conditioning aggregator.

[0152] Without considering the user's willingness to participate in the air conditioning aggregator model, the current standby compensation price As the input of the air-conditioning user participation scheduling optimization model, the spare power generation capacity of the air-conditioning user is optimized, and the temperature adjustment strategy of the air-conditioning cluster at each time period and the spare power generation capacity of the air-conditioning user participating in the air-conditioning aggregator regulation are output. .

[0153] The temperature regulation strategy for the air conditioning cluster during each time period is based on optimizing the air conditioning system power and indoor temperature, while meeting the constraints of the air conditioning indoor temperature limit, air conditioning power limit, and air conditioning backup power generation capacity limit. This strategy is designed to achieve the goal of enabling air conditioning users to participate in scheduling optimization. This strategy aims to balance user comfort and economic needs while ensuring the stable operation of the air conditioning system and the safe scheduling of the power system.

[0154] Step S404: Based on the user willingness model for participating in the air conditioning aggregator, the user's willingness to participate in the air conditioning aggregator's regulation is determined according to the temperature adjustment strategy and the spare power generation capacity of the air conditioning user participating in the air conditioning aggregator's regulation.

[0155] Among them, the user's willingness to participate in the regulation of air-conditioning aggregators is calculated based on the temperature adjustment strategy and the backup power generation capacity provided by the user, combined with the weights of the user's economy and comfort, through the user's willingness model to participate in air-conditioning aggregators.

[0156] After obtaining the temperature regulation strategy and air-conditioning users participating in the regulation of air-conditioning aggregators, the spare power generation capacity Finally, the temperature regulation strategy includes the provision of backup power generation capacity by air-conditioning users and the temperature set point that needs to be adjusted. The discomfort level is mainly related to the indoor temperature. The user discomfort level is expressed as:

[0157]

[0158] in, That is, it is set through the temperature adjustment strategy, which shows that the temperature adjustment strategy directly affects the user's comfort experience. The greater the deviation from the comfortable temperature range, the lower the user's willingness.

[0159] At the same time, the spare power generation capacity affects the expenditure satisfaction by affecting the economic benefits of users. In general, the spare power generation capacity is proportional to the compensation income, and the expenditure cost after participating in the air-conditioning aggregator dispatch should be the actual expenditure cost after participating in the air-conditioning aggregator dispatch - compensation income. Therefore, the spare power generation capacity is proportional to the expenditure cost after participating in the air-conditioning aggregator dispatch. The relationship is:

[0160]

[0161] Where, For backup power generation capacity, is the cost coefficient, which is generally positive. is the actual expenditure cost after dispatching by participating air-conditioning aggregators. To compensate for the income, The expenditure cost after dispatching by the air-conditioning aggregator is equal to Among them, the cost coefficient To convert dimensions, such as cost coefficient It is a composite dimension of "cost / power" to make the dimensions of both sides consistent.

[0162] Users can receive compensation for providing backup generation capacity. When users receive compensation for providing backup generation capacity, the more the compensation exceeds the additional costs, the higher their willingness to participate in regulation. This user willingness model for participating in air conditioning aggregator participation transforms the subjective experience of air conditioning users into a quantitative indicator of their willingness to participate, which is then reflected in their decisions about backup generation capacity, revealing their willingness to participate in regulation by air conditioning aggregators.

[0163] If the user's willingness is high, it means that the user is relatively satisfied with the current temperature adjustment strategy and standby compensation price, and is willing to actively participate in the regulation of the air-conditioning aggregator; conversely, if the user's willingness is low, it may be necessary to adjust the standby compensation price or temperature adjustment strategy to improve user participation and satisfaction.

[0164] Step S405: According to the user's willingness to participate in the regulation of the air conditioning aggregator, the spare power generation capacity of the air conditioning user participating in the regulation of the air conditioning aggregator is corrected to obtain the actual spare power generation capacity of the air conditioning user participating in the regulation of the air conditioning aggregator.

[0165] Among them, the compensation price and backup generation capacity And temperature adjustment strategy, calculate the user's willingness to participate By joining the will , update the actual spare power generation capacity of air-conditioning users participating in the regulation of air-conditioning aggregators .

[0166] Specifically, get the compensation price and backup generation capacity and temperature regulation strategies, through the willingness For backup generating capacity Make corrections to get the actual available backup power generation capacity:

[0167]

[0168] Where, 、 is the actual spare capacity after correction.

[0169] Based on user willingness, the degree of participation in regulation is dynamically adjusted, and further feedback is given to load aggregators for pricing optimization, thus building a linkage mechanism among willingness, capacity and price.

[0170] Therefore, although the willingness is not initially considered in the user response optimization stage of the model, after the user willingness is calculated, the actual backup power generation capacity is dynamically updated through the above-mentioned correction formula, so that the final control strategy fully reflects the influence of the user's subjective willingness.

[0171] Step S406: Input the actual standby power generation capacity of the air conditioner users participating in the air conditioner aggregator's regulation into the air conditioner aggregator's dispatch model, optimize the air conditioner aggregator's dispatch model, and obtain an optimized standby compensation price.

[0172] Among them, the actual reserve power generation capacity Input the dispatch model of the air-conditioning aggregator, use the mathematical solver to find the optimal solution for the dispatch model of the air-conditioning aggregator, obtain the optimized standby compensation price, and update the compensation price. .

[0173] Step S407: Update the optimized standby compensation price to the current standby compensation price, and input the current standby compensation price into the air-conditioning user participation scheduling optimization model, seek and solve the air-conditioning user participation scheduling optimization model, and iterate the steps of obtaining the temperature regulation strategy of the air-conditioning cluster for each time period, and the standby power generation capacity of the air-conditioning users participating in the regulation of the air-conditioning aggregator until the preset iteration condition is reached, stop the iteration, and output the temperature regulation strategy of the air-conditioning cluster for each time period and the standby power generation capacity of the air-conditioning users participating in the regulation of the air-conditioning aggregator.

[0174] Among them, the price will be compensated The backup power generation capacity of air-conditioning users is optimized as input, and the above steps are repeated until the preset iteration conditions are met.

[0175] Among them, the iteration conditions are set, and the expected reserve benefits of air-conditioning users participating in the regulation of aggregators are used as the model convergence indicator:

[0176]

[0177] Where, is the expected reserve income of air-conditioning users participating in the aggregator regulation in the kth iteration; ε is the convergence threshold.

[0178] Among them, the optimal air-conditioning control strategy includes the temperature adjustment strategy of the air-conditioning cluster in each period and the spare power generation capacity regulated by air-conditioning users participating in the control of the air-conditioning aggregator.

[0179] In order to prove the effectiveness of the master-slave game scheduling method of the air-conditioning aggregator proposed in this application, the embodiment of this application studies the potential of regulating and controlling the provision of spare power generation capacity for a cluster of 100 air conditioners participating in the air-conditioning load aggregator. The air-conditioning load parameters obey a uniform distribution within the range shown in Table 1. In the pricing optimization, the maximum and minimum limits of the compensation price formulated by the Economic Value Added (EVA) are set to 0.5 yuan / (kW·h) and 0 yuan / (kW·h), respectively. R is the spare power generation capacity, C is the expenditure cost of the air conditioner after participating in the air-conditioning aggregator scheduling, and P is the compensation price. is the indoor temperature of the air-conditioning environment, is the proportional coefficient of load distribution, The cooling / heating efficiency of the air conditioner.

[0180] Table 1 Air conditioning equipment parameters

[0181]

[0182] According to the method proposed in this invention, the optimal pricing strategy for maximizing the dual-objective benefits obtained through the master-slave game between air-conditioning aggregators and air-conditioning users can be obtained. At the same time, the optimal results are shown in Table 2, which correspond to the upper and lower backup power generation capacities that air-conditioning users can provide under the electricity price incentive.

[0183] Table 2 Optimal control strategy

[0184]

[0185] The regulation results show that, taking into account user preferences, air conditioning load aggregators set higher upper reserve compensation prices during peak demand periods to incentivize users to provide more regulation capacity. During low-load periods, aggregators use higher lower reserve compensation prices to encourage users to proactively increase their electricity consumption, thereby unlocking regulation potential. Overall, reserve generation capacity exhibits a favorable response to price changes, demonstrating the effectiveness of this strategy in balancing user preferences with economic efficiency.

[0186] Based on the same inventive concept, an embodiment of the present application also provides an air-conditioning aggregator master-slave game scheduling system for implementing the above-mentioned air-conditioning aggregator master-slave game scheduling method.

[0187] The implementation solution provided by this system to solve the problem is similar to the implementation solution recorded in the above method. Therefore, the specific limitations in the embodiments of the master-slave game scheduling system for one or more air-conditioning aggregators provided below can be found in the above limitations on the master-slave game scheduling method for air-conditioning aggregators, and will not be repeated here.

[0188] like Figure 5As shown, the embodiment of the present application provides a master-slave game scheduling system for air-conditioning aggregators, including:

[0189] The willingness model building module 100 is used to build a user willingness model for participating in air conditioning aggregators based on the user's spending satisfaction and temperature comfort;

[0190] The user model building module 200 is used to build an air conditioning user participation scheduling optimization model with the minimization of all user expenditure costs and the minimization of the sum of all user discomfort levels as the first optimization goal and the balanced operation of the air conditioner as the first constraint condition;

[0191] an aggregator model building module 300 for building a scheduling model for the air conditioning aggregator, taking maximizing the total revenue of the air conditioning aggregator from participating in the reserve market and the energy market as a second optimization objective and taking the electricity price limit of the air conditioning aggregator as a second constraint;

[0192] The control optimization module 400 is used to construct a master-slave game model between air conditioning aggregators and users based on the air conditioning user participation scheduling optimization model and the air conditioning aggregator's scheduling model, and to optimize and solve the master-slave game model based on the user's willingness model to participate in the air conditioning aggregator to obtain the optimal air conditioning control strategy.

[0193] In some embodiments, the willingness model building module 100 is used to:

[0194] Determine the user's discomfort level based on the user's air-conditioning indoor temperature and the initial value of the air-conditioning temperature; wherein the discomfort level is used to represent the user's temperature comfort;

[0195] Determine the user's spending satisfaction based on the user's spending costs before and after participating in the air conditioning aggregator's scheduling;

[0196] Normalize the discomfort level and expenditure satisfaction respectively to obtain the normalized discomfort level and normalized expenditure satisfaction;

[0197] The normalized discomfort level and normalized expenditure satisfaction are weighted to obtain a model of users' willingness to participate in air conditioning aggregators.

[0198] In some embodiments, the first objective function corresponding to the first optimization objective is:

[0199]

[0200] Where, The benefits for users to participate in the air conditioning aggregator scheduling, Cost to users, The user's discomfort level;

[0201] in,

[0202] Where, The electricity cost for users; The income obtained by users from participating in the scheduling of air conditioning aggregators;

[0203]

[0204] Where N is the number of users, i is the user index, t is the time, is the initial time, T is the total time period, for The electricity price of user i at the moment, for The air conditioning power of user i at the moment;

[0205]

[0206] Where, 、 They are The upper and lower reserve power generation capacities provided by user i to the air conditioning aggregator at the moment; 、 for The compensation price for upper and lower backup provided by the air conditioning aggregator to user i at that moment;

[0207]

[0208] Where, for The indoor temperature of user i's air conditioner at the moment; The initial value of the air conditioning temperature set by user i.

[0209] In some embodiments, the first constraint condition includes an air-conditioning power balance constraint, an air-conditioning indoor temperature limit constraint, an air-conditioning power limit constraint, and an air-conditioning standby power generation capacity limit constraint.

[0210] In some embodiments, the second objective function corresponding to the second optimization objective is:

[0211]

[0212] Where, For the benefits of air conditioning aggregators, represents the revenue earned by air conditioning aggregators from providing backup generation capacity to the reserve market, represents the revenue of air-conditioning aggregators from selling electricity to users, represents the cost of electricity purchased from the grid by AC aggregators;

[0213] in,

[0214]

[0215]

[0216] Where, The electricity cost for users, It represents the electricity price given by the power grid to the air-conditioning aggregator. for The air conditioning power of user i at the moment;

[0217] The second constraint includes the upper and lower standby compensation price limit constraints given by the air conditioning aggregator.

[0218] In some embodiments, the control optimization module 400 is configured to:

[0219] With the air conditioner aggregator as the leader in the game and the user as the follower, a master-slave game model between the air conditioner aggregator and the user is constructed based on the air conditioner user participation scheduling optimization model and the air conditioner aggregator scheduling model. The master-slave game model between the air conditioner aggregator and the user is:

[0220]

[0221] Where G is the master-slave game model between air-conditioning aggregators and users, For the game player, Strategies for AC aggregators, strategies for users;

[0222] in,

[0223]

[0224]

[0225] Where, For air conditioning aggregators, For air-conditioning users;

[0226] Initialize the initial value of the standby compensation price provided by the air-conditioning user formulated by the air-conditioning aggregator, and use the initial value of the standby service compensation price as the current standby compensation price;

[0227] The current reserve compensation price is input into the air conditioning user participation scheduling optimization model, and the air conditioning user participation scheduling optimization model is optimized and solved to obtain the temperature adjustment strategy of the air conditioning cluster in each time period, as well as the reserve power generation capacity of the air conditioning users participating in the air conditioning aggregator's regulation;

[0228] Based on the user willingness model for participating in air conditioning aggregator regulation, the user's willingness to participate in air conditioning aggregator regulation is determined according to the temperature regulation strategy and the spare power generation capacity of air conditioning users participating in air conditioning aggregator regulation;

[0229] According to the user's willingness to participate in the regulation of the air conditioning aggregator, the spare power generation capacity of the air conditioning user participating in the regulation of the air conditioning aggregator is corrected to obtain the actual spare power generation capacity of the air conditioning user participating in the regulation of the air conditioning aggregator;

[0230] The actual reserve power generation capacity of air conditioner users participating in the regulation of air conditioner aggregators is input into the dispatch model of air conditioner aggregators, and the dispatch model of air conditioner aggregators is optimized to obtain the optimized reserve compensation price.

[0231] The optimized standby compensation price is updated to the current standby compensation price, and the current standby compensation price is input into the air-conditioning user participation scheduling optimization model. The air-conditioning user participation scheduling optimization model is optimized and solved to obtain the temperature regulation strategy of the air-conditioning cluster in each time period and the standby power generation capacity of the air-conditioning users participating in the regulation of the air-conditioning aggregator. The iteration is stopped until the preset iteration condition is reached, and the temperature regulation strategy of the air-conditioning cluster in each time period and the standby power generation capacity of the air-conditioning users participating in the regulation of the air-conditioning aggregator are output.

[0232] like Figure 6 The embodiment of the present application shown provides an electronic device, the electronic device 10 includes a memory 20 and a processor 30, the memory 20 stores a computer program, and when the computer program is executed by the processor 30, the processor 30 executes the steps of the master-slave game scheduling method of the air-conditioning aggregator in the above embodiment.

[0233] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed, the steps of the master-slave game scheduling method for air-conditioning aggregators in the above embodiment are implemented.

[0234] An embodiment of the present application provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the steps of the master-slave game scheduling method for air-conditioning aggregators in the above-mentioned embodiment.

[0235] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, electronic devices, computer storage media, and computer program products can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0236] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0237] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0238] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, electronic devices, computer storage media, computer program products and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0239] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0240] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0241] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the method described in each embodiment of the present invention via a computer device (which can be a personal computer, server, or network device, etc.). The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0242] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A master-slave game scheduling method for air conditioning aggregators, characterized in that: include: Based on users' spending satisfaction and temperature comfort, a model of users' willingness to participate in air conditioning aggregators is constructed; Taking the minimization of all users' expenditure costs and the minimization of the sum of all users' discomfort levels as the first optimization goal, and the balanced operation of air conditioning as the first constraint, an air conditioning user participation scheduling optimization model is constructed; Taking the maximization of the total revenue of air-conditioning aggregators participating in the reserve market and energy market as the second optimization objective and the electricity price limit of air-conditioning aggregators as the second constraint, a scheduling model for air-conditioning aggregators is constructed. Based on the air conditioning user participation scheduling optimization model and the air conditioning aggregator scheduling model, a master-slave game model between the air conditioning aggregator and the user is constructed. Based on the user willingness model for participating in the air conditioning aggregator, the master-slave game model is optimized and solved to obtain the optimal air conditioning control strategy, including: With the air conditioner aggregator as the leader in the game and the user as the follower, a master-slave game model between the air conditioner aggregator and the user is constructed based on the air conditioner user participation scheduling optimization model and the air conditioner aggregator scheduling model. The master-slave game model between the air conditioner aggregator and the user is: ； Where G is the master-slave game model between air-conditioning aggregators and users, For the game player, Strategies for AC aggregators, For user strategies, For the benefits of air conditioning aggregators, Profits for users who participate in air conditioning aggregator scheduling; in, ; ； ； Where, For air conditioning aggregators, For air-conditioning users; 、 They are The upper and lower reserve power generation capacities provided by user i to the air conditioning aggregator at the moment; 、 for The compensation price for upper and lower backup provided by the air conditioning aggregator to user i at that moment; Initializing and setting an initial value of the standby compensation price provided by the air conditioner user and formulated by the air conditioner aggregator, and using the initial value of the standby compensation price as the current standby compensation price; Inputting the current reserve compensation price into the air conditioning user participation scheduling optimization model, optimizing and solving the air conditioning user participation scheduling optimization model to obtain the temperature adjustment strategy for each time period of the air conditioning cluster and the reserve power generation capacity regulated by the air conditioning users participating in the air conditioning aggregator; Determining the user's willingness to participate in the air conditioning aggregator's regulation based on the user's willingness model to participate in the air conditioning aggregator's regulation according to the temperature regulation strategy and the spare power generation capacity of the air conditioning user participating in the air conditioning aggregator's regulation; According to the user's willingness to participate in the regulation of the air conditioning aggregator, the spare power generation capacity of the air conditioning user participating in the regulation of the air conditioning aggregator is corrected to obtain the actual spare power generation capacity of the air conditioning user participating in the regulation of the air conditioning aggregator; Inputting the actual reserve power generation capacity of the air conditioner user participating in the air conditioner aggregator's regulation into the air conditioner aggregator's dispatch model, optimizing the dispatch model of the air conditioner aggregator, and obtaining an optimized reserve compensation price; The optimized standby compensation price is updated to the current standby compensation price, and the current standby compensation price is input into the air-conditioning user participation scheduling optimization model, the air-conditioning user participation scheduling optimization model is optimized and solved, and the steps of obtaining the temperature regulation strategy of the air-conditioning cluster for each time period and the standby power generation capacity regulated by the air-conditioning users participating in the regulation of the air-conditioning aggregator are iterated until the preset iteration condition is reached, the iteration stops, and the temperature regulation strategy of the air-conditioning cluster for each time period and the standby power generation capacity regulated by the air-conditioning users participating in the regulation of the air-conditioning aggregator are output.

2. The master-slave game scheduling method for air conditioning aggregators according to claim 1, characterized in that: The user willingness model for participating in air conditioning aggregators is constructed based on the user's spending satisfaction and temperature comfort, including: Determining the user's discomfort level based on the user's air-conditioning indoor temperature and the initial value of the air-conditioning temperature; wherein the discomfort level is used to represent the user's temperature comfort; Determining the user's expenditure satisfaction based on the user's expenditure costs before and after participating in the air conditioning aggregator's scheduling; Normalizing the discomfort level and the expenditure satisfaction respectively to obtain a normalized discomfort level and a normalized expenditure satisfaction; A weighted calculation is performed on the normalized discomfort level and the normalized expenditure satisfaction to obtain a model of the user's willingness to participate in air conditioning aggregators.

3. The master-slave game scheduling method for air conditioning aggregators according to claim 1, characterized in that: The first objective function corresponding to the first optimization objective is: ； Where, The benefits for users to participate in the air conditioning aggregator scheduling, Cost to users, The user's discomfort level; in, ; Where, The electricity cost for users; The income obtained by users from participating in the scheduling of air conditioning aggregators; ； Where N is the number of users, i is the user index, t is the time, is the initial time, T is the total time period, for The electricity price of user i at the moment, for The air conditioning power of user i at the moment; ； Where, 、 They are The upper and lower reserve power generation capacities provided by user i to the air conditioning aggregator at the moment; 、 for The compensation price for upper and lower backup provided by the air conditioning aggregator to user i at that moment; ； Where, for The indoor temperature of user i's air conditioner at the moment; The initial value of the air conditioning temperature set by user i.

4. The master-slave game scheduling method for air conditioning aggregators according to claim 3, characterized in that: The first constraint condition includes an air conditioning power balance constraint, an air conditioning indoor temperature limit constraint, an air conditioning power limit constraint, and an air conditioning standby power generation capacity limit constraint.

5. The master-slave game scheduling method for air conditioning aggregators according to claim 1, characterized in that: The second objective function corresponding to the second optimization objective is: ； Where, For the benefits of air conditioning aggregators, represents the revenue earned by air conditioning aggregators from providing backup generation capacity to the reserve market, represents the revenue of air-conditioning aggregators from selling electricity to users, represents the cost of electricity purchased from the grid by AC aggregators; The income obtained by users from participating in the scheduling of air conditioning aggregators; in, ; ； ； Where, The electricity cost for users, It represents the electricity price given by the power grid to the air-conditioning aggregator. for The air conditioning power of user i at the moment; is the initial moment, 、 are the upper and lower standby compensation prices that the air-conditioning aggregator gives to all users at time t; 、 They are The upper and lower reserve power generation capacity provided by all users to the air conditioning aggregator at all times; The second constraint condition includes the upper and lower standby compensation price limit constraints given by the air conditioning aggregator.

6. A master-slave game scheduling system for air conditioning aggregators, characterized by: include: The willingness model building module is used to build a model of users' willingness to participate in air conditioning aggregators based on their spending satisfaction and temperature comfort; The user model building module is used to build an air conditioning user participation scheduling optimization model with the minimization of all user expenditure costs and the minimization of the sum of all user discomfort levels as the first optimization goal and the balanced operation of the air conditioning as the first constraint condition; an aggregator model building module, which is used to build a dispatch model for air conditioning aggregators, taking maximizing the total revenue of air conditioning aggregators participating in the reserve market and energy market as the second optimization objective and taking the electricity price limit of air conditioning aggregators as the second constraint; a control optimization module for constructing a master-slave game model between air conditioner aggregators and users based on the air conditioner user participation scheduling optimization model and the air conditioner aggregator's scheduling model, and solving the master-slave game model based on the user's willingness model to participate in the air conditioner aggregator to obtain an optimal air conditioner control strategy; Based on the air conditioning user participation scheduling optimization model and the air conditioning aggregator scheduling model, a master-slave game model between the air conditioning aggregator and the user is constructed. Based on the user willingness model for participating in the air conditioning aggregator, the master-slave game model is optimized and solved to obtain the optimal air conditioning control strategy, including: With the air conditioner aggregator as the leader in the game and the user as the follower, a master-slave game model between the air conditioner aggregator and the user is constructed based on the air conditioner user participation scheduling optimization model and the air conditioner aggregator scheduling model. The master-slave game model between the air conditioner aggregator and the user is: ； Where G is the master-slave game model between air-conditioning aggregators and users, For the game player, Strategies for AC aggregators, For user strategies, For the benefits of air conditioning aggregators, Profits for users who participate in air conditioning aggregator scheduling; in, ; ； ； Where, For air conditioning aggregators, For air-conditioning users; 、 They are The upper and lower reserve power generation capacities provided by user i to the air conditioning aggregator at the moment; 、 for The compensation price for upper and lower backup provided by the air conditioning aggregator to user i at that moment; Initializing and setting an initial value of the standby compensation price provided by the air conditioner user and formulated by the air conditioner aggregator, and using the initial value of the standby compensation price as the current standby compensation price; Inputting the current reserve compensation price into the air conditioning user participation scheduling optimization model, optimizing and solving the air conditioning user participation scheduling optimization model to obtain the temperature adjustment strategy for each time period of the air conditioning cluster and the reserve power generation capacity regulated by the air conditioning users participating in the air conditioning aggregator; Determining the user's willingness to participate in the air conditioning aggregator's regulation based on the user's willingness model to participate in the air conditioning aggregator's regulation according to the temperature regulation strategy and the spare power generation capacity of the air conditioning user participating in the air conditioning aggregator's regulation; According to the user's willingness to participate in the regulation of the air conditioning aggregator, the spare power generation capacity of the air conditioning user participating in the regulation of the air conditioning aggregator is corrected to obtain the actual spare power generation capacity of the air conditioning user participating in the regulation of the air conditioning aggregator; Inputting the actual reserve power generation capacity of the air conditioner user participating in the air conditioner aggregator's regulation into the air conditioner aggregator's dispatch model, optimizing the dispatch model of the air conditioner aggregator, and obtaining an optimized reserve compensation price; The optimized standby compensation price is updated to the current standby compensation price, and the current standby compensation price is input into the air-conditioning user participation scheduling optimization model, the air-conditioning user participation scheduling optimization model is optimized and solved, and the steps of obtaining the temperature regulation strategy of the air-conditioning cluster for each time period and the standby power generation capacity regulated by the air-conditioning users participating in the regulation of the air-conditioning aggregator are iterated until the preset iteration condition is reached, the iteration stops, and the temperature regulation strategy of the air-conditioning cluster for each time period and the standby power generation capacity regulated by the air-conditioning users participating in the regulation of the air-conditioning aggregator are output.

7. An electronic device, characterized in that: The electronic device includes a memory and a processor, wherein a computer program is stored in the memory. When the computer program is executed by the processor, the processor executes the steps of the master-slave game scheduling method for air-conditioning aggregators as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, the steps of the master-slave game scheduling method for air-conditioning aggregators as described in any one of claims 1 to 5 are implemented.

9. A computer program product, characterized in that The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions, wherein when the program instructions are executed by a computer, the computer is caused to perform the steps of the master-slave game scheduling method for air-conditioning aggregators as described in any one of claims 1 to 5.

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