Comprehensive energy multi-energy network energy sharing mutual aid optimization strategy based on cooperative game

Abstract

The invention discloses a comprehensive energy multi-energy network energy sharing mutual aid optimization strategy based on a cooperative game, and belongs to the field of multi-energy network economic optimization, and the strategy comprises the following steps: S1, building a multi-energy network multi-energy flow model for calculating multi-energy complementary characteristics of three parks; s2, a target function with the optimal economical efficiency is established for the multi-energy network multi-energy flow model; and S3, solving the target function by using the multi-energy network cooperation sharing game model based on the ADMM algorithm. By constructing the multi-energy network multi-energy flow modeling considering the multi-energy complementary characteristic, efficient cooperative operation between different comprehensive energy systems is achieved, energy supply and demand balance is achieved, overflow energy is efficiently utilized, energy consumption is reduced, and energy utilization efficiency is improved. And a multi-energy network optimization model considering a cooperative sharing game is constructed and solved, so that the problem of multi-subject benefit distribution is solved, the total cost is lowest, efficient integration and utilization of multi-element energy are finally achieved, and the overall economic benefit of the park is maximized.

Description

Technical Field

[0001] The present invention relates to the field of multi-energy network economic optimization, and in particular to an energy sharing and mutual assistance optimization strategy for an integrated energy multi-energy network based on cooperative game. Background Art

[0002] The integrated energy network is a core component of the modern energy architecture. It integrates multiple energy forms such as electricity, natural gas, and thermal energy, and relies on cutting-edge energy conversion and storage technology to achieve the integration and utilization of these energy sources, realizing the horizontal energy sharing and mutual assistance of multiple energy sources and the vertical external output. This integrated energy system can not only improve the overall energy utilization efficiency based on the output of a single energy system, but also absorb new energy on a large scale, which has a significant and lasting impact on promoting the long-term progress of the energy industry. By constructing a multi-energy flow model, the multi-energy network realizes the efficient transmission and distribution of various energy sources in a complex network, which lays a solid foundation for building a green, energy-saving, safe, reliable and efficient energy system.

[0003] Existing research on integrated energy systems has introduced cooperative game models to solve the problem of interest distribution among multiple subjects. By considering complementarity and dependence, efficient energy utilization and cost minimization are achieved. The complementarity of electricity, gas, cooling and heating equipment is modeled, and optimization methods such as Nash equilibrium and Shapley value are used to provide theoretical support and new ideas for the coordinated operation and interest distribution of the system. The cooperative game model provides a theoretical basis for solving the problem of interest distribution among multiple subjects in integrated energy systems, but current research faces multiple challenges, namely, as the scale of the system expands, the complexity of the model increases, and the requirements for computational efficiency and calculation accuracy increase; the design of cooperation and incentive mechanisms is still imperfect, and it is difficult to ensure a win-win situation. Therefore, future research needs to conduct in-depth exploration and improvement on these challenges to promote the widespread application and sustainable development of cooperative game models in the coordinated operation of integrated energy systems, and achieve more efficient and fairer energy utilization and cost minimization. Summary of the invention

[0004] The purpose of the present invention is to provide an energy sharing and mutual assistance optimization strategy for a comprehensive energy multi-energy network based on cooperative game, which aims to achieve efficient coordinated operation between different comprehensive energy systems by constructing a multi-energy network multi-energy flow model that takes into account the multi-energy complementary characteristics, achieve energy supply and demand balance and efficient use of overflow energy, reduce energy consumption, and improve energy utilization efficiency. At the same time, in the process of coordinated operation of each system, a multi-energy network optimization model that takes into account cooperative sharing games is constructed and solved to solve the problem of multi-subject interest distribution. On the premise of balancing the interests of each park, the lowest total cost is achieved, and ultimately the efficient integration and utilization of multiple energy sources is achieved, and the overall economic benefits of the park are maximized.

[0005] To achieve the above objectives, the present invention provides an energy sharing and mutual assistance optimization strategy for a comprehensive energy multi-energy network based on cooperative game, comprising the following steps:

[0006] S1: Establish a multi-energy network and multi-energy flow model to calculate the multi-energy complementary characteristics of three parks including commercial area, industrial area and residential area;

[0007] S2: Establish the economically optimal objective function for the multi-energy network and multi-energy flow model;

[0008] S3: Use the multi-energy network cooperative sharing game model based on the ADMM algorithm to solve the objective function.

[0009] Preferably, the specific steps of S1 are:

[0010] S101: Establish an operation model of multi-energy network energy production equipment, conversion equipment, and storage equipment;

[0011] S102: Calculate the complementary characteristics between different energy sources;

[0012] S103: Divide the operation model and grid load in S101 into three parts: commercial area, industrial area and residential area, and establish a multi-energy network energy sharing and mutual assistance system integrating the operation model in S101.

[0013] Preferably, the operation model established in S101 specifically includes:

[0014] Photovoltaic generator model:

[0015]

[0016]

[0017] In the formula, f is the basic derating factor, which is 0.9; k is the influence coefficient of temperature on power, which is -0.47% / ℃; Indicates the upper limit of photovoltaic output power;

[0018] Wind turbine model:

[0019]

[0020]

[0021] Where P wt,rate is the rated output power, v r is the rated wind speed, v is the real-time wind speed, v ct is the wind speed at the start of power generation, v c0 To stop the wind speed for power generation, is the upper limit of the rated power of the fan, P wt(v) is the output power of the wind turbine. For wind turbines of the same batch and model, at a certain moment, the power output of the wind turbine generator is:

[0022] P wt (v) = NP wt (v);

[0023] Where N is the number of wind power generation devices in the wind turbine generator set;

[0024] Microturbine Model:

[0025]

[0026] In the formula, is the output power of the micro gas turbine at time t; is the waste heat of the micro gas turbine at time t; η MT , η l are the power generation efficiency and heat dissipation loss coefficient of the micro gas turbine respectively. The power generation efficiency η of the micro gas turbine MT for:

[0027]

[0028] The power generation output capacity and ramp rate limit of the micro turbine (MT) are constructed as follows:

[0029]

[0030]

[0031] In the formula, It is the start / stop status flag of MT in period t. It is recorded as 0 when MT is stopped, and 1 otherwise. and They are the upper and lower limits of MT’s power generation respectively; and They are the upper and lower limits of MT climbing rate respectively;

[0032] Gas boiler (GB) model:

[0033]

[0034]

[0035] In the formula, is the output thermal power of GB at time t; is the natural gas input by GB at time t; η GB is the heat generation efficiency of GB; is the maximum output power of GB, is the minimum output power of GB;

[0036] Recovery Heating Boiler (RHB) Model:

[0037]

[0038]

[0039] In the formula, is the output thermal power of RHB at moment t; is the waste heat recovery efficiency of MT; is the waste heat recovery efficiency of GB; C RHB is the heating coefficient of RHB; is the maximum RHB output power, is the minimum output power of RHB;

[0040] Electric Refrigeration / Heat Engine (EC) Model:

[0041]

[0042]

[0043] In the formula is the EC output power at time t; is the input power of EC at time t; COP EC is the transfer coefficient; and are the minimum and maximum values ​​of EC output power respectively;

[0044] Energy storage equipment (EES) model:

[0045] The mathematical model of the energy storage battery is:

[0046]

[0047] The constraints to ensure the safe state of the energy storage battery are:

[0048]

[0049] In the formula, are the energy storage capacity of the energy storage battery at time t and time t-1 respectively; e is the self-damage rate of the energy storage device; They are respectively the charging and discharging power range of the energy storage battery at time t; are the charging and discharging efficiencies of the energy storage battery at time point t respectively; are the charging and discharging states, which are 0-1 variables; Δt is the charging and discharging time, which is 1h; are the maximum storage capacity and minimum reserved capacity of the energy storage battery respectively; They are the maximum power input and output capabilities of the energy storage battery respectively; T is a cycle (24h), that is, the charge before and after a cycle remains consistent.

[0050] Preferably, in S102, the complementarity of the two different types of energy is:

[0051] {E1, E2; A};

[0052] In the formula, E1 and E2 represent two different types of energy; A represents the performance index; by observing the changing trend of f, the mutual complementation ability of two different types of energy in specific performance indicators can be evaluated. The calculation formula f is:

[0053]

[0054] In the formula, f is the degree of association, P f Represents the total output of the two energy sources, P E1 , P E2 Indicates the output of the two energy sources respectively;

[0055] Based on the comparison of the complementarity of two energy sources on a certain performance indicator, it is extended to the mutual complementarity of multiple energy sources on a certain performance parameter:

[0056]

[0057] In the formula It indicates the correlation degree between the i-th energy source and the j-th energy source under x performance indicators.

[0058] Preferably, the specific steps of S2 are:

[0059] S201: Construct a function with the goal of economic optimization;

[0060] S202: Construct constraints to ensure the normal operation of the multi-energy network energy sharing and mutual assistance system.

[0061] Preferably, in S201, the objective function is:

[0062] minC=C1+C2+C3+C4+C5;

[0063] In the formula, C represents the total system operating expenses, C1 represents the electricity purchase cost, C2 represents the natural gas purchase cost, C3 represents the operation and maintenance cost, C4 represents the transmission pipeline configuration cost, and C5 represents the interactive benefits with the distribution network.

[0064]

[0065] In the formula, and represents the gas purchase price and electricity purchase power of the park in the representative period y under scenario s during period t;

[0066]

[0067]

[0068] In the formula, and It represents the calorific value cost of gas consumption and the output power of gas turbine and gas boiler in the park in the representative period y under scenario s during period t;

[0069]

[0070] In the formula, and They are the operation and maintenance factors and power output corresponding to the equipment respectively;

[0071]

[0072] In the formula, T is the total number of scheduling periods throughout the day; is the thermal energy purchase power of the subject in the representative period y under scenario s during period t; p , G , B are the corresponding energy transfer coefficients respectively;

[0073]

[0074] Where: is the power sold by the park to the distribution network in time period t; The power purchased from the power distribution grid by the park in time period t; are the corresponding electricity selling price and electricity purchasing cost respectively.

[0075] Preferably, in S202, the constraint conditions include:

[0076] Electrical power balance:

[0077]

[0078] Thermal power balance:

[0079]

[0080] The power balance constraint to ensure continuous energy supply is:

[0081]

[0082] In the formula, Indicates the output of the corresponding energy equipment in the park, The output limit of the corresponding energy equipment in the park;

[0083] The power constraint for interaction with the distribution network is:

[0084]

[0085]

[0086] In the formula, To limit the power of buying and selling electricity to the distribution network, The maximum power limit for buying and selling electricity to the distribution network.

[0087] Preferably, the specific process of S3 is:

[0088] Use the ADMM algorithm to solve convex optimization problems:

[0089] minx,f(x);

[0090] stAx = c;

[0091] In the formula, x is the optimization variable, f(x) is a convex function, A and c are known coefficient matrices and vectors;

[0092] Subsequently, the Lagrange multiplier λ is used to separate the electricity transaction prices in the commercial area, industrial area, and residential area:

[0093]

[0094] In the formula, The prices that commercial areas expect to buy electricity from industrial areas and the prices that industrial areas expect to buy electricity from commercial areas are respectively; The prices that commercial areas expect to buy electricity from residential areas and the prices that residential areas expect to buy electricity from commercial areas are respectively; The prices that industrial areas expect to buy electricity from residential areas and residential areas expect to buy electricity from industrial areas respectively;

[0095] Finally, the augmented Lagrangian function is constructed based on the expectations of multiple agents and the constraints, and the optimal total cost of each agent is obtained according to the ADMM principle.

[0096] Therefore, the present invention adopts the above-mentioned structure of the comprehensive energy multi-energy network energy sharing mutual assistance optimization strategy based on cooperative game, which includes the following advantages:

[0097] (1) Through the preset modeling parameters and specific conditions, a cooperative sharing game model of a multi-energy network containing integrated energy is constructed that takes into account energy sharing and mutual assistance. Combined with the multi-energy network multi-energy flow model that takes into account the multi-energy complementary characteristics, the integrated energy in different parks is scientifically laid out and allocated to obtain the optimal processing strategy.

[0098] (2) The specific construction of the data optimization model includes input unit, judgment unit and optimization unit, which improves the rationality of the benefit distribution of each park, ensures the efficiency of energy utilization and the reduction of overall cost.

[0099] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0100] Figure 1 It is a structural schematic diagram of the energy sharing and mutual assistance optimization strategy of the comprehensive energy multi-energy network based on cooperative game of the present invention;

[0101] Figure 2 This is a multi-energy network multi-energy flow model architecture diagram of the present invention that takes into account the multi-energy complementary characteristics of the energy sharing and mutual assistance optimization strategy of the comprehensive energy multi-energy network based on cooperative game;

[0102] Figure 3 This is a diagram of the architecture of a cooperative sharing game model of an integrated energy multi-energy network that takes into account energy sharing and mutual assistance for the energy sharing and mutual assistance optimization strategy of the integrated energy multi-energy network based on cooperative game of the present invention. DETAILED DESCRIPTION

[0103] Example

[0104] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0105] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0106] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0107] In the description of the present invention, it should be noted that the terms "upper", "lower", "inside", "outside", etc. indicate directions or positional relationships based on the directions or positional relationships shown in the accompanying drawings, or are directions or positional relationships in which the product of the invention is usually placed when in use. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as a limitation on the present invention.

[0108] In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "setting", "installation" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0109] Some embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0110] In the description of the present invention, it should be noted that the directions or positional relationships indicated by terms such as “upper”, “lower”, “left”, “right”, “inside” and “outside” are based on the directions or positional relationships shown in the accompanying drawings and are only for the convenience of describing the present invention and simplifying the description. They do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, they cannot be understood as limitations on the present invention.

[0111] The specific model specifications need to be selected and determined based on the actual specifications of the device, and the specific selection calculation method adopts the existing technology in this field, so it will not be described in detail.

[0112] like Figures 1 to 3 As shown, the energy sharing and mutual assistance optimization strategy of the comprehensive energy multi-energy network based on cooperative game in the present invention includes the following steps:

[0113] S1: Establish a multi-energy network and multi-energy flow model to calculate the multi-energy complementary characteristics of three parks including commercial area, industrial area and residential area;

[0114] The specific steps of S1 are:

[0115] S101: Establish an operation model of multi-energy network energy production equipment, conversion equipment, and storage equipment;

[0116] In a multi-energy complementary integrated energy system, due to the various types of equipment involved and their unique parameters, their energy needs and utilization patterns are also different. Therefore, when deeply studying the optimized operation of the system, the first step is to deeply analyze the characteristics of each equipment unit in the system and establish a corresponding mathematical model. Then, based on this starting point, the overall system is comprehensively designed and optimized with the goal of improving operating efficiency. In this process, the key is to build a mathematical model covering the flow of multiple energy sources for the main equipment in the integrated energy network.

[0117] The operation model established in S101 specifically includes:

[0118] In recent years, photovoltaic power generation technology has achieved rapid development and has been widely adopted and implemented in the power market. Photovoltaic generator model:

[0119]

[0120]

[0121] In the formula, f is the basic derating factor, which is 0.9; k is the influence coefficient of temperature on power, which is -0.47% / ℃; Indicates the upper limit of photovoltaic output power;

[0122] Wind resources are abundant around the world and are renewable, clean and pollution-free. The output power Pwt(v) generated by a wind turbine depends on wind speed and direction. Wind turbine model:

[0123]

[0124]

[0125] Where P wt,rate is the rated output power, v r is the rated wind speed, v is the real-time wind speed, v ct is the wind speed at the start of power generation, v c0 To stop the wind speed for power generation, is the upper limit of the rated power of the fan, P wt (v) is the output power of the wind turbine. For wind turbines of the same batch and model, at a certain moment, the power output of the wind turbine generator is:

[0126] P wt (v) = NP wt (v);

[0127] Where N is the number of wind power generation devices in the wind turbine generator set;

[0128] Micro gas turbines are known for their high efficiency, miniaturization, and flexible control performance. Their operating mechanism is to inject high-pressure and burned natural gas into the impeller, causing the impeller to rotate at high speed, thereby driving the generator to generate electricity. Micro gas turbine model:

[0129]

[0130] In the formula, is the output power of the micro gas turbine at time t; is the waste heat of the micro gas turbine at time t; η MT , η l are the power generation efficiency and heat dissipation loss coefficient of the micro gas turbine respectively. The power generation efficiency η of the micro gas turbine MT for:

[0131]

[0132] The power generation output capacity and ramp rate limit of the micro turbine (MT) are constructed as follows:

[0133]

[0134]

[0135] In the formula, It is the start / stop status flag of MT in period t. It is recorded as 0 when MT is stopped, and 1 otherwise. and They are the upper and lower limits of MT’s power generation respectively; and They are the upper and lower limits of MT climbing rate respectively;

[0136] Gas boiler is a kind of equipment that uses natural gas as fuel to provide heat. It has superior performance and its working efficiency can exceed 90%. Gas boiler (GB) model:

[0137]

[0138]

[0139] In the formula, is the output thermal power of GB at time t; is the natural gas input by GB at time t; η GB is the heat generation efficiency of GB; is the maximum output power of GB, is the minimum output power of GB;

[0140] Recovery Heating Boiler refers to the use of the residual heat generated by the micro gas turbine and gas boiler to generate heat. Recovery Heating Boiler (RHB) Model:

[0141]

[0142]

[0143] In the formula, is the output thermal power of RHB at moment t; is the waste heat recovery efficiency of MT; is the waste heat recovery efficiency of GB; C RHB is the heating coefficient of RHB; is the maximum RHB output power, is the minimum output power of RHB;

[0144] Electric-driven refrigeration equipment is a critical cooling component in the integrated energy system. Electric Refrigeration / Heat Engine (EC) Model:

[0145]

[0146]

[0147] In the formula is the EC output power at time t; is the input power of EC at time t; COP EC is the transfer coefficient; and are the minimum and maximum values ​​of EC output power respectively;

[0148] Energy storage equipment has various forms of energy storage, mainly including electricity storage, heat storage, gas storage, and cold storage. It is a key device to achieve the mutual complementation of various energy sources in the integrated energy system. Energy storage equipment (EES) model:

[0149] The mathematical model of the energy storage battery is:

[0150]

[0151] The constraints to ensure the safe state of the energy storage battery are:

[0152]

[0153] In the formula, are the energy storage capacity of the energy storage battery at time t and time t-1 respectively; e is the self-damage rate of the energy storage device; They are respectively the charging and discharging power range of the energy storage battery at time t; are the charging and discharging efficiencies of the energy storage battery at time point t respectively; are the charging and discharging states, which are 0-1 variables; Δt is the charging and discharging time, which is 1h; are the maximum storage capacity and minimum reserved capacity of the energy storage battery respectively; They are the maximum power input and output capabilities of the energy storage battery respectively; T is a cycle (24h), that is, the charge before and after a cycle remains consistent.

[0154] S102: Calculate the complementary characteristics between different energy sources;

[0155] In S102, the complementarity of the two different types of energy is:

[0156] {E1, E2; A};

[0157] In the formula, E1 and E2 represent two different types of energy; A represents the performance index;

[0158] If the two energy sources are not complementary, the power generation of the integrated energy system is the same as that of the two energy sources. If the two energy sources are complementary, the power generation of the integrated energy system is different from that of the two energy sources. By comparing the power generation under these two situations, we can know the complementarity between the two energy sources. By observing the changing trend of f, we can evaluate the mutual complementarity of two different types of energy in specific performance indicators. The calculation formula f is:

[0159]

[0160] In the formula, f is the degree of association, P f Represents the total output of the two energy sources, P E1 , P E2 Indicates the output of the two energy sources respectively;

[0161] Based on the comparison of the complementarity of two energy sources on a certain performance indicator, it is extended to the mutual complementarity of multiple energy sources on a certain performance parameter:

[0162]

[0163] In the formula It indicates the correlation degree between the i-th energy source and the j-th energy source under x performance indicators.

[0164] S103: Divide the operation model and grid load in S101 into three parts: commercial area, industrial area and residential area, and establish a multi-energy network energy sharing and mutual assistance system integrating the operation model in S101.

[0165] The energy sharing and mutual assistance system architecture of a multi-energy network containing integrated energy is as follows Figure 2The system integrates models of various energy forms such as electricity, heat, natural gas and their supporting equipment, and uses cutting-edge energy conversion, storage and distribution technologies, as well as intelligent energy management systems, to achieve efficient collaboration and energy complementarity between energy suppliers, power parks and operators.

[0166] Energy sharing and mutual assistance means that when multiple entities work together, the entity with insufficient energy can be compensated through the comprehensive energy system of other entities. That is, the entity with idle electricity transfers the right to use it to the demander, and the latter creates economic value and pays compensation. The key lies in the existence of "idle electricity".

[0167] Considering energy sharing and mutual assistance, the cooperative sharing game model architecture of the integrated energy multi-energy network is as follows: Figure 3 As shown. Each park has an independent multi-energy network system to achieve autonomous optimization operation within the park. The distribution operator is responsible for the coordinated optimization between parks and the interactive optimization between the park and the distribution network. When the integrated energy system within the park has excess electricity, it can sell electricity to the distribution operator to obtain revenue. When the integrated energy system within the park is insufficient, it can purchase electricity from the distribution operator to create economic benefits.

[0168] S2: Establish the economically optimal objective function for the multi-energy network and multi-energy flow model; the specific steps of S2 are:

[0169] S201: Construct a function with the goal of economic optimization;

[0170] In S201, under the condition that all devices in the system are in stable operation, the total cost is minimized as the optimization goal to maximize the economic benefits of the system. The objective function is:

[0171] minC=C1+C2+C3+C4+C5;

[0172] In the formula, C represents the total system operating expenses, C1 represents the electricity purchase cost, C2 represents the natural gas purchase cost, C3 represents the operation and maintenance cost, C4 represents the transmission pipeline configuration cost, and C5 represents the interactive benefits with the distribution network.

[0173]

[0174] In the formula, and represents the gas purchase price and electricity purchase power of the park in the representative period y under scenario s during period t;

[0175]

[0176]

[0177] In the formula, and It represents the calorific value cost of gas consumption and the output power of gas turbine and gas boiler in the park in the representative period y under scenario s during period t;

[0178]

[0179] In the formula, and They are the operation and maintenance factors and power output corresponding to the equipment respectively;

[0180]

[0181] In the formula, T is the total number of scheduling periods throughout the day; is the thermal energy purchase power of the subject in the representative period y under scenario s during period t; p , G , B are the corresponding energy transfer coefficients respectively;

[0182]

[0183] Where: is the power sold by the park to the distribution network in time period t; The power purchased from the power distribution grid by the park in time period t; are the corresponding electricity selling price and electricity purchasing cost respectively.

[0184] S202: Construct constraints to ensure the normal operation of the multi-energy network energy sharing and mutual assistance system.

[0185] In S202, the constraints include:

[0186] Electrical power balance:

[0187]

[0188] Thermal power balance:

[0189]

[0190] Considering that each park has an independent and complete integrated energy system, in order to ensure continuous energy supply to the park in an adjustable scenario, the power balance constraints must be met:

[0191]

[0192] In the formula, Indicates the output of the corresponding energy equipment in the park, The output limit of the corresponding energy equipment in the park;

[0193] The power constraint for interaction with the distribution network is:

[0194]

[0195]

[0196] In the formula, To limit the power of buying and selling electricity to the distribution network, The maximum power limit for buying and selling electricity to the distribution network.

[0197] S3: Use the multi-energy network cooperative sharing game model based on the ADMM algorithm to solve the objective function; the specific process of S3 is:

[0198] The traditional Nash bargaining method will make the subject less motivated. For the overall alliance, it is necessary to optimize the fairness of benefit distribution according to the contribution of different subjects and improve the overall cooperation enthusiasm. The ADMM algorithm mainly deals with the following forms of convex optimization problems:

[0199] minx,f(x);

[0200]

[0201] In the formula, x is the optimization variable, f(x) is a convex function, A and c are known coefficient matrices and vectors;

[0202] Subsequently, the Lagrange multiplier λ is used to separate the electricity transaction prices in the commercial area, industrial area, and residential area:

[0203]

[0204] In the formula, The prices that commercial areas expect to buy electricity from industrial areas and the prices that industrial areas expect to buy electricity from commercial areas are respectively; The prices that commercial areas expect to buy electricity from residential areas and the prices that residential areas expect to buy electricity from commercial areas are respectively; The prices that industrial areas expect to buy electricity from residential areas and residential areas expect to buy electricity from industrial areas respectively;

[0205] Finally, the augmented Lagrangian function is constructed based on the expectations of multiple agents and the constraints, and the optimal total cost of each agent is obtained according to the ADMM principle.

[0206] Therefore, the present invention adopts the above-mentioned structure of the energy sharing and mutual assistance optimization strategy of the comprehensive energy multi-energy network based on cooperative game, and realizes efficient coordination and operation between different comprehensive energy systems by constructing a multi-energy network multi-energy flow model that takes into account the multi-energy complementary characteristics, so as to achieve energy supply and demand balance and efficient utilization of overflow energy, reduce energy consumption, and improve energy utilization efficiency. At the same time, in the process of coordinated operation of each system, a multi-energy network optimization model that takes into account cooperative sharing game is constructed and solved to solve the problem of multi-subject interest distribution. Under the premise of balancing the interests of each park, the lowest total cost is achieved, and finally the efficient integration and utilization of multiple energy sources is achieved, and the overall economic benefits of the park are maximized.

[0207] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. An energy sharing and mutual assistance optimization strategy for a comprehensive energy multi-energy network based on cooperative game, characterized by: The following steps are involved: S1: Establish a multi-energy network and multi-energy flow model to calculate the multi-energy complementary characteristics of three parks including commercial area, industrial area and residential area; S2: Establish the economically optimal objective function for the multi-energy network and multi-energy flow model; S3: Use the multi-energy network cooperative sharing game model based on the ADMM algorithm to solve the objective function.

2. The energy sharing and mutual assistance optimization strategy of the comprehensive energy multi-energy network based on cooperative game according to claim 1 is characterized by: The specific steps of S1 are: S101: Establish an operation model of multi-energy network energy production equipment, conversion equipment, and storage equipment; S102: Calculate the complementary characteristics between different energy sources; S103: Divide the operation model and grid load in S101 into three parts: commercial area, industrial area and residential area, and establish a multi-energy network energy sharing and mutual assistance system integrating the operation model in S101.

3. The energy sharing and mutual assistance optimization strategy of the comprehensive energy multi-energy network based on cooperative game according to claim 2 is characterized by: The operation model established in S101 specifically includes: Photovoltaic generator model: In the formula, f is the basic derating factor, which is 0.9; k is the coefficient of temperature on power, which is -0.47% / ℃; Indicates the upper limit of photovoltaic output power; Wind turbine model: Where P wt,rate is the rated output power, v r is the rated wind speed, v is the real-time wind speed, v ct is the wind speed at the start of power generation, v c0 To stop the wind speed for power generation, is the upper limit of the rated power of the fan, P wt (v) is the output power of the wind turbine. For wind turbines of the same batch and model, at a certain moment, the power output of the wind turbine generator is: P wt (v)=NP wt (v); Where N is the number of wind power generation devices in the wind turbine generator set; Microturbine Model: In the formula, is the output power of the micro gas turbine at time t; is the waste heat of the micro gas turbine at time t; η MT , η l are the power generation efficiency and heat dissipation loss coefficient of the micro gas turbine respectively; the power generation efficiency η of the micro gas turbine MT for: The power generation output capacity and ramp rate limit of the micro-turbine MT are constructed as follows: In the formula, It is the start / stop status flag of MT in period t. It is recorded as 0 when MT is stopped, and 1 otherwise. and They are the upper and lower limits of MT’s power generation respectively; and They are the upper and lower limits of MT climbing rate respectively; Gas boiler GB model: In the formula, is the output thermal power of GB at time t; is the natural gas input by GB at time t; η GB is the heat generation efficiency of GB; is the maximum output power of GB, is the minimum output power of GB; Recovery Heating Boiler RHB Model: In the formula, is the output thermal power of RHB at moment t; is the waste heat recovery efficiency of MT; is the waste heat recovery efficiency of GB; C RHB is the heating coefficient of RHB; is the maximum RHB output power, is the minimum output power of RHB; Electric Refrigeration / Heat Engine EC Model: In the formula is the EC output power at time t; is the input power of EC at time t; COP EC is the transfer coefficient; and are the minimum and maximum values ​​of EC output power respectively; Energy storage equipment EES model: The mathematical model of the energy storage battery is: The constraints to ensure the safe state of the energy storage battery are: In the formula, are the energy storage capacity of the energy storage battery at time t and time t-1 respectively; e is the self-damage rate of the energy storage device; They are respectively the charging and discharging power range of the energy storage battery at time t; are the charging and discharging efficiencies of the energy storage battery at time point t respectively; are the charging and discharging states, which are 0-1 variables; Δt is the charging and discharging time, which is 1h; are the maximum storage capacity and minimum reserved capacity of the energy storage battery respectively; They are the maximum power input and output capabilities of the energy storage battery respectively; T is a cycle of 24h.

4. The energy sharing and mutual assistance optimization strategy of the comprehensive energy multi-energy network based on cooperative game according to claim 2 is characterized by: In S102, the complementarity of the two different types of energy is: {E1, E2; A}; In the formula, E1 and E2 represent two different types of energy; A represents the performance index; observing the changing trend of f, the calculation formula for evaluating the mutual complementation ability of two different types of energy in specific performance indicators is: In the formula, f is the degree of association, P f Represents the total output of the two energy sources, P E1 , P E2 Indicates the output of the two energy sources respectively; Based on the comparison of the complementarity of two energy sources on a certain performance indicator, it is extended to the mutual complementarity of multiple energy sources on a certain performance parameter: In the formula It indicates the correlation degree between the i-th energy source and the j-th energy source under x performance indicators.

5. The energy sharing and mutual assistance optimization strategy of the comprehensive energy multi-energy network based on cooperative game according to claim 1 is characterized by: The specific steps of S2 are: S201: Construct a function with the goal of economic optimization; S202: Construct constraints to ensure the normal operation of the multi-energy network energy sharing and mutual assistance system.

6. The energy sharing and mutual assistance optimization strategy of the comprehensive energy multi-energy network based on cooperative game according to claim 5 is characterized by: In S201, the objective function is: minC=C1+C2+C3+C4+C5; In the formula, C represents the total system operating expenses, C1 represents the electricity purchase cost, C2 represents the natural gas purchase cost, C3 represents the operation and maintenance cost, C4 represents the transmission pipeline configuration cost, and C5 represents the interactive benefits with the distribution network; in In the formula, and represents the gas purchase price and electricity purchase power of the park in the representative period y under scenario s during period t; In the formula, and It represents the calorific value cost of gas consumption and the output power of gas turbine and gas boiler in the park in the representative period y under scenario s during period t; In the formula, and They are the operation and maintenance factors and power output corresponding to the equipment respectively; In the formula, T is the total number of scheduling periods throughout the day; is the thermal energy purchase power of the subject in the representative period y under scenario s during period t; p , G , B are the corresponding energy transfer coefficients respectively; Where: is the power sold by the park to the distribution network in time period t; The power purchased from the power distribution grid by the park in time period t; are the corresponding electricity selling price and electricity purchasing cost respectively.

7. The energy sharing and mutual assistance optimization strategy of the comprehensive energy multi-energy network based on cooperative game according to claim 5 is characterized by: In S202, the constraints include: Electrical power balance: Thermal power balance: The power balance constraint to ensure continuous energy supply is: In the formula, Indicates the output of the corresponding energy equipment in the park, The output limit of the corresponding energy equipment in the park; The power constraint for interaction with the distribution network is: In the formula, To limit the power of buying and selling electricity to the distribution network, The maximum power limit for buying and selling electricity to the distribution network.

8. The energy sharing and mutual assistance optimization strategy of the comprehensive energy multi-energy network based on cooperative game according to claim 1 is characterized by: The specific process of S3 is: Use the ADMM algorithm to solve convex optimization problems: minx,f(x); stAx = c; In the formula, x is the optimization variable, f(x) is a convex function, A and c are known coefficient matrices and vectors; The Lagrange multiplier λ is used to separate the electricity transaction prices in the commercial area, industrial area, and residential area: In the formula, The prices that commercial areas expect to buy electricity from industrial areas and the prices that industrial areas expect to buy electricity from commercial areas are respectively; The prices that commercial areas expect to buy electricity from residential areas and the prices that residential areas expect to buy electricity from commercial areas are respectively; The prices that industrial areas expect to buy electricity from residential areas and residential areas expect to buy electricity from industrial areas respectively; Then, the augmented Lagrangian function is constructed based on the expectations of multiple agents and the constraints, and the optimal total cost of each agent is obtained according to the ADMM principle.

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