New energy power generation system adjusting method

Abstract

The invention discloses a new energy power generation system adjusting method, and belongs to the technical field of new energy power generation, and the method comprises the steps: S1, obtaining the historical operation data of a new energy power generation system, and extracting a benefit feature, a power feature and an energy storage performance feature based on the historical operation data; s2, constructing a hybrid strategy game model based on the benefit characteristics, the power characteristics and the energy storage performance characteristics, and collecting real-time operation data of the new energy power generation system; s3, setting a real-time parameter combination of the hybrid strategy game model based on the real-time operation data, and performing stability analysis on the hybrid strategy game model based on a stability rule and the real-time parameter combination to obtain a stable equilibrium point; s4, operating the hybrid strategy game model based on the stable equilibrium point to obtain a load demand prediction set, and constructing an adjustment strategy based on the load demand prediction set; the problem that in the prior art, the mutual influence relation between the new energy power generation power and the energy storage power station performance is not considered, and consequently the stability of a new energy power generation system is poor is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy power generation, and specifically to a method for adjusting a new energy power generation system. Background Art

[0002] With the development of new energy power generation technology, the proportion of new energy power generation in the power grid is increasing. At the same time, considering that a single type of new energy power generation will cause the stability of the power grid to decline due to its inherent properties. For example, photovoltaic power generation has randomness, volatility and uncertainty, and wind power has the characteristic of reverse peak shaving. Generally, a new energy power generation in the power grid is built into a wind-solar-storage cluster to suppress the impact of new energy power generation on the power grid by means of the spatio-temporal complementarity of wind power and photovoltaic power generation. However, the performance of the energy storage power station in the wind-solar-storage cluster will decline with the increase of charge and discharge times, and wind power and photovoltaic power generation are limited by environmental factors, resulting in continuous changes in the proportion of high-quality power output. Therefore, it is necessary to continuously charge and discharge the energy storage power station to ensure the power quality of the wind-solar-storage cluster, which also leads to the decline of the performance of the energy storage power station and the significant reduction of its service life.

[0003] Chinese Patent, Publication No.: CN114819373A, Publication Date: July 29, 2022, discloses a method for energy storage planning of a shared hybrid energy storage power station based on cooperative game, including: S1, formulating an operation strategy for hybrid energy storage according to the different operation characteristics of batteries and supercapacitors; S2, establishing a two-layer optimal configuration model for the hybrid energy storage power station to maximize the annual income of the hybrid energy storage power station, and constructing an evaluation index for the configuration effect of the hybrid energy storage; S3, establishing a cooperative game model, and based on the Shapley score method, determining a comprehensive distribution strategy considering the configuration effect of the hybrid energy storage; S4, based on the operation strategy of the hybrid energy storage in step S1 and the two-layer optimal configuration model in step S2, obtaining the hybrid energy storage configuration plan and the annual income of the hybrid energy storage power station, and then using the cooperative game model in step S3 to allocate income to the new energy power stations in the alliance; however, this invention does not consider the mutual influence relationship between the new energy power generation power and the performance of the energy storage power station, resulting in poor stability of the new energy power generation system. Summary of the Invention

[0004] The object of the present invention is to address the problem that the prior art does not consider the mutual influence relationship between new energy power generation power and the performance of energy storage power stations, resulting in poor stability of new energy power generation systems. A new energy power generation system regulation method is proposed. A hybrid strategy game model is constructed through efficiency characteristics, power characteristics, and energy storage performance characteristics extracted from the historical operation data of the new energy power generation system. At the same time, real-time parameter combinations of the hybrid strategy game model are set based on real-time operation data, and the stable equilibrium point of the hybrid strategy game model is analyzed based on stability rules. Finally, the hybrid strategy game model is operated based on the real-time parameter combinations and the stable equilibrium point to obtain a load demand prediction set, and a regulation strategy that fits the new energy power generation system can be constructed according to the load demand prediction set, significantly improving the stability of the new energy power generation system.

[0005] In a first aspect, a technical solution provided in an embodiment of the present invention is a new energy power generation system regulation method, including the following steps: S1. Obtain the historical operation data of the new energy power generation system, and extract benefit characteristics, power characteristics, and energy storage performance characteristics based on the historical operation data; S2. Construct a hybrid strategy game model based on the benefit characteristics, power characteristics, and energy storage performance characteristics, and collect the real-time operation data of the new energy power generation system; S3. Set real-time parameter combinations of the hybrid strategy game model based on real-time operation data, and perform stability analysis on the hybrid strategy game model based on stability rules and the real-time parameter combinations to obtain a stable equilibrium point; S4. Operate the hybrid strategy game model based on the stable equilibrium point to obtain a load demand prediction set, and construct a new energy power generation system regulation strategy based on the load demand prediction set.

[0006] In this solution, benefit features, power features, and energy storage performance features are extracted based on the historical operation data of the new energy power generation system to fully explore the mutual influence relationship between the new energy power generation and the energy storage power station. A hybrid strategy game model is constructed according to the mutual influence relationship to simulate the operation state of the new energy power generation system, so as to predict the changes in various data of the new energy power generation system. At the same time, the real-time parameter combination of the hybrid strategy game model is set based on the real-time operation data of the new energy power generation system to make the hybrid strategy game model fit the actual working conditions of the new energy power generation system, improve the accuracy of the hybrid strategy game model, and perform stability analysis on the hybrid strategy game model based on the stability law to find the stable equilibrium point where the new energy power generation and the energy storage power are balanced and operate stably. Finally, the load demand prediction set is obtained by operating the hybrid strategy game model based on the real-time parameter combination and the stable equilibrium point to predict the operation state of the corresponding new energy power generation system, and the adjustment strategy of the corresponding new energy power generation system is constructed based on the load demand prediction set. The new energy power generation system executes the adjustment action in response to the adjustment strategy, significantly improving the stability of the new energy power generation system and effectively delaying the performance loss rate of the corresponding energy storage device, greatly extending the service life of the energy storage device.

[0007] Preferably, in S1, the specific process of extracting the benefit features, power features, and energy storage performance features based on the historical operation data is as follows: Extract the wind power generation revenue and wind power generation cost based on the wind power generation device and historical operation data in the new energy power generation system; Extract the photovoltaic power generation revenue and photovoltaic power generation cost based on the photovoltaic power generation device and historical operation data in the new energy power generation system; Extract the energy storage revenue and energy storage cost based on the energy storage device and historical operation data in the new energy power generation system; Sort out the wind power generation revenue, wind power generation cost, photovoltaic power generation revenue, photovoltaic power generation cost, energy storage revenue, and energy storage cost to obtain the benefit features; extract the power features based on the power data change trend corresponding to the benefit features in the historical operation data; Extract the energy storage performance features based on the energy storage performance data change trend in the energy storage dataset.

[0008] In this solution, based on the wind power generation device, photovoltaic power generation device, and energy storage device in the new energy power generation system, historical operation data can be divided into a wind power data set, a photovoltaic data set, and an energy storage data set. Furthermore, based on the wind power data set, wind power revenue and wind power cost can be extracted; based on the photovoltaic data set, photovoltaic revenue and photovoltaic cost can be extracted; based on the energy storage data set, energy storage revenue and energy storage cost can be extracted. At the same time, since the wind power data set, photovoltaic data set, and energy storage data set all belong to the historical operation data of the new energy power generation system, by combining the topological structure of the new energy power generation system, that is, the wind power generation device, photovoltaic power generation device, and energy storage device, the mutual influence relationship among wind power revenue, wind power cost, photovoltaic revenue, photovoltaic cost, energy storage revenue, and energy storage cost can be obtained. Based on this mutual influence relationship, the power characteristics and energy storage performance characteristics can be corresponding to the benefit characteristics, and the mutual connection among the power characteristics, energy storage performance characteristics, and benefit characteristics can be clarified.

[0009] Preferably, in step S2, the specific process of constructing a hybrid strategy game model based on the benefit characteristics, power characteristics, and energy storage performance characteristics is as follows: S211. Construct a grid-connected revenue payment function based on the benefit characteristics and power characteristics, and construct a service life payment function based on the benefit characteristics and energy storage performance characteristics; S212. Construct a hybrid strategy game matrix based on the grid-connected revenue payment function and the service life payment function; S213. Establish an expected revenue function and an average expected revenue function based on the hybrid strategy game matrix and the selection probability corresponding to the working mode of the new energy power generation system, and construct a hybrid strategy game model based on the revenue function and the average expected revenue function.

[0010] In this solution, the revenue and cost of the new energy power generation system during grid-connected operation and energy storage coordination can be accurately quantified through the grid-connected revenue payment function and the service life payment function. While the hybrid strategy game model simulates the operation state of the new energy power generation system, the maximum economic benefit can be achieved, effectively saving the performance resources of the corresponding energy storage device. Secondly, by introducing the selection probability corresponding to the working mode of the new energy power generation system into the hybrid strategy game model, the hybrid strategy game model can find the optimal balance strategy that conforms to the actual working conditions of the new energy power generation system from multiple dimensions, such as economic benefits, energy storage performance loss, photovoltaic volatility, and wind power reverse peak regulation characteristics.

[0011] Preferably, in step S212, the hybrid strategy game matrix is specifically as follows: In the formula, K represents the hybrid strategy game matrix, x is the probability that the wind power generation device produces low-quality electric energy, y is the probability that the photovoltaic power generation device refuses to coordinate and connect to the grid, z is the probability that the energy storage device operates in a strict life standard consumption mode, CW is the electricity sales revenue for wind power grid connection, C W,CC1 is the high-quality wind power construction cost, C W,CC2 is the basic wind power construction cost, C W,IC is the cost for wind power to seek photovoltaic coordination, C EW is the additional grid connection revenue of wind power, C ESPS,omc is the grid connection cost of energy storage, C ESPS is the charging and discharging revenue of energy storage, C ESPS,LL is the charging cost of energy storage, C ESPS,T is the cost of energy storage life penalty, C ESPS,W,C is the compensation given by wind power to photovoltaic, C ESPS,wdz is the low-quality operation and maintenance cost of wind power, C PV is the energy supply revenue of photovoltaic, C PV,omc is the coordination cost of photovoltaic, C XJ is the negative cost of photovoltaic, C SM is the energy storage life benefit, C LQ is the fine for low quality of wind power.

[0012] Preferably, in the S213, the mixed strategy game model is specifically: In the formula, is the replicator dynamic equation of energy storage, x is the probability of the wind power generation device producing low-quality electric energy, E 11 is the expected revenue of energy storage, is the average expected revenue of energy storage, is the replicator dynamic equation of wind power, y is the probability that the photovoltaic power generation device refuses to coordinate grid connection, E 21 is the expected revenue of wind power, is the average expected revenue of wind power, is the replicator dynamic equation of photovoltaic, z is the probability that the energy storage device operates in a strict life standard consumption mode, E 31 is the expected revenue of photovoltaic, is the average expected revenue of photovoltaic, and t is time.

[0013] Preferably, in the S3, the specific process of setting the real-time parameter combination of the mixed strategy game model based on the real-time operation data is: S311. Determine the parameter types based on the parameter combination of the mixed strategy game model, and extract the data change characteristics and data interaction characteristics corresponding to the parameters based on the parameter types and the real-time operation data; S312. Determine the real-time parameter combination based on the data change characteristics and the data interaction characteristics.

[0014] Preferably, in S3, the specific process of performing stability analysis on the hybrid strategy game model based on the stability law and real-time parameter combination to obtain the stable equilibrium point is as follows: S321. Adjust the hybrid strategy game model based on the real-time parameter combination, and extract the equilibrium point of the adjusted hybrid strategy game model based on the selection probability of the working mode of the new energy power generation system and the preset balanced probability value; S322. Construct a Jacobian matrix based on the equilibrium point, and judge the stability of the equilibrium point based on the real part of the eigenvalue in the Jacobian matrix. If the real parts of all the eigenvalues are negative real parts, it is determined that the corresponding equilibrium point is stable; if at least one of the real parts of the eigenvalues is a positive real part, it is determined that the corresponding equilibrium point is unstable; Synchronously, mark all the equilibrium points determined to be stable as stable equilibrium points.

[0015] In this solution, due to the time-varying nature of the new energy power generation system, the balance conditions of the new energy power generation system in different time periods and different working conditions are somewhat different. Therefore, after adjusting the hybrid strategy game model based on the real-time parameter combination, a Jacobian matrix is established based on the selection probability of the working mode of the new energy power generation system and the preset balanced probability value to find the stable equilibrium point of the hybrid strategy game model, and the equilibrium stable state corresponding to the balance condition of the new energy power generation system of the hybrid strategy game model is found with the help of the stable equilibrium point, effectively improving the robustness of the hybrid strategy game model.

[0016] Preferably, in S322, the Jacobian matrix is specifically as follows: In the formula, J is the Jacobian matrix, J 1 is the first equilibrium point, J 2 is the second equilibrium point, J 3 is the third equilibrium point, J 4 is the fourth equilibrium point, J 5 is the fifth equilibrium point, J 6 is the sixth equilibrium point, J 7 is the seventh equilibrium point, J 8 is the eighth equilibrium point, J 9 is the ninth equilibrium point, is the energy storage replicator dynamic equation, x is the probability that the wind power generation device produces low-quality electric energy, is the wind power replicator dynamic equation, y is the probability that the photovoltaic power generation device refuses to coordinate and connect to the grid, is the photovoltaic replicator dynamic equation, z is the probability that the energy storage device operates in the strict life standard consumption mode.

[0017] Preferably, in step S4, the specific process of obtaining the load demand prediction set based on the stable equilibrium point by operating the mixed strategy game model is as follows: S411. Adjust the selection probability of the working mode of the new energy power generation system corresponding to the mixed strategy game model based on the stable equilibrium point to obtain the real-time mixed strategy; S412. Operate the mixed strategy game model based on the real-time mixed strategy to obtain the load demand prediction data, and draw the load demand prediction graph based on the load demand prediction data; S413. Organize the load demand prediction data and the load demand prediction graph to obtain the load demand prediction set.

[0018] In this solution, adjusting the selection probability of the working mode of the new energy power generation system based on the stable equilibrium point to obtain the real-time mixed strategy can deeply explore the load demand of the new energy power generation system on the premise of meeting the real-time balance condition of the new energy power generation system, and obtain an accurate load demand prediction set.

[0019] Preferably, in step S4, the specific process of constructing the adjustment strategy of the new energy power generation system based on the load demand prediction set is as follows: S421. Determine the load change trend of the new energy power generation system on the time scale based on the load demand prediction set, and determine the adjustable power and the non-adjustable power based on the load change trend; S422. Determine the adjustment device and the device to be adjusted based on the adjustable power, the non-adjustable power and the topology structure of the new energy power generation system, and construct the adjustment strategy of the new energy power generation system based on the adjustment device and the device to be adjusted.

[0020] The present invention has at least the following substantial effects: This application extracts benefit characteristics, power characteristics, and energy storage performance characteristics based on the historical operation data of a new energy power generation system, fully explores the mutual influence relationship between the new energy power generation and the energy storage power station, and constructs a hybrid strategy game model according to the mutual influence relationship to simulate the operation state of the new energy power generation system, so as to predict the changes in various data of the new energy power generation system. At the same time, based on the real-time operation data of the new energy power generation system, a real-time parameter combination of the hybrid strategy game model is set, so that the hybrid strategy game model fits the actual working conditions of the new energy power generation system, improves the accuracy of the hybrid strategy game model, and conducts a stability analysis of the hybrid strategy game model based on the stability law to find the stable equilibrium points where the new energy power generation and the energy storage power are balanced and operate stably under different time periods and different working conditions. Finally, based on the real-time parameter combination and the stable equilibrium points, the hybrid strategy game model is operated to obtain a load demand prediction set, the operation state of the corresponding new energy power generation system is predicted, and a regulation strategy for the corresponding new energy power generation system is constructed based on the load demand prediction set. The new energy power generation system responds to the regulation strategy to execute the regulation action, significantly improves the stability of the new energy power generation system, effectively delays the performance loss rate of the corresponding energy storage device, and greatly improves the service life of the energy storage device. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Other features, objects, and advantages of the present invention will become more apparent by reading the detailed description of the non-limiting embodiments with reference to the following drawings. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components.

[0022] Figure 1 It is a schematic flowchart of a method for regulating a new energy power generation system; Figure 2 It is a schematic diagram of a load demand prediction graph. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] In order to make the purpose, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described here are only the best embodiments of the present invention, which are only used to explain the present invention and do not limit the protection scope of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0024] Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the operations (or steps) as sequential processes, many of the operations (or steps) can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operations are completed, but it can also have additional steps not included in the drawings; the process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0025] Embodiment 1: As Figure 1 shown, this embodiment provides a method for adjusting a new energy power generation system, including the following steps: S1. Obtain the historical operation data of the new energy power generation system, and extract the benefit characteristics, power characteristics, and energy storage performance characteristics based on the historical operation data.

[0026] In one embodiment, the specific process of extracting the benefit characteristics, power characteristics, and energy storage performance characteristics based on the historical operation data is as follows: Extract the wind power generation revenue and wind power generation cost based on the wind power generation device in the new energy power generation system and the historical operation data; Extract the photovoltaic power generation revenue and photovoltaic power generation cost based on the photovoltaic power generation device in the new energy power generation system and the historical operation data; Extract the energy storage revenue and energy storage cost based on the energy storage device in the new energy power generation system and the historical operation data; Sort out the wind power generation revenue, wind power generation cost, photovoltaic power generation revenue, photovoltaic power generation cost, energy storage revenue, and energy storage cost to obtain the benefit characteristics; extract the power characteristics based on the change trend of the power data corresponding to the benefit characteristics in the historical operation data; Extract the energy storage performance characteristics based on the change trend of the energy storage performance data in the energy storage data set.

[0027] In this embodiment, considering that the characteristics of different types of new energy power generation devices in the new energy power generation system are different, for example, the wind power generation device has an anti-peak shaving characteristic, and the photovoltaic power generation device has randomness, volatility, and uncertainty, the power data, benefit data, cost data, etc. corresponding to the wind power generation device are different from the data corresponding to the photovoltaic power generation device. Therefore, it is necessary to carefully divide the historical operation data to extract the characteristics corresponding to the characteristics of the new energy power generation device and improve the accuracy of the characteristics, that is, wind power generation revenue, wind power generation cost, photovoltaic power generation revenue, photovoltaic power generation cost, energy storage revenue, and energy storage cost.

[0028] S2. Build a hybrid strategy game model based on the benefit characteristics, power characteristics, and energy storage performance characteristics, and collect the real-time operation data of the new energy power generation system.

[0029] In one embodiment, the specific process of constructing a hybrid strategy game model based on the benefit characteristics, power characteristics, and energy storage performance characteristics is as follows: S211. Construct a grid-connected revenue payment function based on the benefit characteristics and power characteristics, and construct a service life payment function based on the benefit characteristics and energy storage performance characteristics; S212. Construct a hybrid strategy game matrix based on the grid-connected revenue payment function and the service life payment function; The specific form of the hybrid strategy game matrix is as follows: In the formula, K represents the hybrid strategy game matrix, x is the probability that the wind power generation device produces low-quality electric energy, y is the probability that the photovoltaic power generation device refuses to coordinate grid connection, z is the probability that the energy storage device operates in the strict life standard consumption mode, C W is the electricity sales revenue from wind power grid connection, C W,CC1 is the construction cost of high-quality wind power, C W,CC2 is the basic wind power construction cost, C W,IC is the cost of the wind power seeking photovoltaic coordination, C EW is the additional grid-connected revenue of wind power, C ESPS,omc is the grid connection cost of the energy storage, C ESPS is the charge-discharge revenue of the energy storage, C ESPS,LL is the charging cost of the energy storage, C ESPS,T is the life penalty cost of the energy storage, C ESPS,W,C is the compensation given by the wind power to the photovoltaic, C ESPS,wdz is the low-quality operation and maintenance cost of the wind power, C PV is the energy supply revenue of the photovoltaic, C PV,omc is the coordination cost of the photovoltaic, C XJ is the negative cost of the photovoltaic, C SM is the life benefit of the energy storage, C LQ is the fine for low-quality wind power.

[0030] In this embodiment, although the wind power generation device and the photovoltaic power generation device have different characteristics and different disadvantages, after establishing a new energy power generation device by taking the wind power generation device and the photovoltaic power generation device as a whole, the respective disadvantages can be eliminated by using the spatio-temporal complementarity between wind power and photovoltaic. Therefore, a grid-connected revenue payment function for wind power is constructed based on a wind power merchant, the wind power constraint conditions corresponding to the wind power merchant, the benefit characteristics, and the power characteristics. The specific form of the grid-connected revenue payment function for wind power is as follows: C W,G = C W,omc + C W,CC1 ; C W,D = C W,omc + CW,CC2 ; In the formula, is the output power of the wind power generation device at time t, is the electricity selling price to the outside at time t. The electricity selling price to the outside is regarded as a constant during the evolutionary game process, and the wind power absorbed by the energy storage is set as the corresponding cost. The electricity price of the cost is negative, k W is the operation and maintenance coefficient, is the output power of the photovoltaic power generation device at time t, ρ PV is the wind power energy search coefficient, λ ew is the additional income coefficient. The additional income coefficient can be specifically formulated according to the actual working conditions and is generally set as the lowest value allowed for the electricity selling price to the outside at time t, λ lq1 is the low-quality coefficient, and T is the time period formed by the set of time t; the specific wind power constraint conditions are: In the formula, is the maximum allowable output power of the wind power generation device at time t; Based on a photovoltaic power generation company, the corresponding photovoltaic constraint conditions, benefit characteristics and power characteristics, a photovoltaic grid-connected income payment function is constructed. The specific photovoltaic grid-connected income payment function is: In the formula, k PV is the photovoltaic operation and maintenance coefficient, λ lq2 is the negative coefficient, σ W is the wind power compensation unit price; The specific photovoltaic constraint conditions are: In the formula, is the maximum allowable output power of the photovoltaic power generation device at time t; In addition, although there is spatio-temporal complementarity between wind power generation and photovoltaic power generation, the overall output still has uncertainty, which will lead to waste of wind power resources or photovoltaic power resources. Therefore, based on the benefit characteristics and energy storage performance characteristics, a service life payment function of the corresponding energy storage device is constructed. The specific service life payment function is: In the formula, is the electricity quantity released or absorbed during the charge and discharge process of the energy storage device, is the additional charging electricity quantity of the energy storage device for consuming wind power, k ESPS is the operation and maintenance coefficient of the energy storage device, and v is the life cost coefficient of the energy storage device. The life cost coefficient is generally set as the electricity selling price to the outside The lowest value allowed at time t is the standard charge-discharge power of the energy storage device, λ SM is the life benefit coefficient of the energy storage device, λ wdz is the low-quality operation and maintenance cost of wind power; Secondly, the energy storage device also needs to meet the energy storage constraint conditions, and the specific energy storage constraint conditions are as follows: In the formula, is the remaining capacity of the energy storage device at time t, E ESPS,min is the minimum capacity of the energy storage device, E ESPS,max is the maximum capacity of the energy storage device, is the remaining capacity of the energy storage device at time t + 1, is a binary variable. Specifically, the binary variable represents discharging when it is 0, and the binary variable represents charging when it is 1, η ESPS,c is the charging efficiency of the energy storage device, is the absorption power of the energy storage device at time t, Δt is the time for the energy storage device to absorb electric energy or output electric energy, is the output power of the energy storage device at time t, is the maximum absorption power of the energy storage device, is the maximum output power of the energy storage device, is the capacity of the energy storage device before participating in regulation, is the capacity of the energy storage device after participating in regulation; In addition, the hybrid strategy game matrix constructed by taking the wind power grid connection revenue payment function, the photovoltaic grid connection revenue payment function, and the service life payment function as a whole also needs to meet the corresponding electricity load demand constraint conditions of the new energy power generation system. The specific electricity load demand constraint conditions are as follows: In the formula, is the output power of the energy storage device at time t, is the output power of the photovoltaic power generation device within time T, is the output power of the wind power generation device within time T, is the load consumption power at time t, is the absorption power of the energy storage device within time T.

[0031] Finally, a hybrid strategy game matrix is constructed based on the grid connection revenue payment function and the service life payment function. The hybrid strategy game matrix also needs to meet five game conditions. Specifically: The first game condition: Taking the wind power operator as the game subject participant 1, the strategy space of the wind power operator is S W ={S W,1 ,S W,2}={producing low-quality wind power, producing high-quality wind power}, and stipulating that the probability of producing low-quality wind power is x, the probability of producing high-quality wind power is (1 - x), and x ∈ [0, 1]; taking the photovoltaic power generator as the game subject participant 2, the strategy space of the photovoltaic power generator is S PV ={S PV,1 ,S PV,2}={refusing to coordinate the power grid, agreeing to coordinate the power grid}, and stipulating that the probability of refusing to coordinate the power grid is y, the probability of agreeing to coordinate the power grid is (1 - y), and y ∈ [0, 1]; taking the energy storage device as the game subject participant 3, the strategy space of the energy storage device is S ESPS ={S ESPS,1 ,S ESPS,2}={strict life standard consumption mode, loose life standard consumption mode}, and stipulating that the probability of the energy storage device choosing the strict life standard consumption mode is z, the probability of the energy storage device choosing the loose life standard consumption mode is (1 - z), and z ∈ [0, 1]; The second game condition: Since wind power has the characteristics of reverse peak shaving and is relatively difficult to connect to the grid compared with photovoltaic power, in order to develop wind power in a high-quality manner, a new energy grid connection operation mode with wind power as the main body and photovoltaic power assisting wind power grid connection is proposed; among them, the wind power operator of the game subject participant 1 uses low-wind-speed wind power generation technology to produce high-quality wind power, specifically a way to smooth the wind power output curve by generating electricity through relevant technologies at low-wind-speed moments at noon. The wind power operator does not need to apply this technology to produce low-quality wind power, and the cost C W,D of producing low-quality wind power is less than the cost C W,G of producing high-quality wind power; secondly, when the wind power operator produces low-quality wind power, especially during the two time periods of high wind power at night and almost zero wind power output at noon, due to the reverse peak shaving characteristics of the wind power generation device, the amount of abandoned wind increases, and it is necessary to coordinate the grid connection through the photovoltaic power generator to meet the grid connection conditions of the new energy power generation system. Otherwise, in order to reduce the output loss of wind power, it will be in a shutdown state for most of the time, and the power grid side and user side will reduce the utilization of new energy due to the randomness of new energy output. At this time, the wind power operator will generate a wind power seeking photovoltaic coordination cost C W,IC , and the wind power seeking photovoltaic coordination cost C W,IC is less than the difference between the cost C W,G of producing high-quality wind power and the cost C W,D of producing low-quality wind power. At the same time, producing low-quality wind power will generate a cost for compensating photovoltaic power; The third game condition: The electric energy generated by wind power during the low wind speed period is less, and the power generation loss during low wind speed operation is large. Therefore, wind turbines may not start during low wind speed periods. Through coordinated grid connection of wind and light, the overall output of new energy can be increased; when photovoltaic agrees to coordinate the grid connection of wind power, the revenue of the photovoltaic power generator for energy supply is C PV , wind power will give a certain compensation C ESPS,W,C to photovoltaic. In addition, when the wind power producer produces low-quality wind power, if photovoltaic refuses to coordinate the grid connection of wind power, that is, photovoltaic participates in other transactions by itself and does not participate in the transactions of the integrated wind-solar-storage charging and discharging power station. At this time, the revenue of the photovoltaic power generator is equal to C PV , mainly because the revenue channels of the photovoltaic power generator have changed, and there will be a large amount of abandoned wind power. If photovoltaic agrees to coordinate the grid connection, a coordination cost C mainly composed of the life loss cost of energy storage devices will be generated PV,omc , and the life loss cost of the energy storage device corresponds to the performance loss of the energy storage device; The fourth game condition: When the energy storage device participates in consumption in accordance with strict life standards, the energy storage device will generate a certain life benefit C SM , and the life benefit C SM is obtained through negotiation with the wind power producer and the photovoltaic power generator. The wind power producer producing low-quality wind power will be fined C LQ , and the photovoltaic power generator that does not coordinate the grid connection will be punished with a certain negative cost C XJ , and C SM < (C LQ + C XJ ). When the energy storage device participates in consumption with a loose life standard, the wind power producer will increase the grid connection capacity and obtain additional grid connection revenue C EW , and the revenue of the wind power producer mainly comes from the abandoned wind volume absorbed by energy storage charging. The cost of the energy storage device participating in the grid connection of wind power is C ESPS,omc , and the C ESPS,omc is mainly the operation and maintenance cost; The fifth game condition: When the wind power producer produces high-quality wind power, it helps to coordinate and complement wind and light, smooth the output of new energy, and reduce the situation of overcharging and over-discharging of the energy storage power station, thereby reducing the life cost consumption of the energy storage device, that is, delaying the performance loss rate of the energy storage device. When the wind power producer produces low-quality wind power and the photovoltaic producer does not coordinate the grid connection, the low-quality wind power will increase the load fluctuation of the power grid, forming a behavior of adding peaks to peaks and valleys to valleys. To regulate the load fluctuation of the power grid, the energy storage device will operate under the loose life charge and discharge standard. At this time, the charging cost of the energy storage device is C ESPS,LL, if the energy storage device is under the loose life charge-discharge standard for a long time, the service life of the energy storage device will be shortened, and it may occur that the energy storage device is scrapped to achieve economic benefits within its cost recovery period. Therefore, the energy storage device will be subject to a certain life penalty cost C ESPS,T , and the life penalty cost C ESPS,T is greater than the cost C ESPS,omc of the energy storage device participating in wind power grid connection. At this time, the charge-discharge income of the energy storage device is C ESPS . Secondly, under the condition of photovoltaic refusal to coordinate grid connection and when the energy storage power station adopts the loose life standard, corresponding low-quality wind power operation and maintenance cost C ESPS,wdz will be generated.

[0032] S213. Establish an expected income function and an average expected income function based on the mixed strategy game matrix and the selection probability corresponding to the working mode of the new energy power generation system, and construct a mixed strategy game model based on the income function and the average expected income function; The specific mixed strategy game model is as follows: In the formula, is the energy storage replicator dynamic equation, x is the probability of the wind power generation device producing low-quality electric energy, E 11 is the energy storage expected income, is the energy storage average expected income, is the wind power replicator dynamic equation, y is the probability of the photovoltaic power generation device refusing to coordinate grid connection, E 21 is the wind power expected income, is the wind power average expected income, is the photovoltaic replicator dynamic equation, z is the probability of the energy storage device operating in the strict life standard consumption mode, E 31 is the photovoltaic expected income, is the photovoltaic average expected income, and t is time.

[0033] In this embodiment, the expected income and the average expected income of the energy storage device participating in and not participating in the consumption of new energy are respectively: E 11 = yz(C W - C W,CC1 ) + y(1 - z)(C W - C W,CC1 - C EW ) + (1 - y)z(C W - C W,CC1 ) + (1 - y)(1 - z)(C W - C W,CC1 - C EW ) E 12= yz(C W - C W,CC2 - C LQ ) + z(1 - y)(C W - C W,CC2 - C LQ - C W,IC ) + y(1 - z)(C W - C W,CC2 - C EW ) + (1 - y)(1 - z)(C W - C W,CC2 - C W,IC + C EW ) In the formula, is the average expected benefit of energy storage, E 12 is the expected benefit of energy storage not participating in the consumption of new energy, E 11 is the expected benefit of energy storage in the mixed - strategy game model, and it is also the expected benefit of energy storage participating in the consumption of new energy; The expected benefits and average expected benefits of wind power producers cooperating and not cooperating with PV for coordinated grid connection are respectively: E 21 = xz(C PV - C PV,omc - C XJ ) + x(1 - z)(C PV ) + (1 - x)z(C PV - C PV,omc - C XJ ) + (1 - x)(1 - z)(C PV - C PV,omc ) E 22 = xz(C PV - C PV,omc + C ESPS,W,C ) + z(1 - x)(C PV - C PV,omc + C ESPS,W,C ) + x(1 - z)(C PV - C PV,omc ) + (1 - x)(1 - z)(C PV - C PV,omc + C ESPS,W,C ) In the formula, is the average expected benefit of wind power, E 21It is the expected revenue for wind power not to cooperate with photovoltaic for coordinated grid connection, and also the expected revenue of wind power in the mixed strategy game model, E 22 It is the expected revenue for wind power to cooperate with photovoltaic for coordinated grid connection; The expected revenues and average expected revenues for photovoltaic power generators to cooperate and not cooperate with wind power for coordinated grid connection are as follows: E 31 = xy(C SM - C ESPS,omc + C ESPS ) + x(1 - y)(C SM - C ESPS,omc + C EW ) +(1 - x)y(C SM - C ESPS,omc + C EW )+(1 - x)(1 - y)(C SM - C ESPS,omc + C ESPS ) E 32 = xy(C ESPS - C ESPS,omc - C ESPS,LL - C ESPS,T )+ y(1 - x)(C ESPS - C ESPS,omc - C ESPS,LL - C ESPS,T ) + x(1 - y)(C ESPS - C ESPS,omc - C ESPS,LL - C ESPS,T )+(1 - x)(1 - y)(C ESPS - C ESPS,omc - C ESPS,LL - C ESPS,T - C ESPS,wdz ) In the formula, E 31 is the expected revenue of photovoltaic in the mixed strategy game model, and also the expected revenue for photovoltaic power generators not to cooperate with wind power for coordinated grid connection, is the average expected revenue of photovoltaic, and E 32 is the expected revenue for photovoltaic power generators to cooperate with wind power for coordinated grid connection.

[0034] S3. Set the real-time parameter combination of the mixed strategy game model based on the real-time operation data, and perform stability analysis on the mixed strategy game model based on the stability rule and the real-time parameter combination to obtain the stable equilibrium point.

[0035] In one embodiment, the specific process of setting the real-time parameter combination of the hybrid strategy game model based on real-time operation data is as follows: S311. Determine the parameter types based on the parameter combination of the hybrid strategy game model, and extract the data change characteristics and data interaction characteristics corresponding to the parameters based on the parameter types and real-time operation data; S312. Determine the real-time parameter combination based on the data change characteristics and data interaction characteristics.

[0036] In this embodiment, since the parameters of the new energy power generation system corresponding to different actual working conditions will be somewhat different, therefore, based on the data change characteristics, that is, the relationship of data on the time scale, and the data interaction characteristics, that is, the mutual influence relationship of different data, to determine the parameter combination, parameters that conform to the actual working conditions of the new energy power generation system can be obtained.

[0037] In one embodiment, the specific process of performing stability analysis on the hybrid strategy game model based on the stability law and real-time parameter combination to obtain the stable equilibrium point is as follows: S321. Adjust the hybrid strategy game model based on the real-time parameter combination, and extract the equilibrium point of the adjusted hybrid strategy game model based on the selection probability of the working mode of the new energy power generation system and the preset balance probability value; S322. Construct a Jacobian matrix based on the equilibrium point, and judge the stability of the equilibrium point based on the real part of the eigenvalue in the Jacobian matrix. If the real parts of all the eigenvalues are negative real parts, it is determined that the corresponding equilibrium point is stable. If at least one of the real parts of the eigenvalues is a positive real part, it is determined that the corresponding equilibrium point is unstable; Synchronously, mark all the equilibrium points determined to be stable as stable equilibrium points; The specific form of the Jacobian matrix is as follows: In the formula, J is the Jacobian matrix, J 1 is the first equilibrium point, J 2 is the second equilibrium point, J 3 is the third equilibrium point, J 4 is the fourth equilibrium point, J 5 is the fifth equilibrium point, J 6 is the sixth equilibrium point, J 7 is the seventh equilibrium point, J 8 is the eighth equilibrium point, J 9 is the ninth equilibrium point, is the energy storage replicator dynamic equation, x is the probability that the wind power generation device produces low-quality electric energy, is the wind power replicator dynamic equation, y is the probability that the photovoltaic power generation device refuses to coordinate and connect to the grid, It is the dynamic equation of the PV replicator, and z is the probability of the consumption mode with strict life standards for the operation of the energy storage device.

[0038] In this embodiment, the stability law is essentially the first Lyapunov law, and the specific content of the first Lyapunov law is as follows: a If all the eigenvalues of the Jacobian matrix have negative real parts, the equilibrium point is an asymptotically stable point; b If at least one of the eigenvalues of the Jacobian matrix has a positive real part, the equilibrium point corresponding to this eigenvalue is an unstable point; When, except for some eigenvalues with zero real parts in the Jacobian matrix, other eigenvalues all have negative real parts, the equilibrium point is in a critical state.

[0039] S4. Run the hybrid strategy game model based on the stable equilibrium point to obtain a load demand prediction set, and construct a new energy power generation system regulation strategy based on the load demand prediction set.

[0040] In one embodiment, the specific process of running the hybrid strategy game model based on the stable equilibrium point to obtain a load demand prediction set is as follows: S411. Adjust the selection probability of the working mode of the new energy power generation system corresponding to the hybrid strategy game model based on the stable equilibrium point to obtain a real-time hybrid strategy; S412. Run the hybrid strategy game model based on the real-time hybrid strategy to obtain load demand prediction data, and draw a load demand prediction graph as shown in Figure 2 the load demand prediction graph; S413. Organize the load demand prediction data and the load demand prediction graph to obtain a load demand prediction set.

[0041] In one embodiment, the specific process of constructing a new energy power generation system regulation strategy based on the load demand prediction set is as follows: S421. Determine the load change trend of the new energy power generation system on the time scale based on the load demand prediction set, and determine the adjustable power and non-adjustable power based on the load change trend; S422. Determine the regulating equipment and the equipment to be regulated based on the adjustable power, non-adjustable power and the topological structure of the new energy power generation system, and construct a new energy power generation system regulation strategy based on the regulating equipment and the equipment to be regulated.

[0042] This embodiment has at least the following substantial effects: In this embodiment, benefit characteristics, power characteristics, and energy storage performance characteristics are extracted based on the historical operation data of the new energy power generation system, the mutual influence relationship between the new energy power generation and the energy storage power station is fully explored, and a hybrid strategy game model is constructed according to the mutual influence relationship to simulate the operation state of the new energy power generation system, so as to predict the changes of various data of the new energy power generation system. At the same time, based on the real-time operation data of the new energy power generation system, the real-time parameter combination of the hybrid strategy game model is set to make the hybrid strategy game model fit the actual working conditions of the new energy power generation system, improve the accuracy of the hybrid strategy game model, and perform stability analysis on the hybrid strategy game model based on the stability law to find the stable equilibrium points where the new energy power generation and the energy storage power are balanced and operate stably under different time periods and different working conditions. Finally, the load demand prediction set is obtained by operating the hybrid strategy game model based on the real-time parameter combination and the stable equilibrium point, the operation state of the corresponding new energy power generation system is predicted, and the regulation strategy of the corresponding new energy power generation system is constructed based on the load demand prediction set. The new energy power generation system responds to the regulation strategy to perform regulation actions, significantly improving the stability of the new energy power generation system and effectively delaying the performance loss rate of the corresponding energy storage device, greatly improving the service life of the energy storage device.

[0043] The above specific implementation manners are the preferred implementation manners of the present invention, which do not limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to this specific implementation manner. All equivalent changes made according to the shape, structure, and method of the present invention are within the protection scope of the present invention.

Claims

1. A method for regulating a new energy power generation system, characterized in that: The following steps are involved: S1. Obtain historical operation data of the new energy power generation system, and extract benefit characteristics, power characteristics and energy storage performance characteristics based on the historical operation data; S2. Building a mixed strategy game model based on the benefit characteristics, power characteristics and energy storage performance characteristics, and collecting real-time operation data of the new energy power generation system; S3. Setting a real-time parameter combination of the mixed strategy game model based on the real-time operation data, and performing stability analysis on the mixed strategy game model based on the stability rule and the real-time parameter combination to obtain a stable equilibrium point; S4. Running a mixed strategy game model based on the stable equilibrium point obtains a load demand forecast set, and constructs a new energy power generation system regulation strategy based on the load demand forecast set.

2. A method for regulating a new energy power generation system according to claim 1, characterized in that: In S1, the specific process of extracting benefit characteristics, power characteristics and energy storage performance characteristics based on historical operation data is as follows: Extract wind power revenue and wind power cost based on wind power generation devices and historical operation data in the new energy power generation system; Extract photovoltaic revenue and photovoltaic cost based on photovoltaic power generation devices and historical operation data in new energy power generation systems; Extract energy storage benefits and costs based on energy storage devices and historical operation data in new energy power generation systems; Arrange the wind power income, wind power cost, photovoltaic income, photovoltaic cost, energy storage income and energy storage cost to obtain benefit characteristics; Extract power characteristics based on the power data change trend of the corresponding benefit characteristics in the historical operation data; The energy storage performance characteristics are extracted based on the change trend of energy storage performance data in the energy storage data set.

3. A method for regulating a new energy power generation system according to claim 1, characterized in that: In S2, the specific process of constructing a mixed strategy game model based on benefit characteristics, power characteristics and energy storage performance characteristics is as follows: S211, constructing a grid-connected benefit payment function based on the benefit characteristics and power characteristics, and constructing a service life payment function based on the benefit characteristics and energy storage performance characteristics; S212, constructing a mixed strategy game matrix based on the grid-connected income payment function and the service life payment function; S213. Establish an expected profit function and an average expected profit function based on the mixed strategy game matrix and the selection probability corresponding to the working mode of the new energy power generation system, and construct a mixed strategy game model based on the profit function and the average expected profit function.

4. A method for regulating a new energy power generation system according to claim 3, characterized in that: In S212, the mixed strategy game matrix is ​​specifically: Where K represents the mixed strategy game matrix, x is the probability that the wind power generation device produces low-quality electricity, y is the probability that the photovoltaic power generation device refuses to coordinate the grid connection, z is the probability that the energy storage device operates in a strict life standard consumption mode, and C W is the electricity sales revenue of wind power grid-connected, C W,CC1 is the construction cost of high-quality wind power, C W,CC2 is the basic wind power construction cost, C W,IC Seeking PV coordination costs for wind power, C EW is the additional grid-connected income of wind power, C ESPS,omc is the grid-connected energy storage cost, C ESPS is the energy storage charging and discharging income, C ESPS,LL is the energy storage charging cost, C ESPS,T is the energy storage lifetime penalty cost, C ESPS,W,C Compensation for photovoltaic power generation from wind power, C ESPS,wdz The low-quality operation and maintenance fee for wind power, C PV is the photovoltaic energy income, C PV,omc is the photovoltaic coordination cost, C XJ is the passive cost of photovoltaic power generation, C SM is the energy storage life benefit, C LQ Fines for low quality wind power.

5. A method for regulating a new energy power generation system according to claim 3, characterized in that: In S213, the mixed strategy game model is specifically: In the formula, is the dynamic equation of the energy storage replicator, x is the probability that the wind power generation device produces low-quality electricity, E 11 is the expected benefit of energy storage, is the average expected benefit of energy storage, is the dynamic equation of wind power replicator, y is the probability of photovoltaic power generation device refusing to coordinate grid connection, E 21 is the expected revenue of wind power, is the average expected revenue of wind power, is the dynamic equation of the photovoltaic replicator, z is the probability of the energy storage device operating in the strict life standard absorption mode, E 31 is the expected revenue of photovoltaic power generation, is the average expected return of photovoltaic power generation, and t is the time.

6. A method for regulating a new energy power generation system according to claim 1, characterized in that: In S3, the specific process of setting the real-time parameter combination of the mixed strategy game model based on the real-time operation data is as follows: S311, determining parameter types based on the parameter combination of the mixed strategy game model, and extracting parameter corresponding data change characteristics and data interaction characteristics based on the parameter types and real-time operation data; S312: Determine a real-time parameter combination based on the data change characteristics and data interaction characteristics.

7. A method for regulating a new energy power generation system according to claim 6, characterized in that: In S3, the specific process of performing stability analysis on the mixed strategy game model based on the stability rule and the real-time parameter combination to obtain a stable equilibrium point is: S321, adjusting the mixed strategy game model based on the real-time parameter combination, and extracting the equilibrium point of the adjusted mixed strategy game model based on the selection probability of the working mode of the new energy power generation system and the preset equilibrium probability value; S322, constructing a Jacobian matrix based on the equilibrium point, and judging the stability of the equilibrium point based on the real parts of the eigenvalues ​​in the Jacobian matrix, if the real parts of the eigenvalues ​​are all negative, then the corresponding equilibrium point is judged to be stable, and if at least one of the real parts of the eigenvalues ​​is a positive real part, then the corresponding equilibrium point is judged to be unstable; Simultaneously, all equilibrium points that are determined to be stable are marked as stable equilibrium points.

8. A method for regulating a new energy power generation system according to claim 7, characterized in that: In S322, the Jacobian matrix is ​​specifically: Where J is the Jacobian matrix, J1 is the first equilibrium point, J2 is the second equilibrium point, J3 is the third equilibrium point, J4 is the fourth equilibrium point, J5 is the fifth equilibrium point, J6 is the sixth equilibrium point, J7 is the seventh equilibrium point, J8 is the eighth equilibrium point, and J9 is the ninth equilibrium point. is the dynamic equation of the energy storage replicator, x is the probability that the wind power generation device produces low-quality electricity, is the dynamic equation of wind power replicator, y is the probability of photovoltaic power generation device refusing to coordinate grid connection, is the dynamic equation of the photovoltaic replicator, and z is the probability of the energy storage device operating in a strict lifetime standard absorption mode.

9. A method for regulating a new energy power generation system according to claim 1, characterized in that: In S4, the specific process of obtaining the load demand forecast set by running the mixed strategy game model based on the stable equilibrium point is: S411, adjusting the selection probability of the working mode of the new energy power generation system corresponding to the mixed strategy game model based on the stable equilibrium point to obtain a real-time mixed strategy; S412, running a mixed strategy game model based on the real-time mixed strategy to obtain load demand forecast data, and drawing a load demand forecast graph based on the load demand forecast data; S413: Arrange the load demand forecast data and the load demand forecast graph to obtain a load demand forecast set.

10. A method for regulating a new energy power generation system according to claim 9, characterized in that: In S4, the specific process of constructing the regulation strategy of the new energy power generation system based on the load demand forecast set is: S421, determining a load change trend of the new energy power generation system on a time scale based on the load demand forecast set, and determining adjustable power and non-adjustable power based on the load change trend; S422: Determine a regulating device and a regulated device based on the adjustable power, the non-adjustable power and the topological structure of the new energy power generation system, and construct a regulating strategy for the new energy power generation system based on the regulating device and the regulated device.

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