Electric heating comprehensive energy balance control method and system based on master-slave game

Abstract

The invention discloses an electric heat comprehensive energy balance control method and system based on a master-slave game, and belongs to the technical field of comprehensive energy management, and the method comprises the steps: taking the benefit maximization of a comprehensive energy operator as a first objective function, constructing an upper layer model, and generating an optimal energy selling price, and decision variables comprise an electricity selling price and a heat selling price; building a lower-layer model by taking user income maximization as a second objective function, and determining an optimal output plan and a load adjustment plan in the lower-layer model through an optimal energy pricing given by the upper-layer model; and taking a comprehensive energy operator corresponding to the upper-layer model as a leader, taking a load aggregator corresponding to the lower-layer model as a follower, and achieving Stackelberg equilibrium through a master-slave game, so that electric heating comprehensive energy is subjected to equilibrium control. According to the method, better global economic performance can be obtained, and the balance between the electricity price and the customer satisfaction is considered at the same time.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated energy management, and in particular to a method and system for controlling electric and thermal integrated energy balance based on master-slave game. Background Art

[0002] As the electric-thermal integrated energy market continues to change, the traditional vertical integration structure is shifting towards a more interactive and competitive structure. However, the decentralized nature of the electric-thermal integrated energy system is becoming more and more obvious, which means that the traditional centralized optimization method is no longer able to reveal the interactive behavior between different stakeholders. Therefore, a more comprehensive and flexible approach is needed to explore the energy value interaction between various stakeholders.

[0003] The dynamic pricing of integrated energy system is essentially to solve the optimal solution problem in the system, which generally includes the minimum cost problem, the maximum benefit problem and other optimal problems. The total cost of system operation includes the sum of equipment operation and maintenance costs, power generation fuel costs, network loss costs, exhaust gas treatment costs, depreciation of energy storage equipment and energy conversion equipment. In the solution process, it is also necessary to consider the constraints on the parameter range. Considering the equipment output range and energy conservation in the actual problem, the constraints can be divided into balance constraints and imbalance constraints. The balance conditions include the balance constraints of electric energy flow in the power grid, the balance constraints of natural gas flow in the natural gas grid and the balance constraints of thermal flow in the thermal network; the imbalance constraints include the upper and lower limits of the generator output in the power grid, the pressure constraints of the water pipeline in the thermal network and the pressure constraints of the gas pipeline in the natural gas network, as well as the maximum power constraints of the energy conversion equipment, the maximum energy storage upper limit of the energy storage equipment and the non-negative energy storage in the equipment. Therefore, it is urgent to design a master-slave game-based electric and thermal integrated energy balance control technology to effectively improve energy utilization efficiency and promote sustainable energy development while meeting the diversified energy demand in the system. Summary of the invention

[0004] In order to solve the above problems, the purpose of the present invention is to provide an electric and thermal integrated energy balancing control technology based on master-slave game, which aims to solve the problem that the traditional hierarchical model can only ensure that the steady state of the system reaches the economic optimum, but ignores the economic problems in the dynamic tracking process, thereby obtaining better global economic performance while taking into account the balance between electricity prices and customer satisfaction.

[0005] In order to achieve the above technical objectives, the present application provides a method for controlling electric and thermal integrated energy balance based on master-slave game, comprising the following steps:

[0006] Taking the maximization of the integrated energy operator's profit as the first objective function, the upper model is constructed to generate the optimal energy selling price, where the decision variables include the electricity selling price and the heat selling price;

[0007] Taking user benefit maximization as the second objective function, the lower model is constructed, and the optimal output plan and load adjustment plan in the lower model are determined through the optimal energy pricing given by the upper model;

[0008] The integrated energy operator corresponding to the upper model is taken as the leader, and the load aggregator corresponding to the lower model is taken as the follower. The Stackelberg equilibrium is achieved through the master-slave game, so that the electric and thermal integrated energy is balanced and controlled.

[0009] Preferably, in the process of constructing the first objective function, the first objective function is constructed based on the revenue obtained by the integrated energy operator from supplying energy to users, the cost of supplying energy to users, the interaction cost with the upper-level power grid, and the penalty cost of heat supply interruption.

[0010] Preferably, in the process of constructing the upper-level model, the upper-level model is constructed based on the first objective function by setting the first constraint condition, wherein the first constraint condition is used to ensure that the energy procurement price of the integrated energy operator is slightly higher (lower) than the market price, and at the same time ensure that the energy is sold at a price slightly higher (lower) than the market price, thereby avoiding the energy supply side and the energy consumption side from directly trading with the power grid, ensuring market stability and fairness, and at the same time ensuring that the price is lower than the average.

[0011] Preferably, in the process of constructing the second objective function, the second objective function is constructed according to the user's utility function and energy cost, wherein the utility function is described by a quadratic function.

[0012] Preferably, in the process of constructing the lower-level model, the lower-level model is constructed based on the second objective function by setting the second constraint condition, wherein the second constraint condition includes: the shiftability constraint of the electric load, the reducibility constraint of the thermal load, the electric power balance constraint, the thermal power balance constraint, the wind turbine output constraint, the photovoltaic cell output constraint, the electric energy storage device constraint, the thermal energy storage device constraint, the gas turbine output constraint, the gas boiler output constraint, the grid interaction constraint and the exchange power constraint.

[0013] Preferably, in the process of the master-slave game, the output of each device in the lower model and the power of the shiftable electric load and the heat load that can be reduced are adjusted according to the dynamic electricity price determined by the upper model.

[0014] Preferably, in the process of achieving Stackelberg equilibrium, when the followers of the lower model make the corresponding optimal scheduling plan according to the energy pricing set by the leader of the upper model, and at the same time, the upper leader accepts the result of the feedback from the lower layer, it is considered that the master-slave game between the upper and lower layers has reached Stackelberg equilibrium.

[0015] Preferably, in the process of equilibrium control, a combined strategy of particle swarm algorithm and quadratic programming is used to solve distributed equilibrium, so that each participant can be optimized individually and finally achieve global equilibrium, wherein the quadratic programming algorithm is applied to the process of particle swarm algorithm to support the decision-making of integrated energy operators.

[0016] The present invention discloses an electric-heat integrated energy balancing control system based on master-slave game, comprising:

[0017] The first model building module is used to build an upper model with the maximization of the integrated energy operator's profit as the first objective function to generate the optimal energy selling price, wherein the decision variables include the electricity selling price and the heat selling price;

[0018] The second model building module is used to build a lower model with maximizing user benefits as the second objective function, and determine the optimal output plan and load adjustment plan in the lower model through the optimal energy pricing given by the upper model;

[0019] The balanced control module is used to take the integrated energy operator corresponding to the upper model as the leader and the load aggregator corresponding to the lower model as the follower, and achieve Stackelberg equilibrium through the master-slave game, so that the electric and thermal integrated energy can be balanced controlled.

[0020] Preferably, the balance control module is also used to use a combined strategy of particle swarm algorithm and quadratic programming to solve distributed balance, so that each participant can be optimized individually and ultimately achieve global balance, wherein the quadratic programming algorithm is applied to the process of the particle swarm algorithm to support the decision-making of integrated energy operators.

[0021] The present invention discloses the following technical effects:

[0022] The present invention takes into account two different stakeholders: the integrated energy system operator and the user load aggregator. As the upper-level leader, the integrated energy system operator formulates the optimal energy dynamic quotation strategy through the energy management strategy formulated by the lower-level followers; as the lower-level follower, the user load aggregator will formulate the corresponding energy management strategy according to the dynamic electricity price released by the upper layer; the existence of the unique solution of the proposed model is proved by proving the uniqueness of the Stackelberg equilibrium; the simulation verification is carried out through Matlab platform programming, and the effectiveness of the proposed model is verified by dividing two different scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. 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 creative work.

[0024] Figure 1 It is a simplified structural diagram of the electric-thermal integrated energy system containing new energy sources described in the present invention;

[0025] Figure 2 It is the dynamic pricing and energy management design framework of the electric-thermal integrated energy system based on master-slave game described in the present invention;

[0026] Figure 3 It is a schematic diagram of the solution process of the master-slave game algorithm of the present invention;

[0027] Figure 4 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0028] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0029] like Figure 1-4As shown, the present invention provides an electric-heat comprehensive energy balance control technology based on master-slave game. The electric-heat comprehensive energy system framework is a system that integrates electricity, heat, gas and other energy sources. It realizes energy efficiency, conservation and sustainable development through the integration and optimization of various energy sources. Its framework mainly includes the following aspects: 1. Energy production: This link mainly includes the production of various energy sources such as coal-fired power generation, nuclear power generation, wind energy, solar energy, and hydropower; 2. Energy conversion: This link mainly converts energy into various forms such as electricity, heat energy, and gas energy. For example, coal-fired power plants convert the heat energy generated by coal combustion into electricity; 3. Energy transmission: This link mainly delivers energy to users through power transmission, gas transmission, heat transmission, etc. to meet their needs; 4. Energy storage: This link mainly stores energy so that it can be called when needed, such as storing energy through batteries, heat storage tanks, etc.; 5. Energy utilization: This link mainly utilizes energy in every detail, such as applying energy to life through air conditioning, heating, lighting, etc. Through the above framework, the electric and thermal integrated energy system can achieve efficient utilization and conservation of energy, while also reducing environmental pollution and improving sustainable development capabilities.

[0030] This paper takes the electric-thermal integrated energy system as the research basis and studies the dynamic pricing and energy management method of the electric-thermal integrated energy system by adopting the master-slave game theory. Figure 1 The figure shows a simplified structural diagram of the electric-thermal integrated energy system containing new energy sources constructed by the present invention. As can be seen from the figure, the electric-thermal integrated energy system constructed by the present invention mainly includes energy conversion equipment such as wind turbines, photovoltaic cells, storage batteries, gas turbines, waste heat recovery devices, gas boilers and heat exchangers. The electric load of the electric-thermal integrated energy system is mainly supplied by the interaction with the upper power grid, the output of wind turbines, the output of photovoltaic cells, the output of batteries and the output of gas turbines; the thermal load in the electric-thermal integrated energy system is mainly supplied by the waste heat recovery device, the gas boiler and the heat storage tank through the heat exchanger.

[0031] like Figure 2 The figure shows the dynamic pricing and energy management design framework of the electric-thermal integrated energy system based on the master-slave game. As can be seen from the figure, the model is a two-layer model, with the upper layer being the leader layer and the lower layer being the follower layer. The upper layer model takes the maximization of the interests of the integrated energy seller as the objective function, which is achieved by optimizing the real-time electricity price and heat price in the model; the lower layer takes the maximization of the benefits of the electric-thermal integrated energy system operator and load aggregator as the objective function.

[0032] The present invention provides a master-slave game-based electric and thermal integrated energy balance control technology, which specifically includes the following contents:

[0033] The present invention constructs a dynamic pricing and energy management model for an electric-thermal integrated energy system, and the research is divided into two stages. The first stage corresponds to the upper-level model, with maximizing the revenue of integrated energy operators as the objective function, and the decision variables include the electricity selling price and the heat selling price. By formulating the optimal energy selling price, the revenue of the integrated energy operator is maximized. The second stage corresponds to the lower-level model, with maximizing user revenue as the objective function, and the optimal output plan and load adjustment plan in the lower-level model are determined by the optimal energy pricing given by the upper-level model. At this time, the upper-level model and the lower-level model influence each other, and the equilibrium solution is obtained through continuous cycle iteration.

[0034] 1. Upper model:

[0035] (1) Objective function:

[0036] In the electric-heat integrated energy system model constructed by the present invention, the upper model takes the maximization of the integrated energy operator's revenue as the objective function. It mainly includes four parts: the revenue obtained by the integrated energy operator from supplying energy to users, the cost of supplying energy to users, the interaction cost with the upper power grid, and the penalty cost of heating interruption. The specific mathematical model is as follows:

[0037]

[0038] Where: T represents the scheduling period. This invention studies the day-ahead scheduling, so the scheduling period is selected as 24 hours a day; It represents the revenue obtained by the integrated energy operator when supplying energy to users at time t; It represents the energy supply cost when the integrated energy operator supplies energy to users at time t; It represents the cost of the integrated energy operator interacting with the upper grid at time t. It means purchasing electricity from the upper grid. It means selling electricity to the upper grid; represents the penalty cost of heat interruption when the integrated energy operator supplies energy to users at all times; Δt represents the length of time, which is 1h in the present invention; Represents the power load demand on the user side at time t; Indicates the heat load demand on the user side at time t; represents the price of electricity sold at time t; represents the price of heat energy sold at time t; Represents the output electric power of the energy supply side at time t; Represents the output electric power of the energy supply side at time t; represents the price of purchasing electricity from the energy supplier at time t; It represents the price of purchasing heat energy from the energy supplier at time t; represents the grid-connected electricity price at time t; represents the electricity price of the power grid at time t; h Represents the penalty coefficient of the heating terminal of the integrated energy operator.

[0039] (2) Constraints:

[0040] In order to prevent the problem from getting worse, it is necessary to ensure that the energy purchase price of the integrated energy operator is slightly higher (lower) than the market price, and at the same time ensure that the energy is sold at a price slightly higher (lower) than the market price, so as to avoid the energy supply side and the energy consumption side from directly trading with the power grid and ensure the stability and fairness of the market. The specific mathematical model is described as follows:

[0041]

[0042] Where: Indicates the lowest lower limit of heat energy price; Indicates the upper limit of heat price.

[0043] At the same time, when the decision variables in the upper model determine the price of electricity and heat, it is also necessary to ensure that the price is lower than the average value as follows:

[0044]

[0045] Where: It represents the upper limit of the average electricity selling price of integrated energy operators; Indicates the upper limit of the average heat selling price of integrated energy operators.

[0046] 2. Lower model:

[0047] In the electric-thermal integrated energy system model constructed by the present invention, the lower model takes maximizing user benefits as the objective function. It mainly consists of two parts: the user's utility function and the user's energy cost. The main function of the lower model is to adjust the output of each device in the lower model and the power of the shiftable electric load and the heat load that can be reduced according to the dynamic electricity price determined by the upper model. The specific mathematical model is as follows:

[0048] (1) Objective function:

[0049] The objective function of the lower model includes two parts: the user's utility function and the user's energy cost. The specific mathematical model is as follows:

[0050]

[0051] Where: represents the user's utility function. It is a function that measures the satisfaction of users when purchasing electricity and heat. Generally, this function has the characteristics of non-decreasing and convexity, and it can be expressed in multiple forms such as quadratic form and logarithmic form. In the present invention, a quadratic function is used to describe the utility function. The specific mathematical model is as follows:

[0052]

[0053] Where: v e , α e It represents the user's preference coefficient for electric energy; v h , α h It represents the user's preference coefficient for thermal energy.

[0054] (2) Constraints:

[0055] The constraints of the lower-level model mainly include the shiftability constraint of the electric load, the reducibility constraint of the thermal load, the output constraint of each device in the electric-thermal integrated energy system, the balance constraint of the electric power, and the balance constraint of the thermal power

[21] .

[0056] 1) Translational constraints of electrical loads

[0057] The shiftable constraint of electric load means that in the system, the electric load can be shifted or adjusted in different time periods, but its total amount must remain unchanged. This means that although the size and distribution of the electric load may be different in different time periods, the total load must be equal to a given constant value. Since the electric load plays a vital role in the operation of the power system, the system planning and optimization must be carried out under the premise of satisfying this shiftable constraint.

[0058]

[0059] Where: It represents the fixed electric load at time t in the integrated energy system. This part of the electric load is not easy to adjust and therefore does not participate in demand response. It represents the electric load that can be shifted at time t in the integrated energy system. This part of the electric energy users will adjust their own electricity consumption behavior according to the electricity price information released by the integrated energy operator, so as to reduce the electricity purchase cost as much as possible; W represents the upper limit of the electric load that can be shifted at time t in the integrated energy system; sel It represents the total amount of shiftable load, that is, the total amount of energy load of users during the dispatch period participating in the electric load demand response needs to remain unchanged.

[0060] 2) Reducible constraints on heat load:

[0061] The heat load reducibility constraint means that in the system, the heat load can be reduced to a certain extent, but it must meet the requirements of system operation. This means that even if an emergency or other changes cause the heat load to be reduced, this must be done without affecting the normal operation of the system. Since the heat load is very important for the heating system, the system must be planned and optimized under the premise of meeting the reducibility constraint to ensure the safety and stability of the system.

[0062]

[0063] Where: It represents the fixed heat load demand at time t in the integrated energy system; It represents the heat load demand that can be reduced at time t in the integrated energy system; Indicates the upper limit of load reduction.

[0064] 3) Electric power balance constraints:

[0065] The power balance constraint means that in the power system, the total power generation must be equal to the sum of the total load power and the system loss power. This means that the total power supply of the power system must be equal to the sum of the total power consumption and the system loss to ensure the stable operation of the system. This constraint is very important in practical applications, because only when the power balance constraint is met can the power system operate normally, avoiding problems such as overload and insufficient power supply, thereby ensuring the reliability and safety of the system.

[0066]

[0067] Where: It represents the actual output power of the wind turbine at time t; It represents the actual electric power output of the photovoltaic cell at time t.

[0068] 4) Thermal power balance constraints:

[0069] In a thermodynamic heating system, a balance must be maintained between the heat source supply and consumer demand. The heating temperature rises as consumer demand decreases, and vice versa. Since the control of the heating temperature is crucial to the quality of heating, it is necessary to ensure that the scheduling results match the actual demand. It is worth noting that the present invention assumes that there is no heat loss during the transmission process.

[0070]

[0071] 5) Wind turbine output constraints:

[0072]

[0073] Where: It represents the predicted value of the electric power output of the wind turbine at time t.

[0074] 6) Photovoltaic cell output constraints

[0075]

[0076] Where: It represents the predicted value of the electric power output of the photovoltaic cell at time t;

[0077] 7) Constraints on electric energy storage devices:

[0078] The constraints on electric energy storage devices are mainly the following: 1. Safety constraints: Electric energy storage devices must comply with relevant safety standards and requirements to ensure safety during use; 2. Economic constraints: Electric energy storage devices need to store and release energy within a certain cost range to ensure economic benefits; 3. Supply and demand constraints: Electric energy storage devices need to store and release energy according to supply and demand to ensure energy balance and stable supply.

[0079] The electric energy storage device needs to meet a series of constraints such as the upper and lower limits of the charging / discharging power and the state of charge limit of the energy storage device. The specific mathematical model is as follows:

[0080]

[0081] Where: represents the charging power of the battery at time t; represents the discharge power of the battery at time t; Indicates the charge and discharge status of the battery at time t. It is a 0-1 variable. When it is 1, it means discharging, and when it is 0, it means charging. and E is the maximum and minimum power of battery charging and discharging respectively; ba,min and E ba,max are the maximum and minimum capacities of the battery respectively.

[0082] 8) Thermal energy storage device constraints:

[0083] Similar to the constraints of electric energy storage devices, thermal energy storage devices also need to meet a series of constraints such as the upper and lower limits of heat storage / release power and the energy storage state limit constraints of the thermal storage device. The specific mathematical model is as follows:

[0084]

[0085] Where: represents the charging power of the battery at time t; represents the discharge power of the battery at time t; Indicates the charge and discharge status of the battery at time t. It is a 0-1 variable. When it is 1, it means discharging, and when it is 0, it means charging. and E is the maximum and minimum power of battery charging and discharging respectively; tst,min and E tst,max are the maximum and minimum capacities of the battery respectively.

[0086] 9) Gas turbine output constraints:

[0087] The gas turbine must also meet the operating power constraints and ramp constraints during operation. The specific mathematical model is as follows:

[0088]

[0089] Where: Indicates the upper limit of the gas turbine output electrical power; Indicates the lower limit of the gas turbine output electrical power; Indicates the upper limit of the gas turbine climbing power; Indicates the upper limit of the gas turbine ramp power.

[0090] 10) Gas boiler output constraints:

[0091]

[0092] Where: Indicates the upper limit of the thermal power output of the gas boiler.

[0093] 11) Grid interaction constraints:

[0094] In order to ensure the balance of the electric load within the integrated energy system, electricity can be sold or purchased from the external distribution network, but the interactive power limit of the distribution network must be observed, and the purchase and sale operations cannot be performed at the same time to ensure the safe operation of the distribution network. The specific mathematical model is as follows:

[0095]

[0096] Where: Indicates the electricity purchasing status of the electric-thermal integrated energy system at the moment. When it is 1, it means it is currently in the electricity purchasing status; Indicates the power selling status of the electric-thermal integrated energy system at the moment. When it is 1, it means it is currently in the power selling status; It indicates the upper limit of electricity purchase of the electric-thermal integrated energy system at the moment; It indicates the upper limit of electricity purchase of the electric-thermal integrated energy system at the moment.

[0097] 12) Switching power constraints:

[0098]

[0099]

[0100] Where: P grid.max Indicates the maximum power purchased by the power grid; P grid.min Indicates the minimum power purchase power of the power grid; P grid.up Indicates the upper limit of the power purchase power of the power grid; P grid.down Indicates the lower limit of the power ramp of the power purchased by the power grid.

[0101] 3. Master-slave game framework:

[0102] 3.1 Basic Concepts

[0103] According to the above-established electric-thermal integrated energy system model, it can be seen that the upper-level model takes maximizing the revenue of the integrated energy system operator as its objective function, and maximizes the revenue of the integrated energy system operator by formulating dynamic energy prices. The lower-level model takes maximizing user revenue as its objective function, and adjusts the output plan and load adjustment of each device in the integrated energy system through the energy price formulated by the upper-level integrated energy operator, so as to maximize user revenue. At the same time, the output plan of the lower layer will affect the energy price formulated by the upper layer. Therefore, the present invention takes the upper-level integrated energy operator as the leader and the lower-level load aggregator as the follower, and establishes a master-slave Stackelberg game model, which can be expressed as follows:

[0104] G={N;ρ ier ; {δ user}; F ier ; {F user}} (44)

[0105] Where: the subscript ier represents the integrated energy operator; the subscript user represents the load aggregator.

[0106] The above game model contains three elements: participants, strategies, and benefits, which can be expressed as follows:

[0107] (1) Participants: The dynamic pricing and energy management model of the electric-thermal integrated energy system based on master-slave game constructed by the present invention includes two participants, the integrated energy operator and the load aggregator, which are expressed in the form of a set as Nier, user.

[0108] (2) Strategy: As the leader, the upper model needs to first formulate energy prices, including electricity prices and heat prices, which are expressed in vector form as ρ ier =(C e,s ,c h，s , c e,b ,c h,b); As a follower, the lower model will adjust the output and load of each device according to the energy price determined by the upper layer after the upper layer electricity price is set. It can be expressed in vector form as δ use1 =(P sel , Q chl ,H IES ,P IES ).

[0109] (3) Benefits: The benefits of the upper model are aimed at maximizing the benefits of the integrated energy operator and are calculated using formula (1). The benefits of the lower model are aimed at maximizing the benefits of users and are calculated using formula (12).

[0110] 3.2 Stackelberg equilibrium:

[0111] When the followers of the lower model make the corresponding optimal scheduling plan according to the energy pricing set by the leader of the upper model, and the upper leader accepts the result of the feedback from the lower model, it is considered that the master-slave game between the upper and lower layers has reached the Stackelberg equilibrium. The following constraints must also be met:

[0112]

[0113] In the Stackelberg equilibrium solution, the integrated energy operator and the user load aggregator are two interested parties, and it is impossible to obtain the optimal solution based on one party alone. The following theorem proves the uniqueness of the existence of the Stackelberg equilibrium solution.

[0114] Theorem: When the master-slave game model satisfies the following conditions, there is a unique Stackelberg equilibrium:

[0115] (1) When the leader sets the optimal energy price, the followers have a unique optimal solution;

[0116] (2) When followers make corresponding output plans based on the energy prices given by the leader, the leader has a unique optimal solution.

[0117] Proof (1): Take greater than zero as an example, and the rest of the cases are similar. The objective function (12) of the load aggregator is respectively Find the first-order partial derivative and get:

[0118]

[0119] Let equation (47) and equation (48) equal to 0, we can get:

[0120]

[0121] Then, the objective function (12) of the load aggregator is respectively Find the second-order partial derivative and we get:

[0122]

[0123] According to formula (47) and formula (51), it can be proved that there is a unique optimal solution.

[0124] Proof (2): When the followers make corresponding decision plans, the upper-level leader’s profit objective function can be changed to:

[0125]

[0126] After taking the first-order and second-order partial derivatives of formula (52), the final Hessian matrix of the leader payoff function is obtained as:

[0127]

[0128] According to formula (54), it can be found that the Hessian matrix is ​​negative definite and has a maximum point, that is, there is a unique optimal solution.

[0129] 4. Solution method:

[0130] In the highly competitive electricity market, information is opaque, and traditional centralized optimization methods require a clear understanding of detailed information such as equipment parameters and energy preferences of all participants. To solve this problem, the present invention proposes a distributed equilibrium solution method, which is implemented using a combination strategy of particle swarm algorithm and quadratic programming, avoiding reliance on detailed information of all participants. Each participant can be optimized individually to ultimately achieve global equilibrium. Leaders operating integrated energy need to make a series of decisions, including solving large-scale nonlinear optimization problems. In order to reduce the complexity of the solution and improve the optimization capability, a particle swarm algorithm can be used. As a follower, the user load aggregator uses a quadratic programming model for solution because its optimization objective is a quadratic function. The quadratic programming algorithm is applied to the process of the particle swarm algorithm to support the decision-making of integrated energy operators. This algorithm enables the energy supply side and the energy consumption side to only rely on the price signal of the integrated energy operator to adjust the power signal, thereby effectively avoiding the leakage of sensitive information and ensuring the privacy and security of information of all parties. The specific algorithm solution process is as follows Figure 3 shown.

[0131] The present invention studies the dynamic pricing and energy management design of the electric-thermal integrated energy system based on master-slave game. In the present invention, a dynamic pricing and energy management design scheme of the electric-thermal integrated energy system based on master-slave game theory is discussed. The scheme integrates components such as integrated energy sellers, new energy electric-thermal integrated energy systems, and adjustable loads. With the integrated energy seller as the center, it coordinates the interconnected power network to achieve economical and efficient energy supply and scientific and reasonable energy utilization. In this way, comprehensive management and effective allocation of integrated energy can be achieved to meet the society's demand for energy, and at the same time, it can also promote the development of the new energy industry and the realization of environmental protection goals.

[0132] The concept of integrated energy sellers proposed in the present invention is expanded on the basis of power sales companies in the electricity market. Integrated energy sellers not only sell electricity, but also provide thermal energy trading services to meet users' needs for different energy sources. This integrated sales model can better meet the personalized needs of users, and also play a positive role in promoting the development of the electricity market. The role of integrated energy sellers is very critical. As a bridge between energy producers and consumers, it aims to achieve an effective balance between supply and demand. These sellers can obtain better prices when purchasing electricity, heat and other energy, and sell them to various users to earn the difference. This model can provide a more flexible pricing strategy, and at the same time encourage the participation of distributed energy systems and the scientific use of energy by small and medium-sized community users, which will have a positive effect on competition in the electricity market.

[0133] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0134] In the description of the present invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0135] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for controlling electric and thermal integrated energy balance based on master-slave game, characterized in that: The following steps are involved: Taking the maximization of the integrated energy operator's profit as the first objective function, the upper model is constructed to generate the optimal energy selling price, where the decision variables include the electricity selling price and the heat selling price; Taking user benefit maximization as the second objective function, the lower model is constructed, and the optimal output plan and load adjustment plan in the lower model are determined through the optimal energy pricing given by the upper model; The integrated energy operator corresponding to the upper model is taken as the leader, and the load aggregator corresponding to the lower model is taken as the follower. The Stackelberg equilibrium is achieved through the master-slave game, so that the electric and thermal integrated energy is balanced and controlled.

2. According to claim 1, a method for controlling electric and thermal integrated energy balance based on master-slave game, characterized in that: In the process of constructing the first objective function, the first objective function is constructed based on the revenue obtained by the integrated energy operator from supplying energy to users, the cost of supplying energy to users, the interaction cost with the upper-level power grid, and the penalty cost of heat supply interruption.

3. According to claim 2, a method for controlling electric and thermal integrated energy balance based on master-slave game, characterized in that: In the process of constructing the upper-level model, based on the first objective function, the upper-level model is constructed by setting the first constraint condition, wherein the first constraint condition is used to ensure that the energy procurement price of the integrated energy operator is slightly higher (lower) than the market price, and at the same time ensure that the energy is sold at a price slightly higher (lower) than the market price, thereby avoiding the energy supply side and the energy consumption side from directly trading with the power grid, ensuring the stability and fairness of the market, and at the same time ensuring that the price is lower than the average.

4. According to claim 3, a method for controlling electric and thermal integrated energy balance based on master-slave game, characterized in that: In the process of constructing the second objective function, the second objective function is constructed according to the user's utility function and energy cost, wherein the utility function is described by a quadratic function.

5. The electric-thermal integrated energy balance control method based on master-slave game according to claim 4 is characterized by: In the process of constructing the lower-level model, based on the second objective function, the lower-level model is constructed by setting the second constraint condition, wherein the second constraint condition includes: the shiftable constraint of electric load, the reducible constraint of thermal load, the electric power balance constraint, the thermal power balance constraint, the wind turbine output constraint, the photovoltaic cell output constraint, the electric energy storage device constraint, the thermal energy storage device constraint, the gas turbine output constraint, the gas boiler output constraint, the grid interaction constraint and the exchange power constraint.

6. The electric-thermal integrated energy balance control method based on master-slave game according to claim 5 is characterized by: In the process of master-slave game, the output of each device in the lower model and the power that can be shifted and the heat load that can be reduced are adjusted according to the dynamic electricity price determined by the upper model.

7. The electric-thermal integrated energy balance control method based on master-slave game according to claim 6 is characterized by: In the process of achieving Stackelberg equilibrium, when the followers of the lower model make the corresponding optimal scheduling plan according to the energy pricing set by the leader of the upper model, and the upper leader accepts the feedback from the lower model, it is considered that the master-slave game between the upper and lower layers has reached Stackelberg equilibrium.

8. The electric-thermal integrated energy balance control method based on master-slave game according to claim 7 is characterized by: In the process of equilibrium control, the combined strategy of particle swarm algorithm and quadratic programming is used to solve distributed equilibrium, so that each participant can be optimized individually and finally achieve global equilibrium. Among them, the quadratic programming algorithm is applied to the process of particle swarm algorithm to support the decision-making of integrated energy operators.

9. An electric and thermal integrated energy balance control system based on master-slave game, characterized in that: include: The first model building module is used to build an upper model with the maximization of the integrated energy operator's profit as the first objective function to generate the optimal energy selling price, wherein the decision variables include the electricity selling price and the heat selling price; The second model building module is used to build a lower model with maximizing user benefits as the second objective function, and determine the optimal output plan and load adjustment plan in the lower model through the optimal energy pricing given by the upper model; The balancing control module is used to take the integrated energy operator corresponding to the upper model as the leader and the load aggregator corresponding to the lower model as the follower, and achieve Stackelberg equilibrium through the master-slave game, so that the electric and thermal integrated energy is balanced and controlled.

10. The electric-thermal integrated energy balance control system based on master-slave game according to claim 9, characterized in that: The balance control module is also used to use the combined strategy of particle swarm algorithm and quadratic programming to solve the distributed balance, so that each participant can optimize individually, and finally achieve The global equilibrium is achieved, in which the quadratic programming algorithm is applied to the particle swarm algorithm process. To support the decision making of integrated energy operators.

Images