Method and system for coordinated operation of wind-solar-storage multi-energy complementary power station

Abstract

The present application relates to the technical field of wind and light storage power station operation control, and discloses a wind and light storage multi-energy complementary power station cooperative operation method and system.The method comprises the following steps: constructing a wind and light fluctuation rate phase plane, defining a coupled stable elliptical region and generating a multi-source coupled state label; constructing a storage response performance plane, calculating a dynamic dead zone threshold parameter, establishing a dynamic breathing hexagon boundary, calculating a penetration depth to generate a storage effective action instruction; constructing a virtual energy gravity potential field using the storage effective action instruction, calculating the virtual potential height of the independent physical node and the nonlinear flow resistance characteristics of the virtual energy transmission pipeline, analyzing the virtual potential height difference and the virtual energy flow rate, and obtaining the final power distribution scheme.The present application realizes accurate classification of fluctuation modes through geometric topology, takes into account battery life and stability control requirements by using dynamic breathing hexagons, solves the multi-objective optimization calculation lag problem based on physical field theory, and significantly improves the operation efficiency and grid friendliness of the power station.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wind-solar-storage power station operation control, more specifically, the present application relates to a wind-solar-storage multi-energy complementary power station collaborative operation method and system. BACKGROUND

[0002] With the rapid growth of new energy grid-connected scale, wind-solar-storage multi-energy complementary power station has become the core regulating unit of the power system. However, traditional collaborative operation methods, such as setting a fixed charge-discharge dead zone or simple allocation based on the absolute value of power gap, generally face the bottleneck of stability control efficiency, and it is difficult to balance battery life and system stability. It mainly stays in the algebraic balance of static power values, ignoring the dynamic coupling resonance effect of multi-source energy in the time-varying process, that is, it cannot distinguish whether the wind-solar fluctuation is a malignant same direction superposition or a benign complementary offset, resulting in invalid high-frequency throughput of the energy storage system in the self-balancing scene, causing life overdraft. In addition, the traditional multi-objective optimization algorithm has a huge amount of calculation to solve complex differential algebraic equations, which cannot meet the real-time requirements of primary frequency modulation. Therefore, how to change from static power balance to dynamic fluctuation rate coupling analysis, change rigid control to adaptive geometric constraint integrating battery health, and break through the calculation lag limit, is a technical problem to be solved in this field.

[0003] In the prior art, a power distribution network optimization scheduling method, computer equipment and power distribution network optimization scheduling system of wind-solar-storage collaboration are disclosed in Chinese patent application No. CN119209634A. The system contains a cost parameter analysis unit, a source-load data acquisition module and a demand response scheduling module, which can realize functions such as intra-day wind-solar cost prediction, source-side power generation and load-side power consumption collection. By analyzing the deviation between the planned power supply and the actual power supply within a day, it takes a B-type incentive demand response or redundant energy storage strategy to realize load balancing and peak clipping of the power distribution network, and to improve the utilization efficiency of power resources. A virtual synchronous machine energy storage frequency modulation method and system based on model prediction and adaptive control are disclosed in Chinese patent application No. CN120200275A. The system adopts a predictive control and adaptive control fusion architecture, containing a virtual synchronous machine prediction model construction unit, a quadratic programming solution module and an inertia damping coefficient adjustment unit, which respectively realize state equation discretization processing, optimal control sequence solving and virtual inertia coefficient dynamic correction. It combines the cost function optimization with the dynamic characteristics of energy storage to improve the frequency stability of the power system with high proportion of new energy access.

[0004] However, the above two prior arts have certain value in power distribution network dispatching optimization and frequency stability improvement, but cannot solve the core pain points of current wind-solar-storage multi-energy complementary power station dynamic collaboration. Among them, the patent with publication number CN119209634A focuses on a static dispatching strategy based on cost parameters, does not involve multi-source energy dynamic coupling resonance effect analysis, cannot distinguish between malignant same-direction superposition and benign complementary offset of wind-solar fluctuations, and causes invalid throughput of storage in a self-balancing scenario; and does not establish an adaptive constraint mechanism integrating battery health, making it difficult to balance battery life and system stability. The patent with publication number CN120200275A focuses on virtual synchronous machine frequency control, although model predictive optimization is used, but cannot break through the bottleneck of large calculation amount of complex algorithm, cannot meet the real-time requirement of primary frequency modulation, and does not take the dynamic coupling characteristics of wind-solar-storage multi-energy into the control model, still staying in the technical framework of single storage frequency modulation. Both of them cannot realize the transition from static power balance to dynamic fluctuation rate coupling analysis, and cannot meet the efficient collaborative operation demand of multi-energy complementary power station. SUMMARY

[0005] The present application is suitable for wind-solar-storage multi-energy complementary power station, especially high proportion of new energy grid-connected scene, can meet the millisecond level frequency stability control and battery life cycle management demand; through the wind-solar fluctuation rate phase plane and the coupling stability ellipse region which can stretch and shrink with the regional power grid operation state in real time, identify the multi-source coupling state label, realize the qualitative classification of energy fluctuation mode, avoid invalid adjustment to the fluctuation within the safe range of power grid; use the storage response performance plane to construct the dynamic breathing hexagon boundary, fuse the one-dimensional power dead zone and the two-dimensional storage system state of charge physical boundary, generate the effective storage action instruction filtered by the storage battery health, introduce the flexible game mechanism at the control source; based on the nonlinear flow resistance characteristics of virtual energy gravity potential field and virtual energy transmission pipeline, analyze the virtual energy flow velocity, convert the complex collaborative optimization into physical field calculation without iteration, solve the multi-objective dispatching calculation lag problem, derive the final power distribution scheme considering economy and stability, improve the power station operation efficiency and grid friendliness.

[0006] To achieve the above purpose, the present application provides the following technical solutions:

[0007] The wind-solar-storage multi-energy complementary power station collaborative operation method comprises:

[0008] Obtain the original power data, normalize the original power data to obtain a set of change rate data, construct a wind-solar fluctuation rate phase plane according to the set of change rate data, define a coupling stability ellipse region which can stretch and shrink with the regional power grid operation state in real time in the wind-solar fluctuation rate phase plane, qualitatively classify the coupling stability ellipse region to obtain a multi-source coupling state label;

[0009] The internal state data of the energy storage system is acquired to construct an energy storage response performance plane, dynamic dead zone threshold parameters of automatic adjustment are calculated according to the multi-source coupled state label and the energy storage response performance plane, and a dynamic breathing hexagon boundary is constructed in the energy storage response performance plane according to the dynamic dead zone threshold parameters.

[0010] The effective energy storage action instruction is used as a driving source to construct a virtual energy gravity potential energy field, and the virtual energy gravity potential energy field is analyzed to obtain a final power distribution scheme.

[0011] Further, the wind-solar fluctuation rate phase plane comprises:

[0012] The original power data comprises total wind farm grid-connected point power and total photovoltaic power station grid-connected point power at each sampling time point of data acquisition according to a preset sampling frequency;

[0013] The original power data is processed to calculate the wind power change rate and the photovoltaic power change rate capable of representing the inertia impact characteristics of the power grid respectively;

[0014] A two-dimensional rectangular coordinate system with the wind power change rate as the X-axis and the photovoltaic power change rate as the Y-axis, i.e. a wind-solar fluctuation rate phase plane, is established;

[0015] The wind power change rate and the photovoltaic power change rate at the same time are mapped into a real-time fluctuation state point in the wind-solar fluctuation rate phase plane, wherein the coordinate origin of the wind-solar fluctuation rate phase plane is defined as a zero fluctuation steady state point, the first quadrant and the third quadrant are defined as a same direction superposition fluctuation area, and the second quadrant and the fourth quadrant are defined as a complementary offset fluctuation area.

[0016] Further, the method for obtaining the coupled stability elliptical area comprises:

[0017] The regional power grid operation parameters are acquired in real time from a power dispatch center, and the regional power grid operation parameters comprise a frequency deviation allowable threshold and a current rotating reserve capacity;

[0018] By using the regional power grid operation parameters, the maximum tolerance limit of the regional power grid to the wind power change rate, i.e. a wind maximum instantaneous acceptance slope, and the maximum tolerance limit of the regional power grid to the photovoltaic power change rate, i.e. a photovoltaic maximum instantaneous acceptance slope, are derived before triggering the action of the low-frequency load shedding device of the regional power grid.

[0019] The maximum instantaneous receiving slope of the wind power is set as a long semi-axis parameter, and the maximum instantaneous receiving slope of the photovoltaic power is set as a short semi-axis parameter, to construct a closed elliptical geometric boundary, i.e., a coupling stable elliptical region; if the current spinning reserve capacity decreases, the coupling stable elliptical region shrinks to the origin of the wind and light fluctuation rate plane to reduce the tolerance to fluctuation, and vice versa, the coupling stable elliptical region expands outward, and this dynamic expansion realizes real-time quantification of the power grid safety margin.

[0020] Further, the multi-source coupling state label comprises:

[0021] The elliptical boundary discriminant value of the real-time fluctuation state point relative to the coupling stable elliptical region is calculated.

[0022] The multi-layer judgment is performed on the elliptical boundary discriminant value, if the elliptical boundary discriminant value is less than or equal to 1, it is judged that the real-time fluctuation state point is located inside or on the boundary of the coupling stable elliptical region, which indicates that the current wind and light combined fluctuation is within the safety range of the regional power grid, and a silent state label is generated; if the elliptical boundary discriminant value is greater than 1, it is judged that the real-time fluctuation state point is located outside the coupling stable elliptical region, which indicates that the current wind and light combined fluctuation exceeds the instantaneous receiving capacity of the regional power grid, and a secondary classification is performed according to the quadrant.

[0023] If the real-time fluctuation state point is located in the first or third quadrant, it indicates that the fluctuation directions of the wind power and the photovoltaic power are the same, forming a resonance effect, and a high forced state label is generated; if the real-time fluctuation state point is located in the second or fourth quadrant, it indicates that the fluctuation directions of the wind power and the photovoltaic power are opposite, and a weak compensation state label is generated, and the silent state label, the high forced state label and the weak compensation state label are combined into a multi-source coupling state label.

[0024] Further, the method for obtaining the energy storage response performance plane comprises:

[0025] The internal state data of the energy storage system comprises the state of charge of the energy storage system, the real-time temperature of the energy storage battery and the health degree of the energy storage battery;

[0026] The real-time load data of the regional power grid is obtained, and the real-time load data of the regional power grid is combined with the total power of the wind power plant and the total power of the photovoltaic power station to calculate the power deviation demand of the power grid.

[0027] A two-dimensional coordinate system, i.e., an energy storage response performance plane, is constructed with the state of charge of the energy storage system as the horizontal axis and the power deviation demand of the power grid as the vertical axis, and any point on the energy storage response performance plane is defined as a real-time operation point.

[0028] Further, the dynamic dead zone threshold parameter comprises:

[0029] The reference dead zone constant is obtained according to a power grid dispatching protocol, and a coupling state correction coefficient is determined according to a multi-source coupling state, wherein the coupling state correction coefficient is set in stages according to the multi-source coupling state.

[0030] The health state correction coefficient is determined according to the real-time temperature of the energy storage battery and the health degree of the energy storage battery, the reference dead zone constant, the coupling state correction coefficient and the health state correction coefficient are multiplied to obtain a dynamic dead zone threshold parameter which is real-time scalable with the working condition.

[0031] Further, the method for obtaining the energy storage effective action instruction comprises:

[0032] The position relationship between the real-time operating point and the dynamic breathing hexagon boundary is judged, if the real-time operating point is located inside or on the dynamic breathing hexagon boundary, the penetration depth is determined to be zero, if the real-time operating point is located outside the dynamic breathing hexagon boundary, the penetration depth needs to be calculated, and the penetration depth is the Euclidean distance from the real-time operating point to the line segment closest to the dynamic breathing hexagon boundary;

[0033] The penetration depth and the power deviation demand of the power grid are combined to obtain the energy storage effective action instruction, so as to realize the suppression of wind and light fluctuations.

[0034] Further, the virtual energy gravity potential energy field comprises:

[0035] The virtual energy gravity potential energy field is a multi-dimensional topological network space based on a physical analogy method, which is composed of independent physical nodes representing core physical subjects and virtual energy transmission pipelines representing electrical connections;

[0036] An actual electrical single-line diagram in the wind-solar-storage multi-energy complementary power station is obtained, and the actual electrical single-line diagram is a topological structure diagram describing the electrical connection relationship and power transmission path between the core physical subjects in the wind-solar-storage multi-energy complementary power station;

[0037] The core physical subjects in the wind-solar-storage multi-energy complementary power station are one-to-one mapped to the independent physical nodes in the virtual energy gravity potential energy field;

[0038] For each independent physical node, a virtual potential height is calculated, and according to the electrical connection relationship and power transmission path in the actual electrical single-line diagram, a virtual energy transmission pipeline is established between adjacent independent physical nodes, and a nonlinear flow resistance characteristic is set for each virtual energy transmission pipeline.

[0039] Further, the method for obtaining the power distribution scheme comprises:

[0040] According to a preset calculation period, each virtual energy transmission pipeline in the virtual energy gravity potential energy field is traversed, and the virtual potential height difference between the independent physical nodes at both ends of the virtual energy transmission pipeline is calculated.

[0041] By using the virtual potential energy height difference and the nonlinear flow resistance characteristics, the virtual energy flow rate of each virtual energy transmission pipeline is obtained;

[0042] The virtual energy flow rate of each virtual energy transmission pipeline is mapped back to the core physical subject of the wind-solar-storage multi-energy complementary power station to generate the final power distribution scheme.

[0043] The wind-solar-storage multi-energy complementary power station cooperative operation system is used to realize the wind-solar-storage multi-energy complementary power station cooperative operation method, and the system comprises:

[0044] The multi-source fluctuation identification module is used to obtain the original power data, perform normalization processing on the original power data to obtain a change rate data set, construct a wind-solar fluctuation rate phase plane according to the change rate data set, define a coupled stable elliptical region that can stretch and shrink in real time according to the running state of the regional power grid in the wind-solar fluctuation rate phase plane, perform qualitative classification on the coupled stable elliptical region to obtain a multi-source coupling state label;

[0045] The energy storage boundary regulation module is used to obtain internal state data of the energy storage system to construct an energy storage response performance plane, calculate a dynamic dead zone threshold parameter of automatic adjustment according to the multi-source coupling state label and the energy storage response performance plane, and construct a dynamic breathing hexagonal boundary in the energy storage response performance plane according to the dynamic dead zone threshold parameter;

[0046] The potential field cooperative scheduling module is used to use the effective energy storage action instruction as a driving source to construct a virtual energy gravity potential field, and perform analysis on the virtual energy gravity potential field to obtain the final power distribution scheme.

[0047] Compared with the prior art, the present application has the following advantages:

[0048] The present application realizes accurate identification of the multi-source coupling state label by constructing a wind-solar fluctuation rate phase plane and defining a coupled stable elliptical region that can stretch and shrink in real time according to the running state of the regional power grid, solves the pain point that the traditional scheme cannot distinguish between benign complement and malignant resonance fluctuation only by power inventory, converts the traditional one-dimensional fixed dead zone control into a two-dimensional geometric constraint that integrates the state of charge physical boundary of the energy storage system and the health degree of the energy storage battery, generates a smooth energy storage effective action instruction by calculating the penetration depth, solves the technical problem that the battery life is often sacrificed when pursuing stability control effect, and solves the problem that the system scheduling calculation lags behind and the economy and stability are difficult to balance based on the physical analogy calculation model of the virtual energy gravity potential field, uses the nonlinear flow resistance characteristics and the virtual potential energy height difference to guide the virtual energy flow rate, reduces the complex multi-objective iterative optimization to one-time algebraic operation, and significantly improves the operation efficiency of the wind-solar-storage multi-energy complementary power station. BRIEF DESCRIPTION OF DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0050] Figure 1 The method flow chart of the wind-solar-storage multi-energy complementary power station cooperative operation method provided by the embodiment of the present application is shown in the figure.

[0051] Figure 2 The schematic diagram of the wind-solar fluctuation rate phase plane provided by the embodiment of the present application is shown in the figure.

[0052] Figure 3 The judgment flow chart of the power distribution scheme provided by the embodiment of the present application is shown in the figure.

[0053] Figure 4 The function module diagram of the wind-solar-storage multi-energy complementary power station cooperative operation system provided by the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0054] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only constitute some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0055] Embodiment 1

[0056] Please refer to Figure 1 The embodiment provides a wind-solar-storage multi-energy complementary power station cooperative operation method, which comprises the following steps:

[0057] In step S10, the original power data is obtained, the original power data is normalized to obtain a change rate data set, a wind-solar fluctuation rate phase plane is constructed according to the change rate data set, a coupling stability elliptical region which can expand or contract with the real-time operation state of the regional power grid is defined in the wind-solar fluctuation rate phase plane, and a multi-source coupling state label is obtained by qualitatively classifying the coupling stability elliptical region.

[0058] Further, step S10 comprises:

[0059] In step S11, the original power data is obtained, the original power data is normalized to obtain a change rate data set, and a wind-solar fluctuation rate phase plane is constructed according to the change rate data set.

[0060] In the physical architecture of a wind-solar-storage multi-energy complementary power station, wind farms and photovoltaic power stations are connected to the power system through specific electrical nodes. The randomness of wind and solar energy causes the output power to exhibit nonlinear time-varying characteristics. In order to accurately capture the microscopic impact of time-varying characteristics on grid frequency stability, an analytical framework is established that can transform dynamic changes in the time dimension into geometric relationships in the spatial dimension, namely the wind-solar fluctuation rate phase plane. This is a two-dimensional Cartesian coordinate system used to describe the rate of change of wind and photovoltaic power and their mutual coupling relationship. The purpose is to focus on the trend and rate of power change, because the physical essence that directly impacts grid frequency stability is the rate of unbalanced change of power rather than the size of the existing power.

[0061] Synchronous phasor measurement units are deployed at both the wind farm grid connection point and the photovoltaic power station grid connection point. These units collect data according to a preset sampling frequency; for example, the sampling frequency is set to 100Hz to ensure that millisecond-level power fluctuations can be captured. The collected raw power data includes the total power at the wind farm grid connection point. and the total power of the photovoltaic power station grid connection point , where t represents the current sampling time.

[0062] After acquiring the raw power data, in order to eliminate high-frequency noise in the signal and extract the fluctuation trend that has significance for the primary frequency regulation response of the power grid, a sliding time window differential algorithm is used to process the total power at the grid connection points of the wind farm and the photovoltaic power station. Specifically, a sliding time window is defined, and the length of the sliding time window is denoted as . , The value range is set to satisfy the time scale of the primary frequency regulation response characteristics of the power grid, for example, The time window is set to 1 to 5 seconds. The rate of change of wind power is calculated based on the sliding time window. With photovoltaic power change rate The formula for calculating the rate of change of wind power is: ,in, Indicates before the current time. The total power of the wind farm at the grid connection point at any given time; the formula for calculating the rate of change of photovoltaic power is: ,in, Indicates before the current time. The reason for setting the numerator term in the two calculation formulas is that the stability of the grid frequency is mainly affected by the power increment rather than the stock; the purpose is to separate the static reference value representing the energy stock from the total power at the wind farm and photovoltaic power station grid connection points, and only retain the dynamic fluctuation component that causes the grid state to change, thereby improving the relevance of the control and eliminating the analysis bias introduced by the different wind power and photovoltaic installed capacity or base output levels. The wind power change rate and the photovoltaic power change rate are combined to obtain a change rate data set, and the combined physical effect of the wind power change rate and the photovoltaic power change rate is defined as the wind-solar combined fluctuation.

[0063] The wind-solar fluctuation rate phase plane is constructed by the wind power change rate and the photovoltaic power change rate of the change rate data set, the wind-solar fluctuation rate phase plane takes the wind power change rate as the X-axis and the photovoltaic power change rate as the Y-axis, and the coordinate origin is defined as the zero fluctuation steady state point, which represents that the wind farm and the photovoltaic power station are both in a constant output state and do not disturb the grid. The positive half-axis region of the X-axis is defined as the wind power climbing region, which represents the positive increase of the wind power over time; the negative half-axis region of the X-axis is defined as the wind power sliding region, which represents the negative decrease of the wind power over time. Similarly, the positive half-axis region of the Y-axis is defined as the photovoltaic power climbing region, and the negative half-axis region of the Y-axis is defined as the photovoltaic power sliding region. By combining and mapping the wind power change rate and the photovoltaic power change rate calculated at the same time into a coordinate point in the wind-solar fluctuation rate phase plane, a real-time fluctuation state point is obtained.

[0064] In step S12, a coupled stable elliptical region that can stretch and contract in real time according to the operating state of the regional grid is defined in the wind-solar fluctuation rate phase plane.

[0065] In the real-time operation of the power system, the ability of the regional grid to absorb power fluctuations is not unlimited, and the regional grid is dynamically constrained by the frequency stability constraint and the rotational reserve capacity limit, so it is necessary to define a safe operating range in the wind-solar fluctuation rate phase plane without the intervention of the energy storage system. In order to define a safe operating range in the wind-solar fluctuation rate phase plane without the intervention of the energy storage system, a geometric boundary that can stretch and contract in real time according to the operating state of the regional grid, i.e., a coupled stable elliptical region, is constructed; the coupled stable elliptical region defines the maximum boundary within which the regional grid can suppress wind-solar fluctuations by relying on its own inertia and primary frequency modulation capability. The purpose of defining the coupled stable elliptical region is to map the complex grid stability constraints into a closed geometric figure in the wind-solar fluctuation rate phase plane, so that it is only necessary to verify the geometric position relationship to determine whether the current fluctuation is safe.

[0066] The regional power grid operation parameters are acquired from the power dispatch center in real time, and the regional power grid operation parameters include a frequency deviation allowable threshold and a current rotating reserve capacity. The frequency deviation allowable threshold defines a safety red line of power grid frequency fluctuation, and the current rotating reserve capacity determines the peak capacity of the power grid under sudden power gap. By using a power grid frequency response model, the maximum tolerance limit of the regional power grid to the wind power change rate before triggering the action of the low-frequency load shedding device itself is derived, which is recorded as a wind power maximum instantaneous acceptance slope, and the maximum tolerance limit of the regional power grid to the photovoltaic power change rate is recorded as a photovoltaic maximum instantaneous acceptance slope. The wind power maximum instantaneous acceptance slope and the photovoltaic maximum instantaneous acceptance slope are combined to obtain a maximum instantaneous slope set.

[0067] A coupling stability ellipse region is constructed in a wind-solar fluctuation rate phase plane through the maximum instantaneous slope set. The coupling stability ellipse region includes a long semi-axis and a short semi-axis in a geometric structure. The wind power maximum instantaneous acceptance slope is set as a long semi-axis parameter A, the photovoltaic maximum instantaneous acceptance slope is set as a short semi-axis parameter B, and a boundary equation of the coupling stability ellipse region is set as: wherein X and Y correspond to X-axis coordinate values and Y-axis coordinate values of the wind-solar fluctuation rate phase plane, the boundary equation anchors an abstract geometric boundary to specific physical limits, when the photovoltaic power change rate is zero, the boundary equation degenerates into , which ensures that in a single energy fluctuation scenario, the X-axis intercept of the wind-solar fluctuation rate phase plane strictly corresponds to the independent limit tolerance capacity of the regional power grid to wind power; similarly, when the wind power change rate is zero, the boundary equation degenerates into , ensures that the Y-axis intercept strictly corresponds to the independent limit tolerance of the regional power grid to photovoltaic. Prevents the setting of the safe region range from deviating from the actual physical constraints of the power grid. The reason for using the quadratic form in the boundary equation is to simulate the nonlinear coupling effect of the frequency impact of multiple source disturbances on the power grid. In the power system, the frequency regulation resources consumed by the simultaneous fluctuations of wind power and photovoltaic, such as rotating reserve capacity, have energy superposition characteristics. The quadratic form defines a smooth nonlinear trade-off relationship, that is, when the wind power variation rate increases, in order to maintain the system in a critical stable state, that is, the boundary equation is equal to 1, the allowed photovoltaic power variation rate decays at a nonlinear rate. The form of the boundary equation accurately depicts the dynamic sharing mechanism of the limited grid regulation capability between the two fluctuation sources, and defines a joint safe domain that conforms to the law of conservation of energy; the reason why the shape of the coupled stable elliptical region is elliptical rather than other shapes is that wind farms are usually connected to high-voltage transmission grids, while photovoltaic power stations are usually connected to distribution grids or collection stations. The regional power grid has different tolerance to power fluctuations of different access points and different electrical characteristics, usually manifested as the maximum instantaneous acceptance slope of wind power not equal to the maximum instantaneous acceptance slope of photovoltaic. The elliptical shape can accurately depict the asymmetric tolerance of the regional power grid to wind and photovoltaic fluctuations, avoiding waste or insufficient protection of regulation resources caused by using other shapes to form the boundary. Among them, A and B are not fixed constants, but variables that change dynamically with the operating parameters of the regional power grid. If the current rotating reserve capacity decreases or the frequency deviation tolerance threshold tightens, A and B will decrease synchronously, causing the coupled stable elliptical region to contract towards the origin, meaning that the tolerance to fluctuations decreases; conversely, when the grid inertia is sufficient, the coupled stable elliptical region expands. This dynamic stretching realizes real-time quantification of the safety margin of the power grid.

[0068] Step S13, qualitative classification is performed in combination with the wind and light fluctuation rate phase plane and the coupled stable elliptical region to obtain a multi-source coupling state label.

[0069] In order to realize real-time quantification of multi-source energy fluctuation safety, that is, to identify whether the power fluctuation represented by the real-time fluctuation state point in the wind and light fluctuation rate phase plane is a safe fluctuation that can be accepted by the regional power grid or an out-of-limit fluctuation that requires external regulation resources to intervene, a logical association between the real-time fluctuation state point and the coupled stable elliptical region is established. The purpose is to qualitatively classify the real-time fluctuation state point and distinguish whether the wind power variation rate and the photovoltaic power variation rate are in a malignant superposition state or a benign complementary state, thereby providing a basis for subsequent discrimination.

[0070] Specifically, the elliptical boundary discriminant value L of the real-time fluctuation state point relative to the coupled stable elliptical region is calculated. The elliptical boundary discriminant value is obtained by constructing a formula with the real-time fluctuation state point, the long semi-axis parameter A and the short semi-axis parameter B. The elliptical boundary discriminant value formula is: The multi-layer determination is performed on the ellipse boundary determination value. The first layer determination is that if the ellipse boundary determination value is less than or equal to 1, it is determined that the real-time fluctuation state point is located inside or on the boundary of the coupled stable ellipse region, which indicates that the current wind-solar combined fluctuation is within the safe range of the regional power grid that can be independently accommodated, and the energy storage system does not need to intervene, avoiding frequent responses to small and harmless power fluctuations, preventing invalid actions and life loss of the energy storage resources, and generating a silent state label. If the ellipse boundary determination value is greater than 1, it is determined that the real-time fluctuation state point is located outside the coupled stable ellipse region, which indicates that the current wind-solar combined fluctuation exceeds the instantaneous accommodation capacity of the regional power grid, which poses a potential threat to the stability of the power grid frequency. At this time, it is determined to be an out-of-limit state, and the second layer determination needs to be performed in combination with the quadrant position of the real-time fluctuation state point. Figure 2 The second layer determination is that if the real-time fluctuation state point is located in the first quadrant or the third quadrant of the wind-solar fluctuation rate phase plane, it indicates that the fluctuations of wind power and photovoltaic power are in the same direction, and the power impact generated by the two is physically superimposed in the same direction, forming a resonance effect, which causes the absolute value of the total power change rate to increase dramatically, and produces a vicious impact on the power grid frequency. A high forced state label is generated, as shown in FIG. 1, and the first quadrant and the third quadrant are defined as the same direction superposition fluctuation area; if the real-time fluctuation state point is located in the second quadrant or the fourth quadrant of the wind-solar fluctuation rate phase plane, it indicates that the fluctuations of wind power and photovoltaic power are in opposite directions, showing a complementary characteristic of one increasing and one decreasing, and the fluctuations of the two are physically partially offset, so that the total power change rate after synthesis is less than the algebraic sum of the single energy fluctuation rate. A weak compensation state label is generated, and the second quadrant and the fourth quadrant are defined as the complementary offset fluctuation area. The silent state label, the high forced state label and the weak compensation state label are combined into a multi-source coupled state label.

[0071] Step S10 solves the technical problems that the output power of the wind-solar-storage multi-energy complementary power station has nonlinear time-varying characteristics due to the randomness of wind energy and solar energy, and it is difficult to accurately capture the physical nature of the microscopic impact on the stability of the power grid frequency only by the size of the power storage, and it is difficult to distinguish between benign complementary fluctuations and malignant resonance fluctuations, realizes real-time quantitative determination of multi-source energy fluctuation safety and accurate classification of energy fluctuation modes. Among them, the wind-solar fluctuation rate phase plane converts the dynamic change of the time dimension into the geometric relationship of the space dimension, focusing on the change trend and rate of power; the coupled stable ellipse region establishes the physical boundary of safe operation; and the multi-source coupled state label provides a qualitative discrimination basis for distinguishing between strong forced state, weak compensation state and silent state for subsequent control strategies.

[0072] Step S20, obtaining the internal state data of the energy storage system to construct an energy storage response performance plane, calculating the dynamic dead zone threshold parameter of automatic adjustment according to the multi-source coupling state label and the energy storage response performance plane, and constructing a dynamic breathing hexagon boundary in the energy storage response performance plane according to the dynamic dead zone threshold parameter.

[0073] Further, step S20 comprises:

[0074] Step S21, obtaining the internal state data of the energy storage system to construct an energy storage response performance plane, and calculating the dynamic dead zone threshold parameter of automatic adjustment according to the multi-source coupling state label and the energy storage response performance plane.

[0075] The conventional energy storage control strategy often adopts a fixed action dead zone, which cannot balance the regional power grid stability control demand and the dynamic balance of energy storage battery life protection. In order to solve the technical pain point that the energy storage system often sacrifices the battery life when pursuing the stability control effect, an analysis space that can integrate the internal physical constraints of the battery and the external grid demand, i.e. the energy storage response performance plane, is constructed; the pure power instruction tracking problem is converted into a geometric area judgment problem based on the battery health state, so as to introduce the flexible game mechanism of the battery physical health constraint and the grid demand at the source of the control instruction generation.

[0076] The internal state data of the energy storage system is obtained by the energy storage battery management system of the energy storage system for suppressing the power fluctuation of the wind farm and the photovoltaic power station in the wind-solar-storage multi-energy complementary power station, the internal state data of the energy storage system includes the state of charge of the energy storage system, the real-time temperature of the energy storage battery and the health degree of the energy storage battery; wherein the state of charge of the energy storage system represents the ratio of the current remaining capacity to the rated capacity of the energy storage battery, which determines the physical capacity boundary of the energy storage system that can charge or discharge at the current time; the real-time temperature of the energy storage battery represents the instantaneous thermodynamic temperature inside the battery module, and the health degree of the energy storage battery represents the ratio of the current maximum available capacity to the rated capacity of the energy storage battery, which represents the aging degree of the battery. At the same time, the real-time load data of the regional power grid is obtained from the power dispatching center, the real-time load data of the regional power grid represents the total active power consumed by all electrical equipment in the power supply area accessed by the multi-energy complementary power station at the current time; the real-time load data of the regional power grid is combined with the total power of the wind farm grid connection point and the total power of the photovoltaic power station grid connection point to calculate the power deviation demand of the grid, the power deviation demand of the grid is the real-time load data of the regional power grid minus the sum of the total power of the wind farm grid connection point and the total power of the photovoltaic power station grid connection point; represents the unbalanced physical quantity between the source and the load at the current time, the purpose is to serve as the original reference signal of the power regulation of the energy storage system, quantifies the size and direction of the energy gap that needs to be filled by the energy storage system, the positive value represents the lack of discharge, and the negative value represents the surplus of charging.

[0077] A storage response performance plane is established based on the state of charge of the energy storage system and the power deviation demand of the power grid, the state of charge of the energy storage system is set as the horizontal axis, the power deviation demand of the power grid is set as the vertical axis, and any coordinate point in the storage response performance plane represents the matching state of the physical capability of the energy storage system at the current sampling time and the external power balance demand. After the storage response performance plane is constructed, a dynamic dead zone threshold parameter D is calculated, which represents the maximum power amplitude boundary of the energy storage system not responding to the power deviation demand of the power grid; the purpose is to replace the fixed action dead zone in the prior art and realize the real-time elastic expansion of the action dead zone range. The calculation formula of the dynamic dead zone threshold parameter is: , wherein, represents the minimum regulation dead zone value required to meet the regional power grid grid-connected dispatching protocol, the purpose is to ensure that the bottom line of any regulation strategy does not violate the grid-connected regulations of the power grid; the dynamic dead zone threshold parameter is preset according to the primary frequency regulation dead zone standard of the regional power grid dispatching protocol, for example, it is set to 2% of the rated capacity of the energy storage system, is a coupling state correction coefficient, which is a dimensionless proportional factor representing the influence degree of the fluctuation coupling characteristics between wind energy and solar energy on the regulation demand of the energy storage system, and is hierarchically preset according to the multi-source coupling state label, for example, it is set to 0.5 when the multi-source coupling state label is a high forced state label, it is set to 1.5 when the multi-source coupling state label is a weak compensation state label, and it is set to 2.0 when the multi-source coupling state label is a silent state label. is a health state correction coefficient, which is a dimensionless proportional factor representing the influence degree of the physical health state of the energy storage battery on the charge and discharge bearing capacity. It is preset according to the life degradation model of the energy storage battery, for example, it is set to 1.0 in the standard state of the battery, and it is set to 2.0 in the high temperature or low health state. The reference dead zone constant is introduced in the calculation formula of the dynamic dead zone threshold parameter in order to anchor the basic dispatching rules of the power grid; the coupling state correction coefficient is introduced in order for the energy storage system to identify whether wind and light are complementary, thereby avoiding invalid regulation when wind and light are complementary; the health state correction coefficient is introduced in order to prevent the life of the sick battery from being overdrafted in order to smooth fluctuations. The three-dimensional unity of regulation constraints, source-load interaction and equipment protection is realized.

[0078] When the multi-source coupling state label is a high forced state label, the coupling state correction coefficient is set to a value less than 1, because the high forced state label means that the wind power and the photovoltaic power are in a same-direction superposition resonance mode, and the impact on the frequency of the regional power grid is great. By reducing the coupling state correction coefficient, the dynamic dead zone threshold parameter is forced to be reduced, the action threshold of the energy storage system is reduced, and the energy storage system is forced to intervene in regulation quickly and sensitively to prioritize the frequency stability of the regional power grid; when the multi-source coupling state label is a weak compensation state label, the coupling state correction coefficient is set to a value greater than 1, because the weak compensation state label means that the wind power and the photovoltaic power are in a complementary mode of one increase and one decrease, and the natural mutual aid of the two can offset part of the power fluctuation. By increasing the coupling state correction coefficient, the dynamic dead zone threshold parameter is artificially enlarged, the action threshold of the energy storage system is increased, and residual fluctuations are filtered out to prevent the energy storage system from performing small charging and discharging cycles at unnecessary times. When the multi-source coupling state label is a silent state label, the coupling state correction coefficient is set to a specific value greater than the value corresponding to the weak compensation state label, because the silent state label means that the current power fluctuation is within the coupling stable ellipse region, that is, the regional power grid can be consumed by relying on its own inertia without external regulation. By increasing the coupling state correction coefficient, the dynamic dead zone threshold parameter is increased, so that the dynamic dead zone threshold parameter covers the current power deviation requirement of the power grid, thereby keeping the energy storage system in a zero power output state, minimizing the number of invalid cycles of the energy storage battery, and prolonging the service life of the battery. The adjustment of the health state correction coefficient is as follows: when the real-time temperature of the energy storage battery is greater than the rated reference temperature value marked on the nameplate of the energy storage battery, or the health degree of the energy storage battery is less than the standard health degree benchmark value marked on the nameplate, the health state correction coefficient value is increased, and the increased health state correction coefficient value is, for example, in the range of 1.8-2.5. By simulating the self-protection mechanism of the organism, when the energy storage battery is in a sub-health state of high temperature or serious aging, the ability of the battery to withstand current impact decreases. As the real-time temperature of the energy storage battery increases or the health degree of the energy storage battery decreases, the health state correction coefficient automatically increases, thereby increasing the dynamic dead zone threshold parameter, avoiding forcing the aged battery to bear a high-intensity regulation task, preventing the battery from overheating or accelerating the decline, and achieving adaptive protection throughout the life cycle.

[0079] In step S22, a dynamic breathing hexagon boundary is constructed in the energy storage response performance plane according to the dynamic dead zone threshold parameter.

[0080] In order to solve the capacity limit problem of the energy storage system for suppressing the power fluctuation of the wind farm and the photovoltaic power station in the wind-solar-storage multi-energy complementary power station under a single power threshold control, which is difficult to prevent the over-discharge of extremely low power or the over-charge of full power; therefore, the dynamic dead zone threshold parameter is mapped in the plane geometry space, and the physical boundary limit of the state of charge of the energy storage system is fused; a closed geometric figure, i.e. a dynamic breathing hexagon boundary, is constructed in the energy storage response performance plane; the purpose is to geometrically fuse the power amplitude constraint determined by the dynamic dead zone threshold parameter and the physical boundary constraint determined by the state of charge of the energy storage system, and form a safe operation envelope surface.

[0081] Specifically, six key vertices are determined in the energy storage response performance plane, and the six key vertices are sequentially connected to form a closed dynamic breathing hexagon boundary. The six key vertices include a left vertex , a left upper vertex , a right upper vertex , a right vertex , a right lower vertex and a left lower vertex . The physical limits of the state of charge allowed to operate of the energy storage system are read from the battery nameplate, including the minimum allowed state of charge and the maximum allowed state of charge ; wherein the minimum allowed state of charge is the lowest power percentage of the energy storage battery before irreversible chemical damage occurs, which is set according to the discharge depth corresponding to the battery nameplate provided by the battery manufacturer, and an example is 10%, and the maximum allowed state of charge is the highest power percentage of the energy storage battery before the risk of overpressure gasification occurs, which is set according to the capacity corresponding to the charging cutoff voltage corresponding to the battery nameplate provided by the battery manufacturer, and an example is 90%. The left vertex defines the physical capacity lower limit of the energy storage system for discharging operation, which represents that when the state of charge of the energy storage system reaches the minimum allowed state of charge, the allowed output power is forced to converge to zero, the purpose is to stop all discharging behaviors to protect the battery, and the coordinates in the energy storage response performance plane are , the line between the left upper vertex and the right upper vertex constitutes a discharging response starting boundary, the height of the discharging response starting boundary is set by the dynamic dead zone threshold parameter, the coordinates of the left upper vertex are , the coordinates of the right upper vertex are , wherein The capacity buffer margin represents the length of the power interval reserved for power smoothing transition, which is set according to the soft landing requirement of the energy storage system power control, and is exemplarily set to 5%. The purpose is to prevent the occurrence of step mutations by reserving a power interval for transition. The discharge response start boundary represents that when the positive grid power deviation demand is greater than the discharge response start boundary, it is determined that the current power gap has adjustment necessity, otherwise it remains inactive. The right vertex defines the upper limit of the physical capacity of the energy storage system for charging operation, which represents that when the state of charge of the energy storage system reaches the maximum allowed state of charge, the input power is forced to converge to zero, and the coordinates in the energy storage response performance plane are The line between the right lower vertex and the left lower vertex constitutes the charging response start boundary, and the depth of the charging response start boundary is set by the dynamic dead zone threshold parameter. Only when the absolute value of the negative grid power deviation demand is greater than the absolute value of the charging response start boundary, it is determined that the current power surplus has adjustment necessity, otherwise it remains inactive. The coordinates of the right lower vertex are The coordinates of the left lower vertex are .

[0082] The closed figure is formed by sequentially connecting , , , , and , that is, the dynamic breathing hexagon boundary. The area surrounded by the dynamic breathing hexagon boundary is defined as the energy storage silent zone, which is represented as: when the real-time operating point representing the current state falls within the energy storage silent zone, it indicates that the current grid power deviation demand has not broken through the composite control constraint boundary composed of the energy storage battery health, the multi-source coupling state label and the state of charge of the energy storage system. The energy storage system remains in a zero power output state and does not generate adjustment instructions. The real-time operating point represents the unique coordinate point in the energy storage response performance plane, which is mapped by taking the state of charge value of the energy storage system as the horizontal coordinate value and the grid power deviation demand value as the vertical coordinate value. The purpose is to quantify the deviation degree of the current power balance state relative to the safety envelope.

[0083] The composite control constraint boundary is defined as the multi-dimensional limit condition set represented by the dynamic breathing hexagon boundary, which integrates the device physical safety and the grid fluctuation characteristics. The dynamic breathing hexagon boundary adopts a hexagonal structure rather than other structures because other structures, such as rectangles, still allow power throughput when the battery power is close to the left vertex or the right vertex, which may cause safety hazards of overcharging or overdischarging of the battery.

[0084] In step S23, the dynamic breathing hexagon boundary is calculated to obtain the penetration depth, and the energy storage effective action instruction representing the control signal is generated according to the penetration depth.

[0085] After the dynamic breathing hexagon boundary is constructed, geometric positioning and out-of-limit analysis are performed; the problem that simple binary logic judgment can only determine whether the energy storage system is in action but cannot determine the specific amplitude of the action, and directly using the original power deviation demand of the power grid as the instruction ignores the dead zone filtering effect and causes the control instruction to have a step mutation is solved; therefore, the penetration depth concept in geometry is introduced; the effective working distance of the real-time operating point exceeding the energy storage silent zone is quantified, thereby generating an energy storage effective action instruction that is smooth and takes into account the battery life.

[0086] Specifically, the positional relationship between the real-time operating point and the dynamic breathing hexagon boundary is judged; if the real-time operating point is located inside or on the dynamic breathing hexagon boundary, i.e., falls into the energy storage silent zone, the penetration depth is determined to be zero; at this time, the energy storage system remains inaction, and the energy storage effective action instruction output is zero; if the real-time operating point is located outside the dynamic breathing hexagon boundary, the penetration depth needs to be calculated. The penetration depth is the Euclidean distance from the real-time operating point to the line segment on the dynamic breathing hexagon boundary that is closest to the real-time operating point; the specific calculation process is as follows: for the discharging condition, i.e., the power deviation demand of the power grid is greater than zero, the real-time operating point to the discharging response starting boundary is calculated; then the penetration depth is equal to the power deviation demand minus the ordinate value of the discharging response starting boundary at the current state of charge of the energy storage system. For the charging condition, i.e., the power deviation demand of the power grid is less than zero, the vertical distance of the real-time operating point to the charging response starting boundary in the vertical axis direction is calculated; then the penetration depth is equal to the absolute value of the power deviation demand minus the absolute value of the ordinate value of the charging response starting boundary at the current state of charge of the energy storage system; for the limit capacity condition in which the state of charge of the energy storage system enters the capacity buffer marginal interval, at this time, the discharging response starting boundary or the charging response starting boundary assumes a slope shape, and the calculation of the penetration depth is based on a slope equation to ensure that as the state of charge of the energy storage system approaches the minimum allowable state of charge or the maximum allowable state of charge, the calculated penetration depth automatically decreases and converges to zero. The capacity buffer marginal interval is an electric quantity interval defined by the capacity buffer marginal, i.e., the interval is or The slope equation is a linear decay function constructed by using the two-point straight line equation principle according to the geometric coordinate points of the left vertex C1 and the left upper vertex C2, and the geometric coordinate points of the right vertex C4 and the right lower vertex C5.

[0087] Through the penetration depth, the energy storage effective action instruction E is generated, which is the active power target value output or absorbed by the energy storage system after being filtered by the dynamic dead zone threshold parameter. The calculation formula of the energy storage effective action instruction E is as follows: wherein, represents the power deviation demand of the power grid, ​​A sign function representing the grid power deviation demand, used to determine the charging and discharging direction of the energy storage system, taking positive and negative 1, positive value driving discharge, negative value driving charge; G is a proportional constant for converting geometric distance into power physical quantity, which is normalized according to the rated power of the energy storage system; F represents the penetration depth, is a nonlinear response index, which is expressed as a power factor indicating the sensitivity of the adjusted energy storage system to the change in penetration depth, which is set according to the dynamic damping response characteristic of the energy storage system, which represents the inherent inertia response capability of the energy storage system to suppress overshoot oscillation, and an exemplary value is 1.5. Finally, the energy storage effective action instruction is issued as the final control signal to the energy storage converter of the energy storage system, driving the energy storage converter to output or absorb the corresponding active power, and realizing the suppression of wind and light fluctuations.

[0088] Step S20 solves the technical problems that the traditional energy storage control strategy cannot balance the regional grid stability control demand and the energy storage battery life protection due to the fixed action dead zone, and lacks geometric hard constraints on the physical capacity boundary of the battery in the extremely low or full charge state, resulting in overcharging, overdischarging or unnecessary frequent action of the battery, by constructing an energy storage response performance plane, calculating a dynamic dead zone threshold parameter, constructing a dynamic breathing hexagon boundary, and calculating a penetration depth. The energy storage response performance plane converts the power instruction tracking problem into a geometric region determination problem; the dynamic dead zone threshold parameter realizes real-time elastic expansion of the action dead zone range; the dynamic breathing hexagon boundary forms a visual safe operation envelope surface; and the penetration depth generates an energy storage effective action instruction that takes into account the life and stability control.

[0089] Step S30 uses the energy storage effective action instruction as a driving source to construct a virtual energy gravity potential field, and performs analysis on the virtual energy gravity potential field to obtain a final power distribution scheme.

[0090] Further, step S30 includes:

[0091] Step S31 uses the energy storage effective action instruction as a driving source to construct a virtual energy gravity potential field.

[0092] In order to solve the control problems of multi-objective optimization scheduling calculation lag and difficulty in coordinating economy and stability, a virtual energy gravity potential field that can simulate the physical process of natural energy flow is constructed using the energy storage effective action instruction as a driving source; the purpose of constructing the virtual energy gravity potential field is to use the physical principle of potential energy driving fluid to convert the complex power distribution optimization problem into a network flow calculation problem driven by potential energy difference, so as to realize automatic optimization and distribution of energy.

[0093] The virtual energy gravity potential field is a multi-dimensional topological network space based on a physical analogy method, which is composed of independent physical nodes representing core physical subjects and virtual energy transmission pipelines representing electrical connections. The flow direction and size of energy only depend on the virtual potential height difference between nodes and the nonlinear flow resistance characteristics of the pipeline. Specifically, an actual electrical one-line diagram of a wind-solar-storage multi-energy complementary power station is obtained. The actual electrical one-line diagram is a topological structure diagram describing the electrical connection relationship and power transmission path between each core physical subject in the wind-solar-storage multi-energy complementary power station. The core physical subjects in the wind-solar-storage multi-energy complementary power station are one-to-one mapped to independent physical nodes in the virtual energy gravity potential field. The core physical subjects include a regional power grid, a wind farm, a photovoltaic power station, an energy storage system, and a load. The regional power grid is an external power system that exchanges power with the wind-solar-storage multi-energy complementary power station through a common connection point. In the actual electrical one-line diagram, it is represented as the high-voltage grid connection port of the power station. The wind farm is a collection of power generation units in the wind-solar-storage multi-energy complementary power station that convert wind energy into electrical energy using wind turbines. In the actual electrical one-line diagram, it is represented as a random power source node connected to the station's AC bus. The photovoltaic power station is a collection of power generation units in the wind-solar-storage multi-energy complementary power station that convert solar energy into electrical energy using photovoltaic modules. In the actual electrical one-line diagram, it is represented as an intermittent power source node connected to the station's AC bus or DC bus. The energy storage system is the energy storage system described in step S21 for the wind-solar-storage multi-energy complementary power station to smooth the power fluctuations of the wind farm and the photovoltaic power station. In the actual electrical one-line diagram, it is represented as an adjustable node with bidirectional power throughput capability. The load is a collection of local electrical equipment within the power supply range of the wind-solar-storage multi-energy complementary power station. In the actual electrical one-line diagram, it is represented as a power sink node that simply consumes electrical energy.

[0094] For each independent physical node, the virtual potential height H is calculated. For the load, since the load is a one-way energy consumption point, the virtual potential height corresponding to the load is set to the lowest reference zero potential in the field , thereby forming a constant energy attraction center in the field. For the regional power grid, the virtual potential height is negatively related to the real-time electricity price J, and the calculation formula is: , where is the basic potential constant, representing the initial potential height of the regional power grid at zero price or reference price. The purpose is to ensure that the calculated virtual potential height always remains within a logically reasonable value range under all possible price fluctuations, avoiding calculation singularities. For example, it is set to 100; ​is a price sensitivity coefficient, representing the weight factor of the response degree of the virtual energy gravity potential field to economic factors, which is set according to the importance of the operation strategy of the wind-solar-storage multi-energy complementary power station to economic benefits. The greater the value, the more inclined to charge at low price and discharge at high price. For example, it is set to 20. The real-time electricity price represents the transaction price of each kilowatt-hour of electric energy at the current time issued by the power trading center. The reason for constructing the calculation formula of the virtual potential height and the real-time electricity price is to use the potential gradient driving mechanism in the physical field to simulate the price-oriented mechanism in the market economy. When the real-time electricity price rises, the virtual potential height of the regional power grid decreases, thereby driving the energy to flow into the regional power grid spontaneously. Without constructing a complex economic objective function, the economic benefits are maximized through the spontaneous evolution of the physical field. For wind farms and photovoltaic power stations, the virtual potential height is proportional to the short-term power prediction value of the wind farm and the photovoltaic power station, so as to ensure that clean energy is always in a high potential position and preferentially flows downstream. The short-term power prediction value represents the maximum theoretical output power of the wind farm or the photovoltaic power station in the future control period, for example, the next fifteen minutes, which is obtained by a prediction algorithm based on numerical weather prediction and historical operation data. For the energy storage system, the virtual potential height is composed of the basic potential and the instruction bias potential. The basic potential is determined by the state of charge of the energy storage system. The higher the remaining power, the higher the basic potential, which is consistent with the physical characteristics of the full battery tending to release energy outward. The instruction bias potential is directly converted from the effective action instruction of the energy storage; the formula is: wherein U represents the instruction bias potential, is a proportional factor for converting the power physical dimension into the potential height dimension, which is set to ensure that the effective action instruction of the energy storage has the highest priority in the virtual energy gravity potential field. For example, the potential driving weight coefficient is set to 2.0.

[0095] After the virtual potential energy height corresponding to each physical body is calculated, a virtual energy transmission pipeline is established between adjacent independent physical nodes according to the electrical connection relationship and power transmission path in the actual electrical single-line diagram. Specifically, a non-linear flow resistance characteristic is set for each virtual energy transmission pipeline, which is determined by the static transmission capacity limit and the device dynamic response time constant. The static transmission capacity limit represents the maximum current or power upper limit allowed by the physical conductor; the purpose is to simulate the overload protection mechanism of the physical line, and when the virtual energy flow value flowing through the virtual energy transmission pipeline approaches the static transmission capacity limit, the flow resistance increases exponentially to limit the flow. The device dynamic response time constant represents the length of time required for the physical device to receive an instruction and actually output power to reach the target value; the purpose is to distinguish the regulation rate characteristics of different devices. For energy storage systems with fast response speed, a small flow resistance reference value is set; for regional power grids with relatively slow response speed, a large flow resistance reference value is set. It is ensured that in the case of sudden power gap, energy is preferentially transmitted through the energy storage system channel with low flow resistance characteristics, realizing multi-time scale automatic coordination based on physical characteristics.

[0096] In step S32, the virtual energy gravity potential energy field is analyzed to obtain the final power distribution scheme.

[0097] In order to analyze the energy flow state in the virtual energy gravity potential energy field; solve the problem that the traditional multi-objective optimization algorithm needs to repeatedly solve differential algebraic equations when dealing with multi-variable coupling, which cannot meet the real-time requirement of millisecond-level response speed of power grid frequency stability control, and is easy to fall into local optimal solution, resulting in the problem that economy and stability are lost; therefore, each virtual energy transmission pipeline in the virtual energy gravity potential energy field is traversed, and the virtual potential energy height difference scanning and virtual energy flow rate analysis are performed; the purpose is to use the natural physical law of potential energy difference driving flow to automatically decode the multi-dimensional heterogeneous information of economy represented by the virtual potential energy height of the regional power grid, safety represented by the instruction bias potential, and physical constraints represented by the flow resistance characteristic into specific power setting values of wind, light and storage execution mechanisms, thereby completing the autonomous cooperative scheduling of the multi-source complementary system.

[0098] Specifically, each virtual energy transmission pipeline in the virtual energy gravity potential energy field is traversed according to a preset calculation period. The calculation period represents the shortest time interval required for performing a complete state collection, strategy operation and instruction issuance, which is set according to the response speed requirement of the regional power grid primary frequency modulation, and the purpose is to ensure that the rapid fluctuations of the frequency can be effectively captured and suppressed; for example, it is set to 10 milliseconds. For any virtual energy transmission pipeline composed of any two connected independent physical nodes, the virtual potential energy height difference is calculated . Exemplarily, taking the independent physical node M1 pointing to the independent physical node M2 as an example, the preset energy flow positive direction of the virtual energy transmission pipeline is that M1 points to M2, and the virtual potential energy height corresponding to M1 and M2 is respectively denoted as and , and the calculation formula of the virtual potential energy height difference is: If is greater than 0, it indicates that the actual energy flow direction is the same as the preset positive direction; if is equal to 0, it indicates that the virtual potential energy heights of the two independent physical nodes are balanced, and there is no energy flow; if is less than 0, it indicates that the actual energy flow direction is opposite to the preset positive direction.

[0099] After obtaining the virtual potential energy height difference, the nonlinear flow resistance characteristic value R of the virtual energy transmission pipeline is calculated, and the nonlinear flow resistance characteristic value is dynamically calculated according to the static transmission capacity limit and the device dynamic response time constant , and the calculation formula of the nonlinear flow resistance characteristic value is: , wherein is the basic flow resistance determined by the device dynamic response time constant, and the faster the response is, the smaller the basic flow resistance is; is the absolute value of the power flowing through the pipeline in the last calculation period, is a congestion penalty coefficient, which is an exponential factor representing the sensitivity of the adjusted flow resistance to the pipeline load rate, and the setting is based on the thermal stability limit characteristic of the physical line. In order to simulate the physical phenomenon that the line impedance increases exponentially when the flow approaches the limit, in order to prevent overloading and burning. Exemplarily, the value is 5.0. , which represents an exponential function with the natural constant e as the base number. The physical meaning of the calculation formula of the nonlinear flow resistance characteristic value is that when the pipeline flow approaches the capacity limit, that is, approaches , the exponential term increases sharply, resulting in a sharp increase in the nonlinear flow resistance characteristic value, thereby automatically limiting the further increase of the flow on the physical level, preventing the line from being overloaded. Finally, the virtual energy flow rate S of the virtual energy transmission pipeline is calculated, which represents the optimal power transmission value spontaneously sought at the current time considering the price incentive, safety constraint and line impedance, and is obtained through the nonlinear flow resistance characteristic value and the virtual potential energy height difference. The calculation formula of the virtual energy flow rate is: , and the construction of the calculation formula is based on the potential flow equation analogous to Ohm's law. The virtual energy flow rate of each virtual energy transmission pipeline is mapped back to the core physical subject of the wind-solar-storage multi-energy complementary power station to generate the final power distribution scheme, such as Figure 3As shown, specifically, for the virtual energy transmission pipeline between the independent physical nodes connected with the energy storage system and the load, the calculated virtual energy flow rate is directly used as the final execution power instruction of the energy storage system in the wind-solar-storage multi-energy complementary power station for smoothing the power fluctuation of the wind farm and the photovoltaic power station; for the virtual energy transmission pipeline between the independent physical nodes connected with the wind farm or the photovoltaic power station and the corresponding independent physical nodes of the load, if the calculated outflow virtual energy flow rate is less than the current short-term power prediction value of the wind farm or the photovoltaic power station, it is determined that the wind or light curtailment condition occurs, and the difference between the short-term power prediction value and the outflow virtual energy flow rate is defined as the power reduction demand. For the wind farm, according to the wind turbine power curve model, the power reduction demand is mapped to the pitch angle increment by using the inverse function, and the wind turbine blades are driven to feather to reduce the captured wind energy; for the photovoltaic power station, according to the characteristic curve of the photovoltaic array in the photovoltaic power station, the power reduction demand is mapped to the voltage bias by using the perturb and observe method logic, and the inverter DC side voltage is driven to deviate from the maximum power point voltage, so as to limit the output power of the photovoltaic array. If the outflow virtual energy flow rate is equal to the short-term power prediction value, the maximum power output is maintained. For the virtual energy transmission pipeline between the independent physical nodes connected with the regional power grid and the load; the virtual energy flow rate represents the gateway exchange power planning value between the wind-solar-storage multi-energy complementary power station and the regional power grid.

[0100] The power distribution scheme reduces the complex wind-solar-storage multi-energy complementary collaborative optimization problem to one-time algebraic operation, and the global optimal solution meeting all physical constraints and taking into account economy and safety can be obtained without iteration; the finally derived power distribution scheme realizes seamless integration of multiple time scales, solves the technical difficulties that a single energy control strategy is difficult to balance system stability and economy, and improves the overall operation efficiency and grid friendliness of the wind-solar-storage multi-energy complementary power station.

[0101] Step S30 solves the technical difficulties that the multi-objective optimization scheduling calculation is lagging, a single energy control strategy is difficult to balance system stability and economy in multiple time scales, and the traditional iterative solution method is easy to fall into local optimum, by constructing a virtual energy gravity potential field, setting a nonlinear flow resistance characteristic, and analyzing the virtual energy flow rate, and realizes reducing the complex wind-solar-storage multi-energy complementary collaborative optimization problem to millisecond-level network flow algebraic operation based on physical laws. The virtual energy gravity potential field simulates the natural flow process of energy between independent physical nodes; the nonlinear flow resistance characteristic determines the path priority of energy flow according to the static transmission capacity limit and the device dynamic response time constant; the virtual energy flow rate, as the final physical quantity derived by field theory calculation, is directly mapped to the final power distribution scheme of the wind-solar-storage execution mechanism.

[0102] Embodiment 2

[0103] The embodiment provides a wind-solar-storage multi-energy complementary power station cooperative operation system based on the embodiment 1, as shown in the figure, comprising: Figure 4

[0104] The multi-source fluctuation identification module is used for acquiring original power data, performing normalization processing on the original power data, obtaining a change rate data set, constructing a wind-solar fluctuation rate phase plane according to the change rate data set, defining a coupling stability elliptical region which can be stretched and contracted in real time according to the running state of a regional power grid in the wind-solar fluctuation rate phase plane, performing qualitative classification on the coupling stability elliptical region, and obtaining a multi-source coupling state label.

[0105] The energy storage boundary regulation module is used for acquiring internal state data of an energy storage system, constructing an energy storage response performance plane, calculating a dynamic dead zone threshold parameter of automatic adjustment according to the multi-source coupling state label and the energy storage response performance plane, and constructing a dynamic breathing hexagonal boundary in the energy storage response performance plane according to the dynamic dead zone threshold parameter.

[0106] The potential field cooperative scheduling module is used for constructing a virtual energy gravity potential field by using the effective energy storage action instruction as a driving source, performing analysis on the virtual energy gravity potential field, and obtaining a final power distribution scheme.

[0107] In the multi-source fluctuation identification module, the original power data is acquired, the original power data is normalized to obtain a change rate data set, a wind-solar fluctuation rate phase plane is constructed according to the change rate data set, a coupling stability elliptical region which can be stretched and contracted in real time according to the running state of a regional power grid is defined in the wind-solar fluctuation rate phase plane, qualitative classification is performed on the coupling stability elliptical region, and a multi-source coupling state label is obtained, comprising:

[0108] In step S11, the original power data is acquired, the original power data is normalized to obtain a change rate data set, and a wind-solar fluctuation rate phase plane is constructed according to the change rate data set.

[0109] In step S12, a coupling stability elliptical region which can be stretched and contracted in real time according to the running state of a regional power grid is defined in the wind-solar fluctuation rate phase plane.

[0110] In step S13, qualitative classification is performed on the wind-solar fluctuation rate phase plane and the coupling stability elliptical region, and a multi-source coupling state label is obtained.

[0111] In the energy storage boundary regulation module, the internal state data of the energy storage system is acquired to construct an energy storage response performance plane, a dynamic dead zone threshold parameter of automatic adjustment is calculated according to the multi-source coupling state label and the energy storage response performance plane, and a dynamic breathing hexagonal boundary is constructed in the energy storage response performance plane according to the dynamic dead zone threshold parameter.

[0112] ​Step S21, obtaining the internal state data of the energy storage system to construct an energy storage response performance plane, and calculating a dynamic dead zone threshold parameter of automatic adjustment according to the multi-source coupling state label and the energy storage response performance plane;

[0113] Step S22, constructing a dynamic breathing hexagon boundary in the energy storage response performance plane according to the dynamic dead zone threshold parameter;

[0114] Step S23, calculating the dynamic breathing hexagon boundary to obtain a penetration depth, and generating an energy storage effective action instruction of a control signal according to the penetration depth.

[0115] In the potential field cooperative scheduling module, the energy storage effective action instruction is used as a driving source to construct a virtual energy gravity potential field, and the virtual energy gravity potential field is executed to obtain a final power distribution scheme, including:

[0116] Step S31, using the energy storage effective action instruction as a driving source to construct a virtual energy gravity potential field;

[0117] Step S32, executing the virtual energy gravity potential field to obtain a final power distribution scheme.

[0118] The method and system of the present application can be implemented in many ways. For example, the method and system of the present application can be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the method is only for illustration, and the steps of the method of the present application are not limited to the above specifically described order, unless otherwise specifically stated.

[0119] In addition, the above technical solutions provided in the embodiments of the present application have not been described in detail, which are consistent with the implementation principles of the corresponding technical solutions in the prior art, so as not to be too verbose.

[0120] The specific embodiments described above further illustrate the purposes, technical solutions and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application, and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for coordinated operation of a wind-solar-storage multi-energy complementary power station, characterized in that, The method comprises: acquiring original power data, normalizing the original power data to obtain a rate of change data set, constructing a wind-solar fluctuation rate phase plane according to the rate of change data set, defining a coupled stability ellipse region that expands and contracts in real time according to the operating state of the regional power grid in the wind-solar fluctuation rate phase plane, qualitatively classifying the coupled stability ellipse region to obtain a multi-source coupling state label; acquiring internal state data of the energy storage system to construct an energy storage response performance plane, calculating a dynamic dead zone threshold parameter of automatic adjustment according to the multi-source coupling state label and the energy storage response performance plane, and constructing a dynamic breathing hexagon boundary in the energy storage response performance plane according to the dynamic dead zone threshold parameter; using the energy storage effective action instruction as a driving source to construct a virtual energy gravity potential field, and performing analysis on the virtual energy gravity potential field to obtain a final power distribution scheme; The multi-source coupling state label comprises: calculating an ellipse boundary discriminant value of a real-time fluctuation state point relative to the coupled stability ellipse region; performing multi-layer judgment on the ellipse boundary discriminant value, if the ellipse boundary discriminant value is less than or equal to 1, it is judged that the real-time fluctuation state point is located inside or on the boundary of the coupled stability ellipse region, indicating that the current wind-solar combined fluctuation is within the safety range of the regional power grid, and a silent state label is generated; if the ellipse boundary discriminant value is greater than 1, it is judged that the real-time fluctuation state point is located outside the coupled stability ellipse region, indicating that the current wind-solar combined fluctuation exceeds the instantaneous acceptance capacity of the regional power grid, and a secondary classification is performed according to the quadrant; if the real-time fluctuation state point is located in the first or third quadrant, it indicates that the fluctuation directions of the wind power and the photovoltaic power are the same, forming a resonance effect, and a high forced state label is generated, if the real-time fluctuation state point is located in the second or fourth quadrant, it indicates that the fluctuation directions of the wind power and the photovoltaic power are opposite, and a weak compensation state label is generated, and the silent state label, the high forced state label and the weak compensation state label are combined into the multi-source coupling state label; The method for obtaining the energy storage response performance plane comprises: the internal state data of the energy storage system comprises a state of charge of the energy storage system, a real-time temperature of the energy storage battery and a health degree of the energy storage battery; acquiring real-time load data of the regional power grid, and calculating the real-time load data of the regional power grid in combination with the total power at the wind farm grid connection point and the total power at the photovoltaic power station grid connection point to obtain a power deviation demand of the power grid; a two-dimensional coordinate system is constructed with the state of charge of the energy storage system as the horizontal axis and the power deviation demand of the power grid as the vertical axis, that is, the energy storage response performance plane, and any point on the energy storage response performance plane is defined as a real-time operating point; The virtual energy gravity potential field comprises: the virtual energy gravity potential field is a multi-dimensional topological network space based on a physical analogy method, which is composed of independent physical nodes representing core physical subjects and virtual energy transmission pipelines representing electrical connections; an actual electrical single-line diagram in the wind-solar-storage multi-energy complementary power station is acquired, the actual electrical single-line diagram is a topological structure diagram describing the electrical connection relationship and power transmission path between the core physical subjects in the wind-solar-storage multi-energy complementary power station; the core physical subjects in the wind-solar-storage multi-energy complementary power station are one-to-one mapped into independent physical nodes in the virtual energy gravity potential field; For each independent physical node, the virtual potential energy height is calculated respectively, and the virtual energy transmission pipeline is established between adjacent independent physical nodes according to the electrical connection relationship and the power transmission path in the actual electrical single-line diagram, and the nonlinear flow resistance characteristics are set for each virtual energy transmission pipeline. 2.The method for coordinated operation of wind-solar-storage multi-energy complementary power station according to claim 1, characterized in that, The wind-solar fluctuation rate phase plane comprises: The original power data comprises the total power of the wind power plant and the total power of the photovoltaic power station at each sampling time according to the preset sampling frequency; The original power data is processed to calculate the wind power rate of change and the photovoltaic power rate of change respectively, which can represent the inertia impact characteristics of the power grid; A two-dimensional rectangular coordinate system is established with the wind power rate of change as the X-axis and the photovoltaic power rate of change as the Y-axis, that is, a wind-solar fluctuation rate phase plane; The wind power rate of change and the photovoltaic power rate of change at the same time are mapped into a real-time fluctuation state point in the wind-solar fluctuation rate phase plane, wherein the origin of the wind-solar fluctuation rate phase plane is defined as a zero fluctuation steady state point, the first quadrant and the third quadrant are defined as a same direction superposition fluctuation area, and the second quadrant and the fourth quadrant are defined as a complementary offset fluctuation area. 3.The method of claim 2, wherein, The method for obtaining the coupled stable elliptical area comprises: The regional power grid operation parameters are obtained from the power dispatch center in real time, and the regional power grid operation parameters comprise a frequency deviation allowable threshold and a current rotating reserve capacity; The maximum tolerance limit of the regional power grid to the wind power rate of change, that is, the wind power maximum instantaneous acceptance slope, and the maximum tolerance limit of the regional power grid to the photovoltaic power rate of change, that is, the photovoltaic maximum instantaneous acceptance slope, are derived by using the regional power grid operation parameters under the premise that the low-frequency load shedding device of the regional power grid is not triggered. The wind power maximum instantaneous acceptance slope is set as a long semi-axis parameter, and the photovoltaic maximum instantaneous acceptance slope is set as a short semi-axis parameter to construct a closed elliptical geometric boundary, that is, a coupled stable elliptical area; wherein if the current rotating reserve capacity decreases, the coupled stable elliptical area shrinks towards the origin of the wind-solar fluctuation rate phase plane to reduce the tolerance to fluctuation, otherwise, the coupled stable elliptical area expands outward, and this dynamic stretching realizes real-time quantification of the safety margin of the power grid. 4.The method for coordinated operation of wind-solar-storage multi-energy complementary power station according to claim 3, characterized in that, The dynamic dead zone threshold parameter comprises: A reference dead zone constant is obtained according to the power grid dispatch protocol, and a coupling state correction coefficient is determined according to the multi-source coupling state, which is classified according to the multi-source coupling state; A health state correction coefficient is determined according to the real-time temperature of the energy storage battery and the health degree of the energy storage battery, and the reference dead zone constant, the coupling state correction coefficient and the health state correction coefficient are multiplied to obtain the dynamic dead zone threshold parameter which is stretched in real time according to the working condition. 5.The method for coordinated operation of wind-solar-storage multi-energy complementary power station according to claim 4, characterized in that, The method for obtaining the energy storage effective action instruction comprises: The position relationship between the real-time operating point and the dynamic respiratory hexagon boundary is judged, if the real-time operating point is located inside or on the dynamic respiratory hexagon boundary, the penetration depth is zero, if the real-time operating point is located outside the dynamic respiratory hexagon boundary, the penetration depth needs to be calculated, and the penetration depth is the Euclidean distance from the real-time operating point to the nearest line segment on the dynamic respiratory hexagon boundary. The penetration depth is combined with the power grid power deviation requirement to obtain an effective action instruction of the energy storage, so as to realize the suppression of wind and light fluctuations. 6.The method for coordinated operation of wind-solar-storage multi-energy complementary power station according to claim 5, characterized in that, The method for obtaining the power distribution scheme comprises: According to a preset calculation period, each virtual energy transmission pipeline in the virtual energy gravity potential field is traversed, and a virtual potential height difference of independent physical nodes at two ends of the virtual energy transmission pipeline is calculated; By using the virtual potential height difference and a nonlinear flow resistance characteristic, a virtual energy flow rate of each virtual energy transmission pipeline is obtained; The virtual energy flow rate of each virtual energy transmission pipeline is mapped back to a core physical subject of the wind-solar-storage multi-energy complementary power station to generate a final power distribution scheme.

7. A system for implementing the method of any one of claims 1-6, characterized in that, The system comprises: A multi-source fluctuation recognition module is configured to obtain original power data, perform normalization processing on the original power data to obtain a change rate data set, construct a wind and light fluctuation rate phase plane according to the change rate data set, define a coupled stability ellipse region that can be stretched and contracted in real time according to a regional power grid operation state in the wind and light fluctuation rate phase plane, perform qualitative classification on the coupled stability ellipse region, and obtain a multi-source coupling state label; An energy storage boundary regulation module is configured to obtain internal state data of an energy storage system to construct an energy storage response performance plane, calculate a dynamic dead zone threshold parameter of automatic adjustment according to the multi-source coupling state label and the energy storage response performance plane, and construct a dynamic breathing hexagon boundary in the energy storage response performance plane according to the dynamic dead zone threshold parameter; A potential field cooperative scheduling module is configured to use the effective action instruction of the energy storage as a driving source to construct a virtual energy gravity potential field, perform analysis on the virtual energy gravity potential field, and obtain a final power distribution scheme.

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