Three-party interaction load aggregator participation demand response incentive model and application method thereof

Abstract

The invention discloses a three-party interaction load aggregator participation demand response incentive model and an application method thereof.The three-party interaction load aggregator participation demand response incentive model comprises a power grid company, a load aggregator and a terminal user, an upper-level game structure and a lower-level game structure are constructed, and in the upper-level game, the power grid company serves as a leader to formulate an incentive price to guide the load aggregator to participate in response; the load aggregator serves as a follower to determine aggregation response quantity according to the incentive price; in the lower-level game, a load aggregator serves as a leader to formulate a compensation price to stimulate a terminal user to participate in response, the terminal user serves as a follower to determine the response amount of the terminal user according to the compensation price, and each game main body aims at maximizing the revenue of the terminal user. According to the three-party interaction load aggregator participation demand response excitation model and the application method thereof, a model architecture is innovated, a power grid company-load aggregator-terminal user three-party interaction master-slave game model is constructed, and the limitation that only part of main body game behaviors are focused traditionally is broken through.

Description

Technical Field

[0001] The present invention relates to the technical field of power optimization, and particularly to an incentive model for a load aggregator participating in demand response with three-party interaction and its application method. Background Art

[0002] In the fields of energy management and power system operation, demand response plays a crucial role in optimizing power resource allocation and ensuring the stable operation of the power grid. With the development and reform of the power market, how to effectively motivate each participating entity to actively participate in demand response has become a research hotspot.

[0003] Game theory has been widely applied in demand response research. Many studies focus on analyzing the game behaviors among various participating entities in the demand response market. These studies aim to analyze the game equilibrium state and explore the optimal game strategies by optimizing the decision-making behaviors of each participating entity, with the goal of improving the overall efficiency and benefits of demand response. However, existing studies have significant deficiencies in the cost-benefit analysis of end-users' participation in demand response.

[0004] In actual situations, the decisions of end-users are not solely determined by simple economic factors. Psychological factors of users play a key role. For example, psychological factors such as users' concerns about power shortages, their awareness and attitudes towards environmental protection and emission reduction will deeply affect their willingness and behaviors to participate in demand response. However, most current studies often ignore these important psychological factors in the model construction and analysis process and rarely incorporate them into the quantitative analysis system of cost-benefit. This omission makes the understanding and prediction of end-users' participation behaviors inaccurate, thereby affecting the effectiveness and rationality of the demand response incentive mechanism.

[0005] In the current power market environment, the power grid company needs to balance power supply and demand. As an important bridge connecting the power grid company and end-users, the role of the load aggregator is becoming increasingly prominent. However, due to the lack of consideration of users' psychological factors and a comprehensive three-party interaction model, it is difficult to achieve precise incentives and efficient resource integration, and it is unable to fully exert the potential of demand response in power system optimization. There is an urgent need for a new model and method to solve these problems. Summary of the Invention

[0006] Technical Solution

[0007] To achieve the above object, the present invention provides the following technical solution: An incentive model for a load aggregator participating in demand response with three-party interaction, including C G,td 、C G,s 、C G,c 、C G,I 、I G 、p G,i 、q i,j 、CG,ld , C G,s , I, M, τ rd , c c , ΔP, R i , α, t con,i , C G,l and τ a , where:

[0008] C G,td is the reduced power transmission and distribution revenue, C G,s is the incentive cost for the load aggregator, C G,c is the avoidable power transmission and distribution capacity cost, C G,I is the avoidable power transmission and distribution network loss cost, I G is the revenue function, p G,i is the incentive price given by the power grid company to the load aggregator j at time period i;

[0009] Its revenue function I G is I G = -C G,ld -C G,s +C G,c +C G,l , and the upper and lower limits of the incentive price are set

[0010] q i,j is the responsive power of the load aggregator j at time period i, C G,ld is the reduced power transmission and distribution revenue, C G,s is the incentive cost for the load aggregator, I is the number of response time periods, M is the number of load aggregators participating in the response, τ rd is the power transmission and distribution price of the power grid company during the demand response implementation period;

[0011] The responsive power of the load aggregator j at time period i

[0012] Reduced power transmission and distribution revenue

[0013] Incentive cost for the load aggregator

[0014] c c is the avoidable power transmission and distribution capacity unit cost, ΔP is the actually avoidable power transmission and distribution capacity, R i represents the total demand response power of all load aggregators at time period i, α represents the power grid power transmission and distribution loss coefficient, t con,i represents the duration of a single peak load period at time period i, C G,l is the avoidable power transmission and distribution network loss cost, τ a represents the market average trading price;

[0015] Avoidable transmission and distribution capacity cost C G,c is

[0016] Avoidable transmission and distribution network loss cost

[0017] Preferably, the revenue function I of the load aggregator j LA,j is Compensation price p LA,i,j needs to satisfy 0 ≤ p LA,i,j < p G,i and where p G,i,j is the incentive price given by the power grid company to the load aggregator j at time period i; p LA,i,j is the compensation price given by the load aggregator j to the user at time period i.

[0018] Preferably, the constructed master - slave game model is

[0019]

[0020] Preferably, for this three - party interactive master - slave game model, when and only when the game strategy meets the following requirements, this game strategy is the game equilibrium solution of this model

[0021]

[0022] wherein, is the equilibrium strategy of the end - users agented by the load aggregator j at time period i; is the equilibrium strategy of all end - users at time period i is the equilibrium strategy of the other end - users agented by the load aggregator j except for user k ∈ N.

[0023] Preferably, the backward induction method is used to prove the existence and uniqueness of the game equilibrium solution of this model, specifically including:

[0024] In the lower - level game, for the compensation price p formulated by the load aggregator LA,j for the end - user revenue function respectively find the first - order and second - order derivatives with respect to q j,k The second - order derivative Let the first - order derivative to obtain the optimal solution of the end - user response strategy

[0025] Substitute the end - user optimal response strategy into the load aggregator revenue function, to obtain

[0026]

[0027] For p LA,j Taking the first - order and second - order derivatives, we can obtain:

[0028]

[0029] I LA,j The Hessian matrix of is negative definite. Let the first - order derivative We get the optimal solution of the load aggregator compensation strategy:

[0030] Substitute the optimal solution of the load aggregator compensation strategy into the optimal response strategy of the end - user, we get the adjusted end - user response strategy and the aggregated response volume of the load aggregator. Then, we calculate the total aggregated response volume of all load aggregators, substitute it into the revenue function of the power grid company and take the derivative to get the optimal solution of the power grid company's incentive strategy Where:

[0031]

[0032] Preferably, the distributed trial - and - error method is used to solve the game model. The specific steps include:

[0033] Initialize the relevant parameters and calculate the initial revenue value I of the power grid company under the initial parameters G ;

[0034] The power grid company releases the initial incentive price, and the subsequent incentive prices are gradually iterated from the lower limit of the incentive price to the upper limit

[0035] The load aggregator conducts a lower - level game based on this incentive price. Combining the situation of the end - users it represents, it determines its optimal compensation price and optimal aggregated response volume through relevant formulas and feeds the data back to the power grid company;

[0036] The power grid company determines the demand response revenue I based on the data information fed back by the load aggregator G ′ , if I G ′ ≥I G , then record the current incentive price and revenue value, and determine whether this decision satisfies the game equilibrium constraint conditions. If the constraint conditions are satisfied, end the iteration and output the results. If not, continue the next iteration until the game equilibrium constraint conditions are satisfied to achieve game equilibrium. During the algorithm operation, the power grid company only needs to send the trial incentive price to the load aggregator without having to specifically grasp the various parameters of the end - users.

[0037] Application method of an incentive model for a load aggregator participating in demand response in a three - party interaction, including a power grid company, a load aggregator, and end - users, where:

[0038] Construct an upper - lower two - level game structure. In the upper - level game, the power grid company acts as the leader to formulate an incentive price to guide the load aggregator to participate in the response, and the load aggregator acts as the follower to determine the aggregated response volume according to the incentive price.

[0039] In the lower - level game, the load aggregator acts as the leader to formulate a compensation price to incentivize end - users to participate in the response, and the end - users act as the followers to determine their own response volume according to the compensation price. Each game subject aims to maximize its own benefits, and information conduction and game competition are carried out through the incentive price and the compensation price.

[0040] Beneficial effects

[0041] Compared with the prior art, the present invention provides an incentive model for a load aggregator participating in demand response in a three - party interaction and its application method, having the following beneficial effects:

[0042] 1. The incentive model for a load aggregator participating in demand response in a three - party interaction and its application method innovate the model architecture: construct a principal - agent game model of three - party interaction among the power grid company - load aggregator - end - users, break through the limitation of traditional models that only focus on the game behavior of some subjects, comprehensively analyze the interaction mechanism among the three parties in demand response, clearly show how the decisions of all parties affect and restrict each other, provide a new perspective and a systematic analysis framework for power demand response research, and help to deeply understand the market dynamics.

[0043] 2. The incentive model for a load aggregator participating in demand response in a three - party interaction and its application method conduct accurate cost - benefit analysis: conduct detailed demand - response cost - benefit analysis for the power grid company and the load aggregator respectively, accurately quantify the economic gains and losses of all parties under different strategies. For example, the power grid company can clarify the changes in various costs and benefits, lay a foundation for formulating scientific and reasonable incentive strategies, and ensure the effective allocation of resources.

[0044] 3. The incentive model for a load aggregator participating in demand response in a three - party interaction and its application method conduct rigorous equilibrium solution demonstration: use backward induction to strictly prove the existence and uniqueness of the game equilibrium solution, ensure that the model is stable in theory and has practical guiding significance, provide a reliable decision - making basis for all parties in a complex power market environment, enable the power grid company, the load aggregator, and the end - users to plan their actions in a stable equilibrium state, and enhance the market predictability and stability.

[0045] 4. The incentive model for a three - party interactive load aggregator to participate in demand response and its application method, efficient privacy - protection solution: A distributed trial - and - error method is proposed to solve the model. The power grid company does not need to know the detailed information of end - users. It can solve the problem only through iterative interaction with the load aggregator, effectively protecting user privacy, avoiding the risk of information leakage, reducing the complexity and cost of information transmission, improving the operation efficiency, accelerating the demand - response decision - making process, and enhancing the overall operation efficiency and response speed of the power system. Brief Description of the Drawings

[0046] Figure 1 It is the master - slave game structure of three - party interaction in the incentive model for a three - party interactive load aggregator to participate in demand response and its application method proposed by the present invention;

[0047] Figure 2 It is the flow chart for solving the game model of the incentive model for a three - party interactive load aggregator to participate in demand response and its application method proposed by the present invention. Detailed Embodiments

[0048] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0049] Please refer to Figure 1-2 , an incentive model for a three - party interactive load aggregator to participate in demand response, including C G,td 、C G,s 、C G,c 、C G,I 、I G 、p G,i 、q i,j 、C G,ld 、C G,s 、I、M、τ rd 、c c 、ΔP、R i 、α、t con,i 、C G,l and τ a , where:

[0050] C G,td is the reduced transmission and distribution revenue, C G,s is the incentive cost for the load aggregator, C G,c is the avoidable transmission and distribution capacity cost, C G,I is the avoidable transmission and distribution network loss cost, I G is the revenue function, p G,iis the incentive price given by the power grid company to the load aggregator j during period i;

[0051] Its revenue function I G is I G =-C G,ld -C G,s +C G,c +C G,l , and set the upper and lower limits of the incentive price

[0052] q i,j is the response power of load aggregator j during period i, C G,ld is the reduced transmission and distribution revenue, C G,s is the incentive cost for the load aggregator, I is the number of response periods, M is the number of load aggregators participating in the response, τ rd is the transmission and distribution price of the power grid company during the demand response implementation period;

[0053] The response power of load aggregator j during period i

[0054] The reduced transmission and distribution revenue

[0055] The incentive cost for the load aggregator

[0056] c c is the unit cost of avoidable transmission and distribution capacity, ΔP is the actually avoidable transmission and distribution capacity, R i represents the total demand response power of all load aggregators during period i, α represents the power grid transmission and distribution loss coefficient, t con,i represents the duration of a single peak load period during period i, C G,l is the cost of avoidable transmission and distribution network losses, τ a represents the average market trading price;

[0057] The cost of avoidable transmission and distribution capacity C G,c is:

[0058] The cost of avoidable transmission and distribution network losses

[0059] The revenue function I of load aggregator j LA,j is The compensation price p LA,i,j needs to satisfy 0 ≤ p LA,i,j < p G,i and where p G,i,j is the incentive price given by the power grid company to load aggregator j during period i; p LA,i,jis the compensation price given by the load aggregator j to users in period i.

[0060] In the demand response event, both the power grid company and the load aggregator aim to maximize their own revenues. The power grid company maximizes the demand response revenue by seeking the optimal incentive price for each period. Each load aggregator makes a decision on the optimal response volume based on the demand response incentive price announced by the power grid company and its own load aggregation situation to achieve revenue maximization. Based on the above analysis, the constructed principal-agent game model is Corresponding to the optimization objectives and constraints of the power grid company and the load aggregator, they form the principal-agent game model. During the game process, the strategies of both sides influence each other and finally reach equilibrium. The incentive price p obtained from the game G,i can be used to design the incentive model of the power grid company for load aggregators, so as to more effectively motivate load aggregators to participate in the response and at the same time achieve the maximization of its own revenue, forming a three-party interactive principal-agent game model. The game structure is specifically as Figure 1 shown. The optimization of the game objective of any one party will affect the other two parties. This is because during the demand response process, the level of the incentive price set by the power grid company will affect the aggregation response volume of the load aggregator, change the level of the compensation price it sets, the level of the compensation price will affect the response decision of the end user, and the response decision of the end user will in turn affect the level of the compensation price set by the load aggregator, and then affect the level of the incentive price set by the power grid company. The game parties interact and influence each other, and continuously adjust their own game strategies (incentive price p G,i , compensation price p LA,i,j , response volume q i,j,k ) to finally reach the game equilibrium.

[0061] For this three-party interactive principal-agent game model, when and only when the game strategy meets the following requirements, this game strategy is the game equilibrium solution of this model

[0062] where, is the equilibrium strategy of the end users agented by the load aggregator j in period i; is the equilibrium strategy of all end users in period i is the equilibrium strategy of the other end users agented by the load aggregator j except for user k∈N.

[0063] Based on the above definition of the game equilibrium solution, assuming is the unique game equilibrium solution existing in the model, it can be known that in the upper-level game, the power grid company, as the leader, uses the incentive price for load aggregators As its strategy, while the load aggregator acts as a follower and adjusts the aggregated response volume according to the incentive price set by the power grid company, and finally adjusts to As its strategy; in the lower-level game, the load aggregator acts as the leader and uses the compensation price As its strategy, while the end-users act as followers and adjust their response volume according to the compensation price set by the load aggregator, and finally adjust to As its strategy. At this time, the interests of all game players reach equilibrium, and none of them can obtain higher benefits by unilaterally adjusting their game strategies.

[0064] The three-party interactive leader-follower game model established in this paper has a unique game equilibrium solution that satisfies the above formula.

[0065] The proof is as follows: In the leader-follower game model established in this paper, the game strategy spaces of all game players (the power grid company, the load aggregator, and the end-users it represents) are all Euclidean non-empty continuous sets. Therefore, it is only necessary to prove that the benefit functions of all game players are continuous concave / convex functions with respect to the game strategy sets. Considering that the positions of game players in the leader-follower game are not equal and the decision-making order of all game players is sequential, with the leader making decisions before the follower, the backward induction method is used here to prove the existence and uniqueness of the game equilibrium solution of this model. First, the compensation price p set by the load aggregator (the leader) in the lower-level game is used as a known parameter for the decision-making problem of the end-users (the followers), and then the optimal response strategy of the end-users is solved. Secondly, based on the optimal response strategy of the end-users, the optimal action strategy of the load aggregator is solved. Finally, according to the action strategy of the load aggregator, the optimal action strategy of the power grid company (the leader) in the upper-level game is solved. It should be noted that to ensure the simplicity of the formula, the time period symbol i will be omitted in the subsequent proof process.

[0066] The backward induction method is used to prove the existence and uniqueness of the game equilibrium solution of this model, which specifically includes:

[0067] The compensation price p set by the load aggregator in the lower-level game LA,j For the end-user revenue function Respectively take the first and second derivatives with respect to q j,k , and the following can be obtained:

[0068]

[0069] Among them, C lac,k Is the power outage cost; C s,k Is the response compensation provided by the load aggregator to users; C dec,k Is the electricity cost; C carb,k Is the psychological value of emission reduction awareness; λ k Is the loss aversion coefficient; α k , βk is a constant greater than 0.

[0070] From the above derivation, it can be seen that the second derivative always holds. Let the first derivative to obtain the optimal solution of the end-user response strategy

[0071] The optimal compensation strategy of the load aggregator will be determined according to the optimal response strategy of the end-user. Substitute the optimal solution formula of each end-user response strategy into the load aggregator revenue function formula.

[0072]

[0073] We can get

[0074] For p LA,j Take the first and second derivatives, and we can get:

[0075]

[0076] I LA,j The Hessian matrix of is a negative definite matrix. Let the first derivative to obtain the optimal solution of the load aggregator compensation strategy:

[0077] Use backward induction to verify the existence of the unique best incentive strategy of the power grid company of.

[0078] First, substitute the optimal solution formula of the load aggregator compensation strategy into the end-user optimal response strategy formula to obtain the adjusted expression of each end-user response strategy:

[0079] At this time, the aggregated response volume of the load aggregator can be obtained as:

[0080] Furthermore, the total aggregated response volume of all load aggregators is obtained:

[0081] To simplify the expression, let:

[0082] Furthermore, the total aggregated response volume formula of all load aggregators is simplified to Substitute this formula into the power grid company revenue function I G It can be adjusted to:

[0083]

[0084] For the processed revenue function formula I G Respectively take the first - order and second - order derivatives with respect to p G We can obtain:

[0085]

[0086] From the above derivation, it can be seen that the Hessian matrix of I G is a negative definite matrix, that is, the revenue function of the power grid company is strictly concave within the feasible region. Let the first - order derivative At this time, the optimal solution of the power grid company's incentive strategy is obtained:

[0087]

[0088] Based on the above analysis and proof, it can be known that the three - party interactive master - slave game model established in this paper has a unique game equilibrium solution that satisfies the above formula.

[0089] The three - party interactive master - slave game model established in this paper has a game equilibrium solution. However, to solve this equilibrium solution, it is necessary to accurately grasp various parameters of the end - users, such as the power - shortage cost parameters α k and β k , the loss - aversion coefficient λ k , the carbon - reduction coefficient ω k etc. Considering the concerns of end - users about personal information leakage and the complexity of information transmission of various parameter information, this scheme proposes a distributed trial - and - error method for solving the three - party interactive master - slave game model. Since during the operation of the algorithm, the power grid company only needs to send the trial - incentive price to the load aggregator without accurately grasping various parameters of the end - users, this algorithm does not need to disclose various information of the end - users, which not only protects user privacy but also reduces unnecessary information transmission and is conducive to improving the operation efficiency. The specific process of applying the distributed trial - and - error method to solve the game model is as Figure 2 shown.

[0090] Using the distributed trial - and - error method to solve the game model, the specific steps include:

[0091] Initialize the relevant parameters and calculate the initial revenue value I of the power grid company under the initial parameters G ;

[0092] The power grid company publishes the initial incentive price, and the subsequent incentive prices are gradually iterated from the lower limit of the incentive price to the upper limit

[0093] The load aggregator conducts a lower - level game based on this incentive price. Combining the situation of the end - users it represents, it determines its optimal compensation price and optimal aggregated response volume through relevant formulas and feeds the data back to the power grid company;

[0094] The power grid company determines the demand response benefit I based on the data information fed back by the load aggregator G ′ , if I G ′ ≥I G , then record the current incentive price and benefit value, and determine whether this decision meets the game equilibrium constraint conditions. If the constraint conditions are met, end the iteration and output the result. If not, continue the next iteration until the game equilibrium constraint conditions are met to achieve game equilibrium. During the operation of the algorithm, the power grid company only needs to send the tentative incentive price to the load aggregator without having to specifically grasp the various parameters of the end-users

[0095] Applied to an application method of an incentive model for load aggregators participating in demand response in a three-party interaction, including the power grid company, load aggregators, and end-users, where:

[0096] Construct an upper and lower two-level game structure. In the upper-level game, the power grid company acts as the leader to formulate the incentive price to guide the load aggregator to participate in the response, and the load aggregator acts as the follower to determine the aggregated response volume based on the incentive price

[0097] In the lower-level game, the load aggregator acts as the leader to formulate the compensation price to incentivize the end-users to participate in the response, and the end-users act as the followers to determine their own response volume. Each game player aims to maximize its own benefit, and conducts information conduction and game competition through the incentive price and compensation price

[0098] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising one" does not exclude the presence of additional identical elements in the process, method, article or device comprising the element

[0099] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents

Claims

1. An incentive model for three-party interactive load aggregators to participate in demand response, characterized by: Including C G,td , C G,s , C G,c , C G,I ,I G 、p G,i ,q i,j , C G,ld , C G,s ,I,M,τ rd 、c c , ΔP, R i ,α,t con,i , C G,l and τ a ,in: C G,td To reduce the transmission and distribution revenue, C G,s is the incentive fee for load aggregators, C G,c In order to avoid transmission and distribution capacity costs, C G,I In order to avoid the transmission and distribution network loss cost, I G is the profit function, p G,i is the incentive price that the power grid company gives to load aggregator j in time period i; Its profit function I G For I G =-C G,ld -C G,s +C G,c +C G,l , and set upper and lower limits for incentive prices q i,j is the response power of load aggregator j in time period i, C G,ld To reduce the transmission and distribution revenue, C G,s is the incentive fee of the load aggregator, I is the number of response periods, M is the number of load aggregators participating in the response, τ rd The transmission and distribution price of the power grid company during the demand response implementation period; The response power of load aggregator j in time period i Reduced transmission and distribution revenue Incentive fees for load aggregators c c is the unit cost of the avoidable transmission and distribution capacity, ΔP is the actual avoidable transmission and distribution capacity, R i represents the total demand response power of all load aggregators in time period i, α represents the transmission and distribution loss coefficient of the power grid, and t con,i represents the duration of a single peak load period in period i, C G,l In order to avoid the transmission and distribution network loss cost, τ a Represents the average transaction electricity price in the market; Avoided transmission and distribution capacity costs C G,c for: Avoid transmission and distribution network loss costs 2. According to claim 1, a three-party interactive load aggregator incentive model for participating in demand response is characterized by: The revenue function I of the load aggregator j is LA,j for Compensation price p LA,i,j Must satisfy 0≤p LA,i,j <p G,i and where p G,i,j is the incentive price that the power grid company gives to load aggregator j in time period i; p LA,i,j is the compensation price given by load aggregator j to users in time period i.

3. The three-party interactive load aggregator incentive model for participating in demand response according to claim 1, characterized in that: The master-slave game model constructed is 4. The three-party interactive load aggregator incentive model for participating in demand response according to claim 1, characterized in that: In this three-party interactive master-slave game model, if and only if the game strategy When the following requirements are met, the game strategy is the game equilibrium solution of this model in, is the balancing strategy for end users represented by load aggregator j in time period i; is the equilibrium strategy for all terminal users in period i is the balancing strategy for other end users except user k∈N represented by load aggregator j.

5. The three-party interactive load aggregator incentive model for participating in demand response according to claim 1, characterized in that: The reverse induction method is used to prove the existence and uniqueness of the game equilibrium solution of the model, including: The compensation price p set by the load aggregator in the lower-level game LA,j Benefit function for end users Find the values ​​of q respectively j,k Find the first and second derivatives of Let the first-order derivative Get the optimal solution for the end-user response strategy Substitute the optimal response strategy of the end user into the load aggregator's revenue function, Available P LA,j Taking the first and second order derivatives, we get: I LA,j The Hessian matrix of is a negative definite matrix, let the first-order derivative Get the optimal solution of the load aggregator compensation strategy: Substitute the optimal solution of the load aggregator compensation strategy into the optimal response strategy of the end user to obtain the adjusted end user response strategy and the aggregated response of the load aggregator, and then obtain the total aggregated response of all load aggregators, substitute it into the power grid company's profit function and derive it to obtain the optimal solution of the power grid company's incentive strategy in:

6. The three-party interactive load aggregator incentive model for participating in demand response according to claim 1, characterized in that: The distributed heuristic method is used to solve the game model. The specific steps include: Initialize the relevant parameters and calculate the initial profit value I of the power grid company under the initialization parameters G ; The grid company publishes the initial incentive price, and the subsequent incentive prices are based on the incentive price floor. Gradually iterate to the upper limit The load aggregator conducts lower-level bargaining based on the incentive price, and determines its optimal compensation price and optimal aggregate response volume through relevant formulas based on the situation of the end users it represents, and feeds the data back to the power grid company; The power grid company determines the demand response benefit I based on the data information fed back by the load aggregator. G ′ , if I G ′ ≥I G , then record the current incentive price and revenue value, and judge whether the decision satisfies the game equilibrium constraint. If the constraint is satisfied, end the iteration and output the result. If not, continue to the next iteration until the game equilibrium constraint is satisfied and the game equilibrium is achieved. During the operation of the algorithm, the power grid company only needs to send the trial incentive price to the load aggregator without having to grasp the various parameters of the end users in detail.

7. An application method for the incentive model for three-party interactive load aggregators to participate in demand response as described in claims 1-6, characterized in that: Includes grid companies, load aggregators and end users, including: Construct a two-level game structure. In the upper game, the power grid company, as the leader, sets incentive prices to guide load aggregators to participate in the response. The load aggregators, as followers, determine the aggregated response amount based on the incentive prices. In the lower-level game, the load aggregator, as the leader, sets the compensation price to encourage the end users to participate in the response. The end users, as followers, determine their own response amount based on the compensation price. Each game subject aims to maximize its own benefits and conducts information transmission and game competition through incentive prices and compensation prices.

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