Wind-solar-storage integrated power grid energy distribution scheduling method

Abstract

The invention provides a wind-solar-storage integrated power grid energy distribution scheduling method, which relates to the technical field of power grid scheduling and comprises the following steps: collecting distribution information of wind-solar-storage equipment, and constructing a regional wind-solar-storage topological graph; collecting a historical wind and light storage operation data set; performing adjustment burden distribution analysis of the energy storage module according to the historical wind and light storage operation data set, and determining energy storage adjustment burden distribution; performing wind curtailment rate distribution analysis of wind power generation and light curtailment rate distribution analysis of photovoltaic power generation by using the historical wind and light storage operation data set to generate wind curtailment rate distribution and light curtailment rate distribution; and combining the energy storage adjustment burden distribution, the wind abandoning rate distribution and the light abandoning rate distribution to carry out wind and light storage balance scheduling optimization, and generating a power grid energy distribution decision. According to the method and the device, the technical problem of unbalanced distribution of energy storage resources among different regions in the prior art can be solved, the technical target of wind and light storage coordinated optimization scheduling is realized, and the technical effect of improving the operation balance of an energy storage system is achieved.

Description

Technical Field

[0001] This application relates to the technical field of power grid dispatching, and particularly to a method for dispatching the energy distribution of an integrated wind-solar-storage power grid. Background Art

[0002] In a multi-energy complementary system of wind, solar, and storage, the energy distribution and dispatching of the power grid usually rely on the independent management mechanism of local energy nodes or the regional dispatching strategy based on a decentralized control structure. To a certain extent, this method can achieve local energy balance and real-time control, but it lacks the system-level coordination ability across regions. In practical applications, wind farms and photovoltaic power stations usually perform adaptive adjustment according to the load demands of their respective access points, while energy storage systems are configured in specific regions to undertake the energy balance tasks of these regions. However, due to the differences in the fluctuation amplitudes of new energy and load characteristics in different regions, some energy storage modules are adjusted frequently and overloaded, resulting in a decline in operating efficiency and even the risk of overcharging and over-discharging. Other energy storage modules in other regions are in a low-load or idle state and cannot participate in the adjustment process, leading to an unbalanced distribution of the overall energy storage resources.

[0003] In summary, in the prior art, due to the lack of a system-level collaborative dispatching mechanism and global perception ability, there are technical problems such as the unbalanced distribution of energy storage resources between different regions, some energy storage modules being overloaded with adjustment loads while other modules are idle, further affecting the overall operating efficiency of the power grid and the new energy consumption ability of the integrated wind-solar-storage multi-energy complementary system. Summary of the Invention

[0004] The purpose of this application is to provide a method for dispatching the energy distribution of an integrated wind-solar-storage power grid to solve the technical problems in the prior art that due to the lack of a system-level collaborative dispatching mechanism and global perception ability, the energy storage resources are unbalanced between different regions, some energy storage modules are overloaded with adjustment loads while other modules are idle, further affecting the overall operating efficiency of the power grid and the new energy consumption ability of the integrated wind-solar-storage multi-energy complementary system.

[0005] In view of the above problems, this application provides a method for dispatching the energy distribution of an integrated wind-solar-storage power grid, including: collecting the distribution information of wind-solar-storage devices in a preset power grid area to construct a regional wind-solar-storage topology map; collecting a historical wind-solar-storage operation data set based on the regional wind-solar-storage topology map; performing an analysis of the adjustment burden distribution of energy storage modules with the historical wind-solar-storage operation data set, marking on the regional wind-solar-storage topology map to determine the energy storage adjustment burden distribution; performing an analysis of the curtailment rate distribution of wind power and an analysis of the curtailment rate distribution of photovoltaic power with the historical wind-solar-storage operation data set, marking on the regional wind-solar-storage topology map to generate the curtailment rate distribution and the curtailment rate distribution; combining the energy storage adjustment burden distribution, the curtailment rate distribution, and the curtailment rate distribution to perform an optimization of the balanced dispatching of wind-solar-storage to generate a power grid energy distribution decision.

[0006] Preferably, the integrated wind-solar-storage power grid energy distribution and scheduling method further includes: each node in the regional wind-solar-storage topology map represents an energy unit, and each edge represents the power grid connection relationship.

[0007] Preferably, the integrated wind-solar-storage power grid energy distribution and scheduling method further includes: based on the historical wind-solar-storage operation data set, statistically analyzing the occurrence frequency of the regulation behaviors of each energy storage module within the scheduling period and calculating the mean value to obtain the regulation frequency of each energy storage module; calculating the ratio of the regulation frequency of each energy storage module to the total sum of the regulation frequencies of each module, and marking it on the regional wind-solar-storage topology map to generate the energy storage regulation burden distribution.

[0008] Preferably, the integrated wind-solar-storage power grid energy distribution and scheduling method further includes: the occurrence frequency of the regulation behavior within the scheduling period is obtained by statistically counting the charge-discharge switching frequencies of each energy storage module.

[0009] Preferably, the integrated wind-solar-storage power grid energy distribution and scheduling method further includes: identifying the passive wind curtailment rate and the passive light curtailment rate based on the historical wind-solar-storage operation data set to generate a historical passive wind curtailment rate data sequence and a historical passive light curtailment rate data sequence; calculating the mean values of the wind curtailment rate and the light curtailment rate within the scheduling period based on the historical passive wind curtailment rate data sequence and the historical passive light curtailment rate data sequence to generate the mean wind curtailment rate data of each wind power generation module and the mean light curtailment rate data of each photovoltaic power generation module; marking the mean wind curtailment rate data of each wind power generation module and the mean light curtailment rate data of each photovoltaic power generation module on the regional wind-solar-storage topology map to generate the wind curtailment rate distribution and the light curtailment rate distribution.

[0010] Preferably, the passive wind curtailment rate and the passive light curtailment rate are the degrees of deviation from the theoretical available power generation caused by the artificial reduction of the power generation output of each wind power generation module and each photovoltaic power generation module after the external dispatching platform issues a power generation limit instruction.

[0011] Preferably, the integrated wind-solar-storage power grid energy distribution and scheduling method further includes: extracting data with a curtailment instruction identifier from the historical wind-solar-storage operation dataset, and identifying the curtailment adjustment parameters of each wind power generation module and the curtailment adjustment parameters of each photovoltaic power generation module; extracting the operation parameter difference and the wind power generation output difference of each wind power generation module under the same meteorological environment conditions from the historical wind-solar-storage operation dataset, and training the curtailment adjustment predictor of each wind power generation module; extracting the operation parameter difference and the photovoltaic power generation output difference of each photovoltaic power generation module under the same meteorological environment conditions from the historical wind-solar-storage operation dataset, and training the curtailment adjustment predictor of each photovoltaic power generation module; calling the curtailment adjustment predictor of each wind power generation module to analyze the curtailment adjustment parameters of each wind power generation module, and completing the identification of the passive curtailment rate of wind power; calling the curtailment adjustment predictor of each photovoltaic power generation module to analyze the curtailment adjustment parameters of each photovoltaic power generation module, and completing the identification of the passive curtailment rate of photovoltaic power.

[0012] Preferably, the integrated wind-solar-storage power grid energy distribution and scheduling method further includes: based on the energy storage regulation burden distribution, identifying high-frequency energy storage modules with a regulation burden higher than a preset burden index and low-frequency energy storage modules with a regulation burden lower than a preset burden index for energy storage scheduling optimization, and generating a first balanced optimization result; based on the curtailment rate distribution and the curtailment rate of photovoltaic power distribution, performing traditional energy scheduling for grid connection of each wind power generation module and each photovoltaic power generation module to minimize the curtailment rate of wind power and the curtailment rate of photovoltaic power, and generating a second balanced optimization result; using the first balanced optimization result and the second balanced optimization result to generate the power grid energy distribution decision.

[0013] Preferably, the integrated wind-solar-storage power grid energy distribution and scheduling method further includes: determining the set of high-regulation-demand energy units connected to the high-frequency energy storage module and the set of low-regulation-demand energy units connected to the low-frequency energy storage module; collecting the regulation demands of the set of high-regulation-demand energy units and the set of low-regulation-demand energy units, and performing regulation demand equalization processing by exchanging elements within the set to generate an equalization processing result; using the equalization processing result to execute the adjustment of the scheduling relationship between each energy storage module and the energy unit, and generating the first balanced optimization result.

[0014] Preferably, the integrated wind-solar-storage power grid energy distribution and scheduling method further includes: the grid connection to the power grid is the power system to which each wind power generation module and each photovoltaic power generation module are connected through a grid connection device.

[0015] The technical solution provided in this application has at least the following technical effects or advantages: by achieving the technical goal of coordinated optimization scheduling of wind-solar-storage based on the energy storage regulation burden distribution and the curtailment rate of wind and photovoltaic power, the technical effects of improving the operation balance of the energy storage system, reducing the curtailment loss of wind and photovoltaic power, and achieving the global optimal distribution of energy at the grid level are achieved.

[0016] The above description is only an overview of the technical solution of the present application. In order to better understand the technical means of the present application, it can be implemented according to the content of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the specific embodiments of the present application are given below. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easily understandable through the following description of the specification. Brief Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings described below are only exemplary, and for those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0018] Figure 1 It is a schematic flowchart of the method for energy distribution and dispatch of the integrated wind-solar-storage power grid of the present application.

[0019] Figure 2 It is a schematic flowchart of determining the distribution of energy storage regulation burden in the method for energy distribution and dispatch of the integrated wind-solar-storage power grid of the present application. Detailed Embodiments

[0020] By providing the method for energy distribution and dispatch of the integrated wind-solar-storage power grid, the present application solves the technical problems in the prior art that due to the lack of a system-level coordinated dispatch mechanism and global perception ability, the distribution of energy storage resources is unbalanced among different regions, some energy storage modules have too heavy regulation loads while other modules are idle, further affecting the overall operation efficiency of the power grid and the new energy consumption ability of the integrated wind-solar-storage multi-energy complementary system. The technical goal of realizing the coordinated and optimized dispatch of the integrated wind-solar-storage based on the distribution of energy storage regulation burden and the distribution of wind and light curtailment rates is achieved, and the technical effects of improving the operation balance of the energy storage system, reducing wind and light curtailment losses and realizing the global optimal distribution of energy at the power grid level are achieved.

[0021] Next, the technical solutions in the present application will be clearly and completely described with reference to the drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described here. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application. Additionally, it should be noted that for the sake of convenience of description, only the parts related to the present application are shown in the drawings rather than all of them.

[0022] Example 1, please refer to the attached Figure 1, this application provides a method for integrated wind-solar-storage power grid energy distribution and scheduling, which specifically includes the following steps: S1: Collect the distribution information of wind-solar-storage devices in a preset power grid area, and construct a regional wind-solar-storage topology map.

[0023] Specifically, the preset power grid area refers to a defined spatial range, such as a certain urban power distribution network, a rural micro-grid area, or a power generation area rich in wind and solar resources. Wind-solar-storage devices refer to wind and photovoltaic power generation facilities that can generate renewable electricity and electrochemical energy storage, battery systems, or other energy storage devices for energy regulation. Obtain the basic information such as the specific locations, types, capacities, access nodes, and electrical connection conditions of wind power generation devices, photovoltaic power generation devices, and energy storage systems within a specific power grid range, and form a graphical data structure according to the actual connection relationships of wind-solar-storage devices in the power grid to construct a regional wind-solar-storage topology map.

[0024] S2: Collect the historical wind-solar-storage operation data set based on the regional wind-solar-storage topology map.

[0025] Specifically, collect the historical wind-solar-storage operation data set based on the regional wind-solar-storage topology map, and extract the information related to each energy unit and its connection relationship in the regional wind-solar-storage topology map, including the historical output power of wind turbine generators, the irradiance response of photovoltaic arrays, the charge and discharge states of battery packs, the voltage fluctuations at each node of the power grid, the current flow direction, and operation control instructions, etc., and also include information such as dispatching response situations, curtailment records, and external meteorological environments.

[0026] S3: Perform an analysis of the distribution of the regulation burden of the energy storage module with the historical wind-solar-storage operation data set, mark it on the regional wind-solar-storage topology map, and determine the distribution of the energy storage regulation burden.

[0027] Specifically, the energy storage module refers to a unit with the function of electrical energy storage and release, such as a battery pack, a super capacitor, or other energy storage media, and the regulation burden represents the frequency and intensity of participating in the power balance of the power grid. Perform an analysis of the distribution of the regulation burden of the energy storage module with the historical wind-solar-storage operation data set, statistically calculate the energy regulation tasks borne by each energy storage module in different time periods, and thus judge the load level in the entire wind-solar-storage device. Mark the obtained regulation burden results of each energy storage module on the regional wind-solar-storage topology map, and attach them to the corresponding graphic nodes in the form of numerical labels or color grades, so as to visually display the differences in the distribution of regulation tasks among different energy storage modules in the regional wind-solar-storage topology map, determine the distribution of the energy storage regulation burden, and clearly identify the energy storage modules in the high-frequency charge and discharge state and the energy storage modules in the low-usage state, which is convenient for optimizing subsequent dispatching strategies.

[0028] S4: Perform the analysis of the curtailment rate distribution of wind power generation and the curtailment rate distribution of photovoltaic power generation with the historical operation dataset of wind-solar-storage, and mark them on the regional wind-solar-storage topology map to generate the curtailment rate distribution of wind power and the curtailment rate distribution of photovoltaic power.

[0029] Specifically, perform the analysis of the curtailment rate distribution of wind power generation and the curtailment rate distribution of photovoltaic power generation with the historical operation dataset of wind-solar-storage, identify and calculate the proportion of the total available power generation that cannot be achieved by each wind power generation module and photovoltaic power generation module due to factors such as curtailment instructions under specific conditions, and classify and analyze the proportion data to form a distribution result describing the severity of curtailment at different locations. The curtailment rate of wind power is the proportion of the electric energy that cannot be generated by the wind power generation module under the available wind energy conditions to the theoretically available power generation, and the curtailment rate of photovoltaic power is the proportion of the electric energy that cannot be output due to artificial restrictions by the photovoltaic power generation module under the available solar energy conditions. Subsequently, mark on the regional wind-solar-storage topology map, and attach the analyzed curtailment ratio data to the nodes of the corresponding wind power generation module and photovoltaic power generation module, so that the curtailment rate of wind power and the curtailment rate of photovoltaic power levels of each node are presented in the entire graphic structure.

[0030] S5: Combine the energy storage regulation burden distribution, the curtailment rate distribution of wind power, and the curtailment rate distribution of photovoltaic power to optimize the balanced scheduling of wind-solar-storage and generate a power grid energy allocation decision.

[0031] Specifically, combine the energy storage regulation burden distribution, the curtailment rate distribution of wind power, and the curtailment rate distribution of photovoltaic power to optimize the balanced scheduling of wind-solar-storage. Incorporate the regulation frequency of the energy storage system in different regions and the curtailment ratios of the wind power and photovoltaic systems in different locations into the scheduling analysis at the same time, and find the globally optimal energy allocation plan through a unified optimization model. The energy storage regulation burden distribution reflects the frequency of each energy storage module undertaking regulation tasks within a certain period. If some modules charge and discharge too frequently, it will accelerate their aging and reduce the system efficiency. The curtailment rate distribution of wind power refers to the spatial difference in the proportion of the unused wind energy generated by each power generation module due to curtailment in the wind power system, while the curtailment rate distribution of photovoltaic power reflects the location characteristics of the proportion of solar energy wasted by each photovoltaic module due to power curtailment in the system. Through scheduling optimization, reasonably transfer the regulation pressure of high-burden energy storage modules to low-burden modules, and give priority to absorbing the power generation capacity in regions with higher curtailment rates of wind power and photovoltaic power, so as to maximize the utilization rate of new energy and the use efficiency of energy storage in the overall system. Based on the comprehensive balance result, determine the power generation amount, charge and discharge amount, and power transmission direction of each time period and each node, so as to ensure the balance of power supply and demand, the optimal power generation efficiency, and the reasonable equipment load, and generate a power grid energy allocation decision.

[0032] Furthermore, this application also includes: Each node in the regional wind-solar-storage topology map represents an energy unit, and each edge represents the grid connection relationship.

[0033] Specifically, each node in the regional wind-solar-storage topology diagram represents an energy unit, and each drawn point represents an entity that can generate or regulate electric energy, including wind turbine generators, photovoltaic power generation arrays, energy storage modules, etc. The energy unit not only has the ability to output or absorb electric energy, but also has the scheduling value of interacting with other units in terms of energy. As the basic component of the topology diagram, nodes are used for abstract modeling, and then the relationships and functions of various devices are uniformly processed.

[0034] Each edge represents the grid connection relationship, representing the physical lines or electrical connections existing in the power system, including the power flow paths established by transmission lines, distribution lines, or electrical switch devices. It determines how electric energy is transmitted from one unit to another and also affects key factors such as power distribution, line load, and scheduling control.

[0035] Furthermore, as Figure 2 shown, this application further includes: based on the historical wind-solar-storage operation data set, statistically analyzing the occurrence frequency of the regulation behaviors of each energy storage module within the scheduling period and calculating the mean value to obtain the regulation frequency of each energy storage module; calculating the ratio of the regulation frequency of each energy storage module to the total sum of the regulation frequencies of all modules, and marking it on the regional wind-solar-storage topology diagram to generate the energy storage regulation burden distribution.

[0036] Specifically, the scheduling period refers to the basic control time period of the power grid operation, such as 15 minutes, 1 hour, or 1 day, etc. The regulation behavior is the active energy adjustment action performed by the wind-solar-storage equipment within the scheduling period, including switching from the charging state to the discharging state, or from the discharging state to the standby or charging state, etc. Based on the historical wind-solar-storage operation data set, statistically analyzing the occurrence frequency of the regulation behaviors of each energy storage module within the scheduling period and calculating the mean value, counting the number of charge-discharge switching behaviors that occur for each energy storage module in a complete scheduling period, and further calculating the average occurrence frequency within the scheduling period, which reflects the activity degree of the energy storage module participating in the power grid regulation, that is, the regulation frequency of each energy storage module. The higher the regulation frequency value, the more grid dynamic response tasks the energy storage module undertakes.

[0037] Dividing the regulation frequency of each energy storage module by the total sum of the regulation frequencies of all energy storage modules, calculating the ratio of the regulation frequency of each energy storage module to the total sum of the regulation frequencies of all modules, obtaining the relative regulation burden ratio of this module, which represents the proportion of the dynamic regulation task undertaken by each energy storage module in the entire wind-solar-storage system. Then, it is marked on the regional wind-solar-storage topology diagram to generate the energy storage regulation burden distribution. Table 1 is the record of the energy storage regulation frequency and burden distribution in the most recent wind-solar-storage operation cycle.

[0038] Table 1: Record of Energy Storage Regulation Frequency and Burden Distribution in the Most Recent Wind-Solar-Storage Operation Cycle Further, this application also includes: the occurrence frequency of adjustment actions within a scheduling period is obtained by counting the charge-discharge switching frequencies of each energy storage module.

[0039] Specifically, the occurrence frequency of adjustment actions within a scheduling period is obtained by counting the charge-discharge switching frequencies of each energy storage module. During the set scheduling time period, each energy storage module is monitored, and the number of times the energy storage module switches from the charging state to the discharging state or from the discharging state to the charging state is recorded, and this is used as the number of adjustment actions of the energy storage module within the scheduling period. The charge-discharge switching frequency reflects the working activity of the energy storage module. The higher the frequency, the more the energy storage module participates in the energy conversion process and the heavier its operating load; conversely, if the frequency is lower, it indicates that the energy storage module operates smoothly or has a low utilization rate within the scheduling period.

[0040] Further, this application also includes: identifying the passive wind curtailment rate and passive light curtailment rate based on the historical wind-solar-storage operation data set to generate a historical passive wind curtailment rate data sequence and a historical passive light curtailment rate data sequence; calculating the mean values of the wind curtailment rate and light curtailment rate within the period based on the historical passive wind curtailment rate data sequence and the historical passive light curtailment rate data sequence during the scheduling period to generate the mean wind curtailment rate data of each wind power generation module and the mean light curtailment rate data of each photovoltaic power generation module; marking the mean wind curtailment rate data of each wind power generation module and the mean light curtailment rate data of each photovoltaic power generation module on the regional wind-solar-storage topology map for marking to generate the wind curtailment rate distribution and the light curtailment rate distribution.

[0041] Specifically, identifying the passive wind curtailment rate and passive light curtailment rate based on the historical wind-solar-storage operation data set, using the historical operation records of wind power generation, photovoltaic power generation, and energy storage systems, combined with the curtailment instruction information issued by the scheduling platform and meteorological condition data, to judge the proportion of each power generation module that fails to generate all the theoretical power during the curtailment period due to non-equipment failures. Among them, the passive wind curtailment rate refers to the proportion of the power loss of the wind power generation module that fails to fully generate electricity due to scheduling or system restrictions when there is available wind speed, and the passive light curtailment rate refers to the power generation loss ratio of the photovoltaic power generation module caused by external interventions such as curtailment when there is sufficient solar radiation. Rely on the curtailment adjustment predictor to model the theoretical power generation during the curtailment period and then compare it with the actual power generation to obtain an accurate power curtailment ratio. Organize each identified passive power curtailment event into a continuous numerical data record in chronological order, and respectively construct a historical passive wind curtailment rate data sequence and a historical passive light curtailment rate data sequence, which reflect the power curtailment ratios encountered by the wind power generation module and the photovoltaic power generation module at each historical moment and can be used for subsequent trend analysis, mean value calculation, and strategy optimization.

[0042] Based on historical passive wind and photovoltaic curtailment rate data sequences within a dispatch cycle, the mean wind and photovoltaic curtailment rates are calculated. This means that the historical curtailment rate data sequences are averaged over the time dimension of grid dispatch, such as hourly or daily, to obtain the average curtailment level per unit time for each wind or photovoltaic module. This serves as a quantitative indicator of the impact of the dispatch strategy on these modules, reflecting their utilization efficiency and the risk of power generation restrictions. The calculated means are aggregated and the corresponding modules are identified to generate mean wind curtailment rate data for each wind module and mean photovoltaic curtailment rate data for each photovoltaic module, facilitating visualization and subsequent system dispatch evaluation.

[0043] The average wind curtailment rate data for each wind power module and the average solar curtailment rate data for each photovoltaic power module are labeled on each wind power node or photovoltaic node in the regional wind, solar, and energy storage topology diagram, forming attribute labels in the graph structure. The differences in curtailment levels of each module can be intuitively reflected in the topology structure through color, symbols, or text. After the labeling is completed on the regional wind, solar, and energy storage topology diagram, the curtailment levels of all wind power nodes and photovoltaic nodes are summarized to form a set of distribution information, generating a wind curtailment rate distribution and a solar curtailment rate distribution, which can be used for further scheduling optimization, power generation regulation, or resource allocation analysis.

[0044] Furthermore, the present application also includes: the passive wind curtailment rate and the passive solar curtailment rate are the degree of deviation from the theoretical power generation capacity due to the artificial reduction of power generation output by each wind power generation module and each photovoltaic power generation module after the external scheduling platform issues a power limit instruction.

[0045] Specifically, the passive wind and solar curtailment rates refer to the situation during grid operation where, due to power system security or stability considerations, the external dispatching platform issues power curtailment instructions, forcing wind or photovoltaic power generation modules to artificially reduce the amount of electricity they could generate. This deviation, compared to the theoretically capable power generation capacity given the prevailing natural resource conditions, results in a deviation. This deviation is the passive curtailment rate. The external dispatching platform is the grid's operational control center, responsible for deciding whether to implement power curtailment on certain renewable energy generation equipment based on factors such as the grid's power balance, transmission capacity, and load demand. Power curtailment instructions are control commands issued by the dispatching platform, requiring power generation terminals to adjust their operating status and reduce energy output.

[0046] In the wind power generation module, the pitch angle of the blade is adjusted or the operating point of the generator set is changed in response to the power curtailment instruction, so that it no longer tracks the maximum power point operation, but actively reduces the wind energy utilization rate. The pitch angle adjustment refers to changing the angle between the wind turbine blade and the wind direction to reduce the wind energy capture amount, thereby controlling the output power. At the same time, it is also possible to directly limit the power output through the generator output power instruction issued by the controller, so that the wind turbine still operates at a low output state under suitable wind speed conditions.

[0047] In the photovoltaic power generation module, power curtailment is achieved by adjusting the operating mode of the inverter. The inverter will enter the power-limited operation state, that is, artificially deviate from the maximum power point tracking, that is, deviate from the MPPT control, so that even if the solar irradiance is sufficient and the component temperature is appropriate, it will not output its theoretical maximum power. The inverter is the core device in the photovoltaic power generation module that converts direct current into alternating current, and its operating mode directly determines the output capacity of the photovoltaic power generation module. Therefore, controlling it is the main way of photovoltaic power curtailment.

[0048] Furthermore, the present application further includes: extracting data with power curtailment instruction identifiers from the historical wind-solar-storage operation dataset, and identifying the power curtailment adjustment parameters of each wind power generation module and the power curtailment adjustment parameters of each photovoltaic power generation module; extracting the operation parameter differences and wind power generation output differences of each wind power generation module under the same meteorological environment conditions from the historical wind-solar-storage operation dataset, and training the power curtailment adjustment predictors of each wind power generation module; extracting the operation parameter differences and photovoltaic power generation output differences of each photovoltaic power generation module under the same meteorological environment conditions from the historical wind-solar-storage operation dataset, and training the power curtailment adjustment predictors of each photovoltaic power generation module; calling the power curtailment adjustment predictors of each wind power generation module to analyze the power curtailment adjustment parameters of each wind power generation module, and completing the identification of the passive wind curtailment rate; calling the power curtailment adjustment predictors of each photovoltaic power generation module to analyze the power curtailment adjustment parameters of each photovoltaic power generation module, and completing the identification of the passive light curtailment rate.

[0049] Specifically, the power curtailment instruction identifier refers to an order issued by the dispatching center to control the system load or grid stability, requiring some power generation equipment to reduce the power output during certain periods, indicating that the equipment operation during the corresponding time period is completed under the power curtailment control state. Extracting the data with power curtailment instruction identifiers from the historical wind-solar-storage operation dataset and screening out the data generated during the period when the power curtailment command is issued by the dispatching platform can further identify the control behavior characteristics of the wind power or photovoltaic equipment during power curtailment.

[0050] Identify the curtailment adjustment parameters of each wind power generation module and each photovoltaic power generation module, and extract key variables from the data with curtailment identification to characterize the response modes of wind power and photovoltaic power during curtailment, such as the change of the fan blade pitch angle, the speed control command, the current reduction amplitude, or the load reduction rate of the photovoltaic inverter, the voltage control action, etc.

[0051] Extract the operation parameter differences and wind power generation output differences of each wind power generation module under the same meteorological environment conditions from the historical wind-solar-storage operation data set. Select time segments with basically the same meteorological conditions such as wind speed and wind direction, analyze the differences between the actual output and the expected output of the wind-solar-storage equipment, and use the difference data as input features to train a machine learning model to train the curtailment adjustment predictor of each wind power generation module, so that the curtailment adjustment predictor can predict the deviation of the wind power output according to future curtailment instructions. The curtailment adjustment predictor is an algorithm model used to infer how much electricity the equipment may output under the influence of curtailment, and is constructed by using regression neural networks, decision trees or ensemble learning methods.

[0052] Extract the operation parameter differences and photovoltaic power generation output differences of each photovoltaic power generation module under the same meteorological environment conditions from the historical wind-solar-storage operation data set, train the curtailment adjustment predictor of each photovoltaic power generation module, and on the basis of ensuring the consistency of conditions such as solar irradiance and ambient temperature, extract the deviation between the actual output and the theoretical output of the photovoltaic power generation module, and establish the curtailment adjustment predictor of each photovoltaic power generation module.

[0053] Call the curtailment adjustment predictor of each wind power generation module to analyze the curtailment adjustment parameters of each wind power generation module, evaluate the gap between its output power and the power that should be generated, and calculate the power loss ratio caused by artificial curtailment, which is the passive wind curtailment rate, and complete the identification of the passive wind curtailment rate. The higher the passive wind curtailment rate, the less effectively the wind resources are utilized, and the dispatching strategy needs to be optimized.

[0054] Call the curtailment adjustment predictor of each photovoltaic power generation module to analyze the curtailment adjustment parameters of each photovoltaic power generation module, calculate the power reduction ratio caused by the curtailment instruction, so as to obtain the passive light curtailment rate, complete the identification of the passive light curtailment rate, and the passive light curtailment rate reflects the impact of dispatching behavior on the photovoltaic utilization efficiency.

[0055] Furthermore, this application also includes: Based on the energy storage regulation burden distribution, identifying high-frequency energy storage modules with a burden higher than the preset burden index and low-frequency energy storage modules with a burden lower than the preset burden index, and optimizing the energy storage scheduling to generate a first balanced optimization result; Based on the wind curtailment rate distribution and the light curtailment rate distribution, minimizing the wind curtailment rate and the light curtailment rate to perform the grid connection of each wind power generation module and each photovoltaic power generation module to the traditional energy dispatching of the power grid, generating a second balanced optimization result; Using the first balanced optimization result and the second balanced optimization result to generate the power grid energy distribution decision.

[0056] Specifically, based on the energy storage regulation burden distribution, identifying high-frequency energy storage modules with a burden higher than the preset burden index and low-frequency energy storage modules with a burden lower than the preset burden index, and optimizing the energy storage scheduling. By analyzing the frequency of the energy storage system undertaking the regulation task in historical operation, finding out the energy storage units with a regulation frequency exceeding the system-set threshold as high-frequency energy storage modules, and the low-frequency energy storage modules with a regulation frequency significantly lower than this threshold. The energy storage regulation burden distribution refers to the distribution of all energy storage units undertaking the charge-discharge regulation task per unit time, reflecting the concentration or dispersion degree of the regulation load. The preset burden index is a reference standard set artificially. For example, it is stipulated that the daily regulation times of each energy storage module should not exceed 10 times. After identifying the high-frequency and low-frequency modules, by readjusting the scheduling relationship between the energy storage modules and new energy or loads, the high-burden units can be relieved of pressure and the low-burden units can increase efficiency, thus generating a more balanced first balanced optimization result.

[0057] Based on the wind curtailment rate distribution and the light curtailment rate distribution, minimizing the wind curtailment rate and the light curtailment rate to perform the grid connection of each wind power generation module and each photovoltaic power generation module to the traditional energy dispatching of the power grid. Using the spatial distribution information of the wind curtailment rate and the light curtailment rate on the wind-solar-storage topological map, re-planning the path or dispatching sequence of the wind power and photovoltaic power generation modules connecting to the power grid to reduce the power loss caused by the curtailment of each power generation module. The wind curtailment rate distribution refers to the differential performance in space of the wind curtailment ratio of each wind power generation module in the historical or predicted period, while the light curtailment rate distribution is the distribution of the light curtailment level of each photovoltaic module. Grid connection refers to the process of the wind power and photovoltaic power generation modules transporting the generated electric energy to the public power grid through equipment such as transformers and inverters. Traditional energy dispatching refers to the dynamic adjustment of the priority or power upper and lower limits of the power source access by the dispatching platform under the established power system structure. By optimizing the access points and dispatching strategies, the total curtailment power is reduced, and finally a second balanced optimization result of reducing wind curtailment and light curtailment losses is generated.

[0058] Generate a power grid energy distribution decision based on the first equilibrium optimization result and the second equilibrium optimization result, which not only considers the balance of load regulation among energy storage modules but also takes into account the consumability of wind power and photovoltaic power generation, and jointly constructs a power grid energy distribution scheme oriented to global optimization. The power grid energy distribution decision refers to giving instructions such as the energy input-output ratio, power upper and lower limits, and scheduling priorities of different energy units in each time period based on various factors such as the actual operating status, equipment capabilities, and power generation potential, so as to guide the coordinated operation of the entire wind-solar-storage system. This decision-making scheme ultimately guides the dispatching platform to adopt a more reasonable distribution, lower loss, and more flexible response operation mode in actual operation.

[0059] Furthermore, this application also includes: determining the set of high-regulation-demand energy units connected to the high-frequency energy storage module and the set of low-regulation-demand energy units connected to the low-frequency energy storage module; collecting the regulation demands of the set of high-regulation-demand energy units and the set of low-regulation-demand energy units, and performing regulation demand equalization processing by exchanging elements within the set to generate an equalization processing result; using the equalization processing result to adjust the scheduling relationship between each energy storage module and energy unit to generate the first equilibrium optimization result.

[0060] Specifically, classify the energy units to which each energy storage module belongs according to the regulation frequency of each energy storage module, respectively identify the energy storage modules that frequently perform charge and discharge regulation within a unit time, and determine that the energy units connected to the energy storage module belong to the high-regulation-demand type. The energy storage modules with lower regulation frequencies and the energy units they are connected to are classified as the low-regulation-demand type, and the set of high-regulation-demand energy units connected to the high-frequency energy storage module and the set of low-regulation-demand energy units connected to the low-frequency energy storage module are determined. An energy storage module is a system unit used to absorb and release electrical energy to balance supply and demand fluctuations. An energy unit usually refers to a wind farm, a photovoltaic power station, or a load cluster, etc., which has a direct impact on the power supply and demand of the power grid. The regulation demand refers to the degree to which an energy unit needs to perform more frequent power balance regulation due to large fluctuations or rapid load changes.

[0061] Obtain the regulation behavior data of energy units in historical operation, such as frequently fluctuating wind speed curves, load change rates, or output power instability, etc., to measure the regulation load intensity, and collect the regulation demands of the set of high-regulation-demand energy units and the set of low-regulation-demand energy units. Perform regulation demand equalization processing by exchanging elements within the set, transfer some high-regulation-demand energy units from being connected to the high-frequency energy storage module to the low-frequency energy storage module, and at the same time move the low-regulation-demand energy units to the high-frequency energy storage module, so that the originally heavily loaded energy storage module can obtain energy units with lighter regulation loads, thereby realizing the balanced distribution of the overall regulation task. Element exchange is a matching optimization operation that reduces the overload risk of a single module by adjusting the connection relationship between energy storage and energy units.

[0062] Execute the scheduling relationship adjustment between each energy storage module and the energy unit based on the balanced processing result, and update the scheduling structure between the energy storage system and each energy unit, that is, change the power fluctuation of the energy storage module in response to the energy unit, form an optimized energy storage scheduling plan, and generate the first balanced optimization result, which helps to extend the life of the energy storage device and improve the system regulation efficiency.

[0063] Furthermore, this application also includes: The grid-connected access to the power grid is the power system to which each wind power generation module and each photovoltaic power generation module are connected through a grid-connection device.

[0064] Specifically, grid connection refers to the process of the power generation source converting from an independent operation state to a state of connecting and operating with the power system, with the aim of enabling the electricity generated by wind or photovoltaic to be directly used by the power grid. The grid-connected access to the power grid is the power system to which each wind power generation module and each photovoltaic power generation module are connected through a grid-connection device, which means the process of each wind power generation module and each photovoltaic power generation module delivering the generated electric energy to the public power network through a specific physical interface. The power system is a network composed of multiple links such as power generation, power transmission, power distribution, and power consumption, which is responsible for reasonably scheduling and delivering the electric energy from different sources to the end load. The electricity generated by the wind power generation module and the photovoltaic power generation module cannot be directly connected to the power grid and needs to undergo voltage conversion, frequency synchronization, and inversion processing through a grid-connection device. The grid-connection device includes a transformer, an inverter, a circuit breaker, and a protection device, etc., which convert the DC or unstable AC power from the new energy module into electric energy that meets the grid standards.

[0065] In summary, the integrated wind-solar-storage power grid energy distribution and scheduling method provided by this application has the following technical effects: By achieving the technical goal of coordinated optimization scheduling of wind-solar-storage based on the distribution of energy storage regulation burden and curtailment rate of wind and photovoltaic power, the technical effects of improving the operation balance of the energy storage system, reducing curtailment losses of wind and photovoltaic power, and achieving global optimal distribution of energy at the power grid level are achieved.

[0066] The above description of the disclosed embodiments enables those skilled in the art to implement or use this application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0067] Obviously, those skilled in the art can make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of this application and its equivalent technologies, this application also intends to include these changes and modifications.

Claims

1. A method for energy distribution and scheduling of an integrated wind-solar-storage power grid, characterized in that Including: Collecting the distribution information of wind-solar-storage devices in a preset power grid area and constructing a regional wind-solar-storage topology map; Collecting a historical wind-solar-storage operation data set based on the regional wind-solar-storage topology map; Performing an analysis of the regulation burden distribution of the energy storage module with the historical wind-solar-storage operation data set, marking on the regional wind-solar-storage topology map, and determining the energy storage regulation burden distribution; Performing an analysis of the wind curtailment rate distribution of wind power generation and an analysis of the light curtailment rate distribution of photovoltaic power generation with the historical wind-solar-storage operation data set, marking on the regional wind-solar-storage topology map, and generating the wind curtailment rate distribution and the light curtailment rate distribution; Combining the energy storage regulation burden distribution, the wind curtailment rate distribution, and the light curtailment rate distribution to optimize the balanced scheduling of wind-solar-storage and generating a power grid energy allocation decision.

2. The integrated wind-solar-storage power grid energy distribution and scheduling method according to claim 1, characterized in that Each node in the regional wind-solar-storage topology map represents an energy unit, and each edge represents a power grid connection relationship.

3. The integrated wind-solar-storage power grid energy distribution and scheduling method according to claim 1, characterized in that, Performing an analysis of the regulation burden distribution of the energy storage module with the historical wind-solar-storage operation data set, marking on the regional wind-solar-storage topology map, and determining the energy storage regulation burden distribution, including: Based on the historical wind-solar-storage operation data set, statistically analyzing the occurrence frequency of the regulation behaviors of each energy storage module within the scheduling period and calculating the mean value to obtain the regulation frequency of each energy storage module; Calculating the ratio of the regulation frequency of each energy storage module to the total sum of the regulation frequencies of each module, and marking on the regional wind-solar-storage topology map to generate the energy storage regulation burden distribution.

4. The integrated wind-solar-storage power grid energy distribution and scheduling method according to claim 3, wherein The occurrence frequency of the regulation behavior within the scheduling period is obtained by statistically counting the charge-discharge switching frequencies of each energy storage module.

5. The integrated wind-solar-storage power grid energy distribution and scheduling method according to claim 1, characterized in that, Performing an analysis of the wind curtailment rate distribution of wind power generation and an analysis of the light curtailment rate distribution of photovoltaic power generation with the historical wind-solar-storage operation data set, marking on the regional wind-solar-storage topology map, and generating the wind curtailment rate distribution and the light curtailment rate distribution, including: Identifying the passive wind curtailment rate and the passive light curtailment rate based on the historical wind-solar-storage operation data set, and generating a historical passive wind curtailment rate data sequence and a historical passive light curtailment rate data sequence; Calculating the mean values of the wind curtailment rate and the light curtailment rate within the period based on the historical passive wind curtailment rate data sequence and the historical passive light curtailment rate data sequence within the scheduling period, and generating the mean wind curtailment rate data of each wind power generation module and the mean light curtailment rate data of each photovoltaic power generation module; Marking the mean wind curtailment rate data of each wind power generation module and the mean light curtailment rate data of each photovoltaic power generation module on the regional wind-solar-storage topology map to generate the wind curtailment rate distribution and the light curtailment rate distribution.

6. The integrated wind-solar-storage power grid energy distribution and scheduling method according to claim 5, characterized in that The passive wind curtailment rate and the passive light curtailment rate are the deviation degrees of the power generation output of each wind power generation module and each photovoltaic power generation module being artificially reduced due to the issuance of a power generation limit instruction by an external dispatching platform, resulting in a deviation from the theoretically available power generation amount.

7. The integrated wind-solar-storage power grid energy distribution and scheduling method according to claim 6, wherein Identifying the passive wind curtailment rate and the passive light curtailment rate based on the historical wind-solar-storage operation data set, including: Extracting the data with a power generation limit instruction identifier from the historical wind-solar-storage operation data set and identifying the power generation limit adjustment parameters of each wind power generation module and the power generation limit adjustment parameters of each photovoltaic power generation module; Extract the operation parameter differences and wind power generation output differences of each wind power generation module under the same meteorological environment conditions from the historical wind-solar-storage operation dataset, and train the curtailment adjustment predictors of each wind power generation module; Extract the operation parameter differences and photovoltaic power generation output differences of each photovoltaic power generation module under the same meteorological environment conditions from the historical wind-solar-storage operation dataset, and train the curtailment adjustment predictors of each photovoltaic power generation module; Call the curtailment adjustment predictors of each wind power generation module to analyze the curtailment adjustment parameters of each wind power generation module, and complete the identification of the passive curtailment rate of wind power; Call the curtailment adjustment predictors of each photovoltaic power generation module to analyze the curtailment adjustment parameters of each photovoltaic power generation module, and complete the identification of the passive curtailment rate of photovoltaic power; 8. The integrated wind-solar-storage power grid energy distribution and scheduling method according to claim 1, wherein Combine the energy storage adjustment burden distribution, the curtailment rate distribution of wind power and the curtailment rate distribution of photovoltaic power to optimize the balanced dispatching of wind-solar-storage, and generate a power grid energy allocation decision, including: Based on the energy storage adjustment burden distribution, identify the high-frequency energy storage modules higher than the preset burden index and the low-frequency energy storage modules lower than the preset burden index for energy storage dispatching optimization, and generate a first balanced optimization result; Based on the curtailment rate distribution of wind power and the curtailment rate distribution of photovoltaic power, conduct the traditional energy dispatching for grid connection of each wind power generation module and each photovoltaic power generation module to minimize the curtailment rate of wind power and the curtailment rate of photovoltaic power, and generate a second balanced optimization result; Generate the power grid energy allocation decision with the first balanced optimization result and the second balanced optimization result; 9. The integrated wind-solar-storage power grid energy distribution and scheduling method according to claim 8, characterized in that, Based on the energy storage adjustment burden distribution, identify the high-frequency energy storage modules higher than the preset burden index and the low-frequency energy storage modules lower than the preset burden index for energy storage dispatching optimization, and generate a first balanced optimization result, including: Determine the set of high-regulation-demand energy units connected to the high-frequency energy storage modules and the set of low-regulation-demand energy units connected to the low-frequency energy storage modules; Collect the regulation demands of the set of high-regulation-demand energy units and the set of low-regulation-demand energy units, and perform the regulation demand equalization process by exchanging elements within the sets to generate an equalization process result; Execute the adjustment of the dispatching relationship between each energy storage module and the energy unit with the equalization process result to generate the first balanced optimization result; 10. The integrated wind-solar-storage power grid energy distribution and scheduling method according to claim 8, wherein, The grid connection is the power system to which each wind power generation module and each photovoltaic power generation module are connected through grid connection devices.

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