An interactive game scheduling method for park integrated energy system group and power grid

Abstract

The invention discloses an interactive game dispatching method for a park integrated energy system group and a power grid, which belongs to the field of integrated energy system operation and control technology, and is characterized by comprising the following steps: ① establishing output models and cost models of conventional generator sets, distributed power sources, energy storage and other equipment; ② establishing a collaborative optimization control framework for the park integrated energy system group and the power grid; ③ establishing a game structure for the power grid and the park integrated energy system group; ④ setting a threshold to determine whether to conduct an interactive game; ⑤ establishing an interactive game model for the park integrated energy system group and the power grid based on the master-slave game; ⑥ establishing an interactive game dispatching Matlab platform for the park integrated energy system group and the power grid to solve the interactive process; ⑦ conducting simulation analysis on the effectiveness of the interactive game dispatching strategy for the hierarchically coordinated park integrated energy system group and the power grid, and verifying that the interactive game dispatching strategy for the hierarchically coordinated park integrated energy system group and the power grid can realize the stable and economic operation of the park integrated energy system group and the power grid. The interactive game dispatching method adopted by the present invention can effectively and reliably conduct the collaborative optimization operation of the park integrated energy system group and the power grid, and provide a technical basis and a practical method for the stable operation of the park integrated energy system group and the power grid.

Description

Technical Field

[0001] The present invention relates to an interactive game scheduling method for a park integrated energy system group and a power grid, and in particular to an interactive game scheduling method for a park integrated energy system group and a power grid based on hierarchical collaborative control and master-slave game, belonging to the technical field of integrated energy system operation and control. Background Art

[0002] The large-scale grid connection of distributed power sources has caused the original single-end power supply radial network to evolve into a complex multi-end power supply network. The power flow direction of the distribution network changes randomly with the fluctuation of distributed power sources and load power, which greatly increases the complexity of line operation control and relay protection. At the same time, the output of renewable distributed power sources has strong randomness and volatility, which will destroy the power balance of the power grid, thereby affecting the voltage and frequency stability in the system. At present, the integrated energy system group is an effective way to solve the high penetration of distributed power sources. In the future, there will be a large number of them in the distribution network, and integrate the resources in the integrated energy system to interact with the power grid. The rapid development of the integrated energy system requires further research on the coordinated operation between the power grid and the integrated energy system, which has become an urgent problem to be solved.

[0003] At present, the research on the park integrated energy system group and the power grid at home and abroad mainly focuses on the "source-grid-load" interactive operation mechanism, the distribution network collaborative optimization technology of high-penetration distributed power sources, the distribution network collaborative control technology based on multi-agents, the bidding mechanism and game method of multiple subjects of the distribution network, etc., but there is relatively little research on the collaborative optimization scheduling of the integrated energy system group and the power grid.

[0004] Some experts have established an optimized scheduling model for multi-park integrated energy systems that takes into account power interaction and coordinated output between different parks, and takes into account power interaction between parks and between parks and distribution networks. However, the above research roughly replaces the impact of the power grid with the interactive power between the park and the distribution network and incorporates it into the minimum operating cost objective function. It is a unified scheduling method, and the coordinated interaction between the power grid and MCIES is not obvious.

[0005] There are currently three issues to be further explored: ① The optimal dispatching of MCIES rarely considers the impact of multi-energy synergy interaction between parks on the optimal operation of multiple parks and the impact of the distribution network on MCIES; ② The multiple parks and the power grid are modeled as different stakeholders, but when solving, the economic optimization of the active distribution network is firstly taken into account, and then the "secondary coordination" of the multi-park integrated energy system is optimal, which cannot achieve the parallel solution of multiple microgrids and power grids. ③ The stakeholders considered in the multi-agent decentralized coordinated dispatching of MCIES are not comprehensive, and the problem of interest distribution between the power grid and the park is not considered.

[0006] The purpose of the present invention is to solve the above-mentioned problems existing in the prior art, and proposes an interactive game scheduling method for a park integrated energy system group and a power grid. The interactive game operation strategy between the power grid and the integrated energy system group has a certain complexity, which is manifested in that the established collaborative operation strategy needs to meet the needs of different stakeholders and at the same time make the overall operation state of the system reach the optimal state. Summary of the invention

[0007] The purpose of the present invention is to solve the above problems existing in the prior art, and to provide an interactive game scheduling method for the park integrated energy system group and the power grid. The coordinated control method adopted by the present invention can more effectively and reliably coordinate the control between the power grid and the integrated energy system group, and provide a technical basis and practical method for the coordinated control of the integrated energy system.

[0008] The basic idea of ​​the interactive game scheduling method for the park integrated energy system group and the power grid proposed in this paper is: for the two different stakeholders, the park integrated energy system group and the power grid, build an upper-level centralized regional coordination and lower-level distributed regional coordination framework, establish an interactive game model, and determine the optimal strategy set of each game participant through the master-slave game theory to achieve economically stable operation of the power grid and the park integrated energy system group.

[0009] The technical solution provided by the present invention is: in the power grid and the park integrated energy system group system, by building the upper centralized regional coordination and the lower distributed regional coordination frame, an interactive game model is established, and the power grid formulates the unit processing plan according to its own benefits and sends it to each park through the master-slave game theory; each park selects the electric and thermal load model and benefit function in combination with its own production plan, and reports the amount of load that can be shifted, reduced and changed to the power grid side on the basis of maximizing its own benefits. After the power grid side summarizes the situation of each household, it re-formulates the power generation unit output plan according to its own benefits and sends it to the user. The user continues to optimize his own benefit function and interacts with the power grid again until all optimization object strategy sets no longer change. At this time, the strategy set of each optimization object is the strategy set of each participant under the Nash equilibrium solution. The economically stable operation of the power grid and the park integrated energy system group is realized.

[0010] Its characteristics include the following steps:

[0011] Step 1) Establish output models and cost models for conventional generator sets, distributed power sources, energy storage and other equipment;

[0012] Step 2) Establish a collaborative optimization control framework between the park's integrated energy system group and the power grid;

[0013] (1) Establish a hierarchical decomposition optimization model to achieve coordinated control of the power grid and the park's integrated energy system group: the upper layer is the regional coordinated control of the power grid and the park operator, and the lower layer is the local coordinated control of the park's integrated energy system group;

[0014] (2) The grid-side model uses the electricity exchange costs between the grid and the park and the power generation costs of conventional units on the grid side as the profit function to determine the output of the park group; the park integrated energy system group model uses the operating cost as the optimized profit function to determine the output of each distributed energy source and other equipment in each park.

[0015] Step 3) Establishing a group game structure for the power grid and the park's integrated energy system;

[0016] (1) Actual game participants: power grid and park integrated energy system group;

[0017] (2) Virtual game participants: operating income of the power grid and the park’s integrated energy system group.

[0018] (3) Grid strategy set: the electricity interaction costs between the grid and the park's integrated energy system group, and the total production cost of the grid-side generator sets.

[0019] (4) Park integrated energy system group strategy set: the energy purchase cost of the park integrated energy system group, the cost of interaction between the park integrated energy system group and the power grid, and the operation and maintenance cost of the integrated energy system group.

[0020] Step 4) Setting a threshold to determine whether to conduct interactive gaming;

[0021] Step 5) Establishing a game model of the park integrated energy system group and the power grid interaction based on the master-slave game;

[0022] (1) Determine the game decision variables;

[0023] (2) Determine the profit function;

[0024] (3) The power grid formulates a unit processing plan based on its own benefits and issues it to each park. Each park selects the electricity and heat load model and benefit function based on its own production plan, and reports to the power grid the amount of load that can be shifted, reduced, and changed while maximizing its own benefits.

[0025] (4) After the grid summarizes the situation of each household, it re-formulates the output plan of the generator set according to its own benefits and sends it to the user. The user continues to optimize his own benefit function and interacts with the grid again;

[0026] (5) Repeat steps 3 and 4 until the strategy sets of all optimization objects no longer change. At this time, the strategy sets of each optimization object are the strategy sets of each participant under the Nash equilibrium solution.

[0027] Step 6) Establishing the interactive game dispatching Matlab platform between the park integrated energy system group and the power grid to solve the interactive process;

[0028] (1) Input initial data and set parameters, including typical daily thermal power load curves of each park, park electricity prices, unit operating parameters, etc.;

[0029] (2) Initialize population a, which includes information such as cooling, heating and electricity load demand and interactive response volume reported by each park;

[0030] (3) The grid dispatching center sends the interactive response volume and unit output plan to the park's integrated energy system group, and then calls the sub-process to optimize the park's benefits;

[0031] (4) The park's integrated energy system group reports the optimized strategy to the power grid dispatching center, and the power grid side calculates its own benefit B1;

[0032] (5) Perform crossover and mutation to form a new subpopulation b;

[0033] (6) The lower-level algorithm is called, and the park cluster optimizes its own benefits and reports the optimized strategy to the power grid dispatching center. The power grid side calculates its own benefit B2;

[0034] (7) Lower-level algorithm: Use nonlinear programming to solve the benefits of the park group and report the optimized results to the power grid dispatching center. When all parks participate in the optimization solution, the process ends.

[0035] (8) If B2>B1, let a=b, B1=B2, and then jump to step (5). Otherwise, determine whether the iteration end requirement is met. If so, the interactive simulation ends. Otherwise, jump to step (5).

[0036] Step 7) Simulate and analyze the effectiveness of the interactive game dispatching strategy between the hierarchically coordinated park comprehensive energy system group and the power grid to verify that the interactive game dispatching strategy between the hierarchically coordinated park comprehensive energy system group and the power grid can achieve stable and economic operation of the park comprehensive energy system group and the power grid.

[0037] The park's integrated energy system group and the power grid are collaboratively optimized and controlled through the interaction of electric energy.

[0038] A hierarchical collaborative optimization control model and an interactive game model are established to realize the optimal dispatching strategy for the park’s integrated energy system group and power grid.

[0039] In the hierarchical collaborative optimization control model, the regional dispatching layer power grid conducts joint dispatch with other power generation companies in the power grid based on the purchase and sale prices, "output" upper and lower limits and other information provided by each park, and determines the power generation plan with the goal of maximizing the benefits of the power grid company. Each park also needs to conduct "secondary coordination" based on the power generation plan, distributed power output and its own load forecast data with the goal of minimizing operating costs.

[0040] Regional dispatch side profit function:

[0041]

[0042] Where: F PG is the total production cost on the regional side; μ i (t) is the time-sharing transaction price between the power grid and the i-th integrated energy system; P G，i (t) is the electric power transmitted between the power grid and the i-th integrated energy system; when its value is negative (positive), it means that the power grid sells (purchases) electricity from the integrated energy system, and n and m are the number of conventional generators in the integrated energy system and the power grid side, respectively; P G，j (t) is the output of the jth conventional unit on the grid side; a j , b j and c j is the corresponding cost coefficient.

[0043] Cost-benefit function of local scheduling side:

[0044]

[0045] Where: F LI is the total production cost on the local side; p gas is the natural gas price; P MT，i (t) is the gas turbine output of the i-th integrated energy system; η MT，i is the gas turbine power generation efficiency of the i-th integrated energy system; H gas is the calorific value of natural gas; N GB，i (t) is the gas consumption of the gas boiler in the i-th integrated energy system; v i，x is the operation and maintenance cost per unit time of equipment x in the i-th park; is the output of equipment x in the ith park; X is the type of equipment in each park.

[0046] The interaction process between the power grid and the integrated energy system group of the park can be one time or a limited number of times until the Nash game equilibrium solution is obtained, that is, the power grid and each park cannot increase their profits by changing their own strategies alone.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] 1. The interactive game dispatching method of the park's integrated energy system group and the power grid can take into account the interests of different parks. The parks can achieve interest distribution through interactive games, which is more in line with the actual situation. It effectively realizes the decentralized coordinated dispatching of the power of the distribution network-park interconnection line and the interactive power between parks, taking into account the economic and safety of operation and the interests of different subjects, so that each subject can achieve the optimal operation of coordinated economy through the two-stage interest game of regional dispatch and local dispatch.

[0049] 2. This method is easy to implement. This method is established on the basis of optimizing the dispatching within the integrated energy system group. By adding the electric energy interaction link between the integrated energy system group and the power grid, the operation dispatching of the integrated energy system does not deviate from the real environment and is more in line with the actual situation. It is easy to implement from the control point of view; at the same time, each prediction function has a ready-made algorithm or software, and the control strategy is also easy to implement.

[0050] 3. This method is convenient for commercial development. With the increasing application of integrated energy systems, there is bound to be a great demand for the development of coordinated optimization control strategies between the system and the power grid. The present invention has good commercial development prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is the overall flow chart of the interactive game dispatching method between the park's integrated energy system group and the power grid;

[0052] Figure 2 It is a framework diagram of the collaborative game between the power grid and the park's integrated energy system group;

[0053] Figure 3 It is a schematic diagram of the coordinated operation structure of the park's integrated energy system group and the power grid;

[0054] Figure 4-5 It is the result of optimization of the park’s comprehensive energy system group. DETAILED DESCRIPTION

[0055] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and simulation experiments.

[0056] like Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 As shown, the present invention comprises the following steps:

[0057] Step 1) Establish output models and cost models for conventional generator sets, distributed power sources, energy storage and other equipment;

[0058] Step 2) Establish a collaborative optimization control framework between the park's integrated energy system group and the power grid;

[0059] (1) Establish a hierarchical decomposition optimization model to achieve coordinated control of the power grid and the park's integrated energy system group: the upper layer is the regional coordinated control of the power grid and the park operator, and the lower layer is the local coordinated control of the park's integrated energy system group;

[0060] (2) The grid-side model uses the electricity exchange costs between the grid and the park and the power generation costs of conventional units on the grid side as the profit function to determine the output of the park group; the park integrated energy system group model uses the operating cost as the optimized profit function to determine the output of each distributed energy source and other equipment in each park.

[0061] Step 3) Establishing a group game structure for the power grid and the park's integrated energy system;

[0062] (1) Actual game participants: power grid and park integrated energy system group;

[0063] (2) Virtual game participants: operating income of the power grid and the park’s integrated energy system group.

[0064] (3) Grid strategy set: the electricity interaction costs between the grid and the park's integrated energy system group, and the total production cost of the grid-side generator sets.

[0065] (4) Park integrated energy system group strategy set: the energy purchase cost of the park integrated energy system group, the cost of interaction between the park integrated energy system group and the power grid, and the operation and maintenance cost of the integrated energy system group.

[0066] Step 4) Setting a threshold to determine whether to conduct interactive gaming;

[0067] Step 5) Establishing a game model of the park integrated energy system group and the power grid interaction based on the master-slave game;

[0068] (1) Determine the game decision variables;

[0069] (2) Determine the profit function;

[0070] (3) The power grid formulates a unit processing plan based on its own benefits and issues it to each park. Each park selects the electricity and heat load model and benefit function based on its own production plan, and reports to the power grid the amount of load that can be shifted, reduced, and changed while maximizing its own benefits.

[0071] (4) After the grid summarizes the situation of each household, it re-formulates the output plan of the generator set according to its own benefits and sends it to the user. The user continues to optimize his own benefit function and interacts with the grid again;

[0072] (5) Repeat steps 3 and 4 until the strategy sets of all optimization objects no longer change. At this time, the strategy sets of each optimization object are the strategy sets of each participant under the Nash equilibrium solution.

[0073] Step 6) Establishing the interactive game dispatching Matlab platform between the park integrated energy system group and the power grid to solve the interactive process;

[0074] (1) Input initial data and set parameters, including typical daily thermal power load curves of each park, park electricity prices, unit operating parameters, etc.;

[0075] (2) Initialize population a, which includes information such as cooling, heating and electricity load demand and interactive response volume reported by each park;

[0076] (3) The grid dispatching center sends the interactive response volume and unit output plan to the park's integrated energy system group, and then calls the sub-process to optimize the park's benefits;

[0077] (4) The park's integrated energy system group reports the optimized strategy to the power grid dispatching center, and the power grid side calculates its own benefit B1;

[0078] (5) Perform crossover and mutation to form a new subpopulation b;

[0079] (6) The lower-level algorithm is called, and the park cluster optimizes its own benefits and reports the optimized strategy to the power grid dispatching center. The power grid side calculates its own benefit B2;

[0080] (7) Lower-level algorithm: Use nonlinear programming to solve the benefits of the park group and report the optimized results to the power grid dispatching center. When all parks participate in the optimization solution, the process ends.

[0081] (8) If B2>B1, let a=b, B1=B2, and then jump to step (5). Otherwise, determine whether the iteration end requirement is met. If so, the interactive simulation ends. Otherwise, jump to step (5).

[0082] Step 7) Simulate and analyze the effectiveness of the interactive game dispatching strategy between the hierarchically coordinated park comprehensive energy system group and the power grid to verify that the interactive game dispatching strategy between the hierarchically coordinated park comprehensive energy system group and the power grid can achieve stable and economic operation of the park comprehensive energy system group and the power grid.

[0083] The park's integrated energy system group and the power grid are collaboratively optimized and controlled through the interaction of electric energy.

[0084] A hierarchical collaborative optimization control model and an interactive game model are established to realize the optimal dispatching strategy for the park’s integrated energy system group and power grid.

[0085] In the hierarchical collaborative optimization control model, the regional dispatching layer power grid conducts joint dispatch with other power generation companies in the power grid based on the purchase and sale prices, "output" upper and lower limits and other information provided by each park, and determines the power generation plan with the goal of maximizing the benefits of the power grid company. Each park also needs to conduct "secondary coordination" based on the power generation plan, distributed power output and its own load forecast data with the goal of minimizing operating costs.

[0086] Regional dispatch side profit function:

[0087]

[0088] Where: F PG is the total production cost on the regional side; μ i (t) is the time-sharing transaction price between the power grid and the i-th integrated energy system; P G，i (t) is the electric power transmitted between the power grid and the i-th integrated energy system; when its value is negative (positive), it means that the power grid sells (purchases) electricity from the integrated energy system, and n and m are the number of conventional generators in the integrated energy system and the power grid side, respectively; P G，j (t) is the output of the jth conventional unit on the grid side; a j , b j and c j is the corresponding cost coefficient.

[0089] Cost-benefit function of local scheduling side:

[0090]

[0091] Where: F LI is the total production cost on the local side; p gas is the natural gas price; P MT，i (t) is the gas turbine output of the i-th integrated energy system; η MT，i is the gas turbine power generation efficiency of the i-th integrated energy system; H gas is the calorific value of natural gas; N GB，i (t) is the gas consumption of the gas boiler in the i-th integrated energy system; ν i，x is the operation and maintenance cost per unit time of equipment x in the i-th park; is the output of equipment x in the ith park; X is the type of equipment in each park.

[0092] The interaction process between the power grid and the integrated energy system group of the park can be one time or a limited number of times until the Nash game equilibrium solution is obtained, that is, the power grid and each park cannot increase their profits by changing their own strategies alone.

[0093] Figure 1It is the overall flow chart, which is consistent with the above calculation steps. It is worth mentioning that this method adds the master-slave game idea to the basic framework of hierarchical collaborative control of power grid and park integrated energy system group, establishes an interactive game model, and obtains the optimal strategy set of participants under Nash equilibrium, that is, the optimal scheduling strategy. This is the essential difference from other methods.

[0094] Figure 2 It is a collaborative game framework diagram between the power grid and the park integrated energy system group. The power grid dispatching center formulates a power generation plan based on the typical information of the integrated energy system and the typical information of the power grid side, and conducts real-time monitoring through the dynamic SCADA system. When |ΔP IES |(absolute value of output change of each park) is greater than δ lim When the threshold in the indicator system is reached, the interactive game scheduling between the power grid and the park integrated energy system group is carried out until the Nash equilibrium is reached and the optimal set of participant strategies is output.

[0095] Figure 3 It is a schematic diagram of the coordinated operation structure of the park's comprehensive energy system group and the power grid. The upper layer is the regional dispatching layer, and the lower layer is the local dispatching layer, which adopts distributed modeling.

[0096] Figure 4 It is the result of optimization of the park’s comprehensive energy system group.

[0097] Assume that a regional power grid has three parks, each equipped with a CCHP system, wind and photovoltaic power generation equipment, and electrical and thermal energy storage. The parameters of each device in the CCHP system are set as follows: Gas turbine power generation efficiency Waste heat recovery efficiency The conversion efficiencies of heat pump and absorption chiller are The electric thermal energy storage capacity is limited to The charging and discharging efficiency of electrothermal energy storage is

[0098] The park loads are electricity, cooling and heat loads, among which the electricity load of Park 1, the cooling load of Park 2 and the heat load of Park 3 are higher than the similar loads of other parks.

[0099] As can be seen from the figure, each park charges the power storage equipment through distributed power sources and the large power grid during the valley period, and provides electricity to the park during the peak period, which can not only reduce the energy cost of the park, but also further absorb the electricity generated by distributed power generation. The CCHP system starts to be used during the normal period, and then the system power output fluctuates with the total power load and distributed power output in the period 10-22. During this period, the output reaches the peak in the period 11-12 and 19. Therefore, the power purchase amount during the peak and normal periods is effectively reduced, thereby achieving the purpose of reducing energy costs. In addition, it can be seen from the power purchase amount of each park in each period that after interactive game optimization, the load demand during the peak period is greatly reduced, and the peak-valley difference of the load demand is reduced, which is conducive to the safe and stable operation of the large power grid.

[0100] During peak and normal periods, the thermal load of the park is basically provided by CCHP and energy storage, while during valley periods, the thermal load is basically provided by electric energy. This is because the electricity prices during peak and normal periods are high. In order to reduce the cost of purchasing electricity, the park chooses to use CCHP to supply electricity to the park and use waste heat to provide thermal energy. When the waste heat is insufficient, gas boilers are used to provide thermal energy. During valley periods, the electricity price is low, and distributed power sources generate excess electricity. The heating method of distributed power generation and power grid purchase and then electric heating is cheaper than the direct heating method of CCHP. In addition, by comparing the optimization results of the three parks, it can be seen that due to the large demand for thermal load in the park, the thermal storage equipment stores more energy through electric-heat conversion during the valley period, so as to provide thermal energy for the park during the evening peak period, thereby reducing the heating cost and promoting the consumption of distributed power generation.

Claims

1. An interactive game dispatching method for a park integrated energy system group and a power grid, including introducing an interactive game optimization mechanism for the park integrated energy system group and the power grid on the basis of a coordinated optimization operation strategy for the park integrated energy system group and the power grid, making full use of the peak-valley characteristics of the load on the power grid side and the park side for energy optimization management, thereby reducing the overall operating cost of the system and the peak-valley difference of the load, and realizing the economical and safe operation of the park integrated energy system group and the power grid; comprising the following steps: Step 1) Establish output models and cost models for conventional generator sets, distributed power sources, energy storage and other equipment; Step 2) Establish a collaborative optimization control framework between the park's integrated energy system group and the power grid; (1) Establish a hierarchical decomposition optimization model to achieve coordinated control of the power grid and the park's integrated energy system group: the upper layer is the regional coordinated control of the power grid and the park operator, and the lower layer is the local coordinated control of the park's integrated energy system group; (2) The grid-side model uses the electricity exchange costs between the grid and the park and the power generation costs of conventional units on the grid as the profit function to determine the output of the park group; the park integrated energy system group model uses the operating cost as the optimized profit function to determine the output of each distributed energy source and other equipment in each park; Step 3) Establishing a group game structure for the power grid and the park's integrated energy system; (1) Actual game participants: power grid and park integrated energy system group; (2) Virtual game participants: operating benefits of the power grid and the park's integrated energy system group; (3) Grid strategy set: the electricity interaction cost between the grid and the park integrated energy system group, and the total production cost of the grid-side generator set; (4) Park integrated energy system group strategy set: the energy purchase cost of the park integrated energy system group, the cost of interaction between the park integrated energy system group and the power grid, and the operation and maintenance cost of the integrated energy system group; Step 4) Setting a threshold to determine whether to conduct interactive gaming; Step 5) Establishing a game model of the park integrated energy system group and the power grid interaction based on the master-slave game; (1) Determine the game decision variables; (2) Determine the profit function; (3) The power grid formulates a unit processing plan based on its own benefits and issues it to each park. Each park selects the electricity and heat load model and benefit function based on its own production plan, and reports to the power grid the amount of load that can be shifted, reduced, and changed while maximizing its own benefits. (4) After the grid summarizes the situation of each household, it re-formulates the output plan of the generator set according to its own benefits and sends it to the user. The user continues to optimize his own benefit function and interacts with the grid again; (5) Repeat steps 3 and 4 until the strategy sets of all optimization objects no longer change. At this time, the strategy sets of each optimization object are the strategy sets of each participant under the Nash equilibrium solution. Step 6) Establishing the interactive game dispatching Matlab platform between the park integrated energy system group and the power grid to solve the interactive process; (1) Input initial data and set parameters, including typical daily thermal power load curves of each park, park electricity prices, and unit operating parameters; (2) Initialize population a, which includes the cooling, heating and electricity load demand and interactive response information reported by each park; (3) The grid dispatching center sends the interactive response volume and unit output plan to the park's integrated energy system group, and then calls the sub-process to optimize the park's benefits; (4) The park's integrated energy system group reports the optimized strategy to the power grid dispatching center, and the power grid side calculates its own benefit B1; (5) Perform crossover and mutation to form a new subpopulation b; (6) The lower-level algorithm is called, and the park cluster optimizes its own benefits and reports the optimized strategy to the power grid dispatching center. The power grid side calculates its own benefit B2; (7) Lower-level algorithm: Use nonlinear programming to solve the benefits of the park group and report the optimized results to the power grid dispatching center. When all parks participate in the optimization solution, the process ends. (8) If B2>B1, let a=b, B1=B2, and then jump to step (5) to determine whether the iteration end requirements are met. If so, the interactive simulation ends, otherwise jump to step (5); Step 7) Simulate and analyze the effectiveness of the interactive game dispatching strategy between the hierarchical coordinated park comprehensive energy system group and the power grid to verify that the interactive game dispatching strategy between the hierarchical coordinated park comprehensive energy system group and the power grid can achieve stable and economic operation of the park comprehensive energy system group and the power grid; The park's integrated energy system group and the power grid conduct coordinated optimization control through the interaction of electric energy; Establish a hierarchical collaborative optimization control model and an interactive game model to achieve the optimal dispatching strategy for the park's integrated energy system group and power grid; In the hierarchical collaborative optimization control model, the regional dispatching layer power grid conducts joint dispatch with other power generation companies in the power grid based on the purchase and sale power prices and "output" upper and lower limit information provided by each park, and determines the power generation plan with the goal of maximizing the benefits of the power grid company; each park also needs to conduct "secondary coordination" based on the power generation plan, distributed power output and its own load forecast data with the goal of minimizing operating costs; Regional dispatch side profit function: Where: F PG is the total production cost on the regional side; μ i (t) is the time-sharing transaction price between the power grid and the i-th integrated energy system; P G，i (t) is the electric power transmitted between the power grid and the i-th integrated energy system; when its value is negative / positive, it means that the power grid sells / purchases electricity from the integrated energy system, and n and m are the number of conventional generators in the integrated energy system and the power grid side, respectively; P G，j (t) is the output of the jth conventional unit on the grid side; a j , b j and c j is the corresponding cost coefficient; Cost-benefit function of local scheduling side: Where: F LI is the total production cost on the local side; p gas is the natural gas price; P MT，i (t) The gas turbine output of the i-th integrated energy system; η MT，i is the gas turbine power generation efficiency of the i-th integrated energy system; H gas is the calorific value of natural gas; N GB，i (t) is the gas consumption of the gas boiler in the i-th integrated energy system; v i，x is the operation and maintenance cost per unit time of equipment x in the i-th park; is the output of equipment x in the ith park; X is the type of equipment in each park.

2. The interactive game scheduling method for a park integrated energy system group and a power grid according to claim 1 is characterized by: The interaction process between the power grid and the integrated energy system group of the park can be one time or a limited number of times until the Nash game equilibrium solution is obtained, that is, the power grid and each park cannot increase their profits by changing their own strategies alone.

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