Virtual pumped storage coordinated control method and device for cascade water and wind power storage complementary system

Abstract

This application provides a virtual pumped-storage coordinated control method and apparatus for a cascade hydropower-wind-solar-storage complementary system, belonging to the field of energy dispatch. The virtual pumped-storage coordinated control method for the cascade hydropower-wind-solar-storage complementary system provided in this application includes: acquiring system input data and calculating the original total output including wind power output, solar power output, and runoff hydropower output; performing empirical mode decomposition on the original total output to obtain fluctuation components and residual components of different frequencies; dividing the fluctuation components into a first imbalance, a second imbalance, and a smooth component based on frequency characteristics; wherein the smooth component is not smoothed; performing virtual pumped-storage regulation on the cascade hydropower based on the first imbalance to obtain the regulated hydropower output; controlling the charging and discharging of the energy storage device based on the second imbalance to obtain the energy storage regulation power; and reconstructing the output by combining the regulated hydropower output and the energy storage regulation power to obtain the final total system output.

Description

Technical Field

[0001] This application relates to the field of energy dispatching technology, and in particular to a virtual pumped storage coordinated control method and device for a cascade hydropower-wind-solar-storage complementary system. Background Technology

[0002] To achieve the "dual carbon" goal, the proportion of renewable energy sources such as wind power and photovoltaics in the power system continues to increase. However, their inherent randomness and volatility can easily cause problems such as power grid imbalance and curtailment of wind and solar power. Cascade hydropower stations have natural reservoir capacity regulation capabilities. When combined with wind, solar and battery energy storage to form a cascade hydro-wind-solar-storage complementary system, it is a key way to smooth out fluctuations and improve the system's stable operation. There is an urgent need for efficient virtual pumped storage coordinated control methods.

[0003] Current systems of this type generally adopt a layered, superimposed control approach, prioritizing the use of hydropower units to balance fluctuations in wind and solar net loads. Any remaining fluctuations that hydropower cannot mitigate are directly allocated to battery storage, or bidirectional power regulation is achieved through newly constructed pumped-storage hydropower stations. These traditional control methods fail to achieve precise power allocation based on the characteristics of the fluctuation spectrum. This can lead to frequent responses from hydropower units to high-frequency fluctuations, resulting in increased wear and tear, and battery storage systems bearing the burden of low-frequency, high-energy components, thus shortening their lifespan. Furthermore, pumped-storage hydropower suffers from high investment costs, long construction periods, and geographical limitations, making it difficult to balance system regulation efficiency, operating costs, and power supply stability.

[0004] Therefore, there is an urgent need for a method to achieve low-cost, highly adaptable, and collaboratively optimizable virtual pumping and storage control. Summary of the Invention

[0005] In view of this, this application provides a virtual pumped storage coordinated control method and device for a cascade hydro-wind-solar-storage complementary system, in order to achieve low-cost, highly adaptable, and synergistically optimizable virtual pumped storage coordinated control.

[0006] Specifically, this application is implemented through the following technical solution:

[0007] The first aspect of this application provides a virtual pumped-storage coordinated control method for a cascade hydro-wind-solar-storage complementary system, the method comprising:

[0008] Obtain system input data and calculate the original total output including wind power output, photovoltaic power output, and runoff hydropower output;

[0009] Empirical mode decomposition is performed on the original total output to obtain fluctuation components and residual components of different frequencies;

[0010] Based on frequency characteristics, the fluctuation component is divided into a first imbalance, a second imbalance, and a smooth component; wherein, the smooth component is not subjected to smoothing processing.

[0011] Based on the first imbalance, the cascade hydropower is virtually pumped and stored to obtain the regulated hydropower output.

[0012] Based on the second imbalance quantity, the energy storage device is charged and discharged to obtain the energy storage regulation power;

[0013] The adjusted hydropower output and energy storage regulation power are reconstructed to obtain the final total output of the system.

[0014] Optionally, based on the first imbalance, virtual pumping and storage regulation is performed on the cascade hydropower to obtain the regulated hydropower output, including: determining whether the first imbalance is greater than zero; if the first imbalance is less than or equal to zero, controlling the cascade hydropower to perform water release operation to supplement the system output; if the first imbalance is greater than zero, determining whether there is runoff-type water abandonment; if there is runoff-type water abandonment, storing the runoff and absorbing the surplus output; if there is no runoff-type water abandonment, controlling the cascade reservoirs to perform water storage operation to absorb the surplus output; and updating the regulated hydropower output according to the power generation flow and reservoir capacity status after virtual pumping and storage regulation.

[0015] Optionally, controlling the charging and discharging of the energy storage device based on the second imbalance to obtain the energy storage regulation power includes: determining whether the second imbalance is greater than zero; if the second imbalance is greater than zero, controlling the energy storage device to charge to absorb the system's surplus power; if the second imbalance is less than or equal to zero, controlling the energy storage device to discharge to supplement the system's shortfall power; updating the energy storage state according to the charging and discharging results, and outputting the corresponding energy storage regulation power.

[0016] Optionally, based on frequency characteristics, the fluctuation components are divided into a first imbalance, a second imbalance, and a smooth component, including: selecting the first K fluctuation components as the second imbalance; selecting the last W fluctuation components and the residual component as smooth components; and selecting the middle NWK fluctuation components as the first imbalance; wherein the total number of fluctuation components is N.

[0017] Optionally, the system input data includes wind speed, solar irradiance, and inflow rate.

[0018] Optionally, empirical mode decomposition is performed on the original total output to obtain fluctuation components and residual components of different frequencies, including: using the original total output as the initial decomposition signal; identifying the local maxima and local minima of the initial decomposition signal, and forming an upper envelope and a lower envelope through interpolation fitting; calculating the mean envelope of the upper and lower envelopes, and subtracting the mean envelope from the initial decomposition signal to obtain candidate mode components; determining whether the candidate mode components satisfy the intrinsic mode function conditions, and if not, using the candidate mode components as the new initial decomposition signal, repeating the extreme value identification, envelope fitting, and mean elimination steps until fluctuation components that satisfy the intrinsic mode function conditions are obtained; removing the extracted fluctuation components from the current decomposition signal, and continuing the decomposition steps on the remaining decomposition signal until the remaining decomposition signal is a monotonic trend term without fluctuations, thus obtaining multiple fluctuation components of different frequencies and one residual component.

[0019] Optionally, before controlling the charging and discharging of the energy storage device based on the second imbalance, the method further includes: performing typical day clustering on the annual second imbalance data; determining the energy storage capacity based on the standard deviation of the second imbalance fluctuation within the typical day; extracting a 24-hour second imbalance reduction ratio template for each typical day; generating hourly energy storage charging and discharging power based on the second imbalance reduction ratio template of the typical class to which each day belongs and the actual second imbalance of each day; and performing operational constraint correction on the energy storage charging and discharging power to obtain the annual energy storage regulation power sequence.

[0020] Optionally, after obtaining the final total output of the system, the method further includes: constructing a multi-objective collaborative optimization model with the objectives of maximizing power generation, optimizing power quality, and minimizing the pressure of water-storage coordinated regulation, and incorporating operational constraints including installed capacity, outflow, reservoir capacity, and battery state of charge; solving the multi-objective collaborative optimization model using a multi-objective optimization algorithm to obtain a Pareto optimal solution set; and selecting the optimal collaborative control scheme from the Pareto optimal solution set through a comprehensive evaluation method.

[0021] Optionally, the multi-objective optimization algorithm includes NSGA-II, and the comprehensive evaluation method includes CRITIC-TOPSIS.

[0022] The second aspect of this application provides a virtual pumped storage coordinated control device for a cascade hydro-wind-solar-storage complementary system, the device comprising a calculation module, a decomposition module, a partitioning module, a processing module and a reconstruction module;

[0023] The calculation module is used to acquire system input data and calculate the original total output including wind power output, photovoltaic power output and runoff hydropower output.

[0024] The decomposition module is used to perform empirical mode decomposition on the original total output to obtain fluctuation components and residual components of different frequencies.

[0025] The division module is used to divide the fluctuation component into a first imbalance, a second imbalance, and a smooth component based on frequency characteristics; wherein the smooth component is not subjected to smoothing processing.

[0026] The processing module is used to perform virtual pumping and storage regulation on the cascade hydropower based on the first imbalance, so as to obtain the regulated hydropower output.

[0027] The processing module is also used to control the charging and discharging of the energy storage device based on the second imbalance to obtain the energy storage regulation power;

[0028] The reconfiguration module is used to reconfigure the adjusted hydropower output and energy storage regulation power to obtain the final total output of the system.

[0029] The virtual pumped storage coordinated control method and device for a cascade hydropower-wind-solar-storage complementary system provided in this application constructs a complete coordinated control logic from the overall process: "original output calculation—modal decomposition and component classification—classified smoothing regulation—output reconstruction." First, the original total output of wind, solar and hydropower is accurately calculated using input data, providing accurate basic data for subsequent control. Then, empirical modal decomposition combined with frequency characteristics is used to classify the first imbalance, second imbalance and smooth components, realizing accurate classification of fluctuation components according to characteristics, avoiding regulation redundancy or insufficient effect caused by uniform processing. Then, for different imbalances, virtual pumped storage of cascade hydropower and charging and discharging of energy storage devices are used to smooth them separately, adapting to the regulation characteristics of different fluctuations, taking into account regulation efficiency and system stability. Finally, the smooth and stable final total output of the system is obtained through reconstruction. The overall process is clear in hierarchy and has a closed-loop logic, which not only achieves refined fluctuation smoothing, but also simplifies the control logic and improves the accuracy, reliability and engineering applicability of virtual pumped storage coordinated control. Attached Figure Description

[0030] Figure 1 A flowchart of the virtual pumped storage coordinated control method for a cascade hydro-wind-solar-storage complementary system provided in Embodiment 1 of this application;

[0031] Figure 2 This is a schematic diagram of the structure of the virtual pumped storage coordinated control device for the cascade hydro-wind-solar-storage complementary system provided in Embodiment 2 of this application. Detailed Implementation

[0032] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0033] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used herein are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0034] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0035] The following specific embodiments are given to illustrate the technical solution of this application in detail.

[0036] Figure 1 This is a flowchart illustrating the virtual pumped-storage coordinated control method for a cascade hydro-wind-solar-storage complementary system provided in Embodiment 1 of this application. Please refer to... Figure 1 The method provided in this embodiment may include:

[0037] S101. Obtain system input data and calculate the original total output including wind power output, photovoltaic power output, and runoff hydropower output.

[0038] Optionally, the system input data includes wind speed, solar irradiance, and inflow rate.

[0039] Specifically, the system input data consists of the fundamental physical quantities required for virtual pumped-storage coordinated control. It is a prerequisite for calculating the output of various types of power generation and is not adjusted or reconfigured; it is used solely for data input and calculation. The system input data includes three parts: wind speed, solar irradiance, and inflow. Wind speed is the raw meteorological data used to calculate wind power output. Solar irradiance is the raw meteorological data used to calculate photovoltaic output. Inflow is the raw hydrological data used to calculate runoff hydropower output.

[0040] Furthermore, the initial total output is the total power generated by the system directly calculated from the aforementioned input data. It is the initial total output without virtual pumped storage regulation or energy storage smoothing. The initial total output is composed of three superimposed parts: wind power output, photovoltaic power output, and runoff hydropower output. Wind power output refers to the actual power generated by the wind farm calculated based on wind speed. Photovoltaic power output refers to the actual power generated by the photovoltaic power station calculated based on solar irradiance. Runoff hydropower output refers to the hydropower generated based on inflow, without considering reservoir regulation, and only according to runoff.

[0041] In practical implementation, the system first collects and acquires the input data required for operation, including measured or predicted wind speed data from wind farms, measured or predicted solar irradiance data from photovoltaic power plants, and measured or predicted inflow data from cascade hydropower stations. Based on the acquired wind speed data, the wind power output at the corresponding time is calculated according to the wind power characteristic curve; based on the acquired solar irradiance data, the photovoltaic output at the corresponding time is calculated in conjunction with the power generation characteristics of photovoltaic modules; based on the acquired inflow data, the runoff hydropower output at the corresponding time is calculated using the power generation calculation method for runoff hydropower stations, without considering reservoir regulation and water storage effects, based solely on natural inflow. The wind power output, photovoltaic output, and runoff hydropower output calculated at the same time are then summed to obtain the original total output of the cascade hydropower-wind-solar-storage complementary system. The specific calculation process for the three types of output can be found in the descriptions in related technologies, and will not be repeated here.

[0042] S102. Perform empirical mode decomposition on the original total output to obtain fluctuation components and residual components of different frequencies.

[0043] Specifically, Empirical Mode Decomposition (EMD) is an adaptive time-frequency decomposition method for non-stationary and nonlinear signals. It decomposes the fluctuating signal of the original total output power according to its own time-scale characteristics, without the need for pre-defined basis functions. It can decompose the signal into a series of components of different frequencies and a trend term. The fluctuation components are multiple intrinsic mode functions (IMFs) obtained after EMD. Each fluctuation component corresponds to a fluctuation component of a certain frequency and period in the original total output power, reflecting the fluctuations in system output power at different time scales. The residual components are the monotonic or approximately monotonic trend term signal remaining after EMD, representing the slowly changing overall trend portion of the original total output power without significant high-frequency fluctuations, and do not contain rapid fluctuation characteristics.

[0044] In specific implementation, empirical mode decomposition is performed on the original total output to obtain fluctuation components and residual components of different frequencies. This includes: using the original total output as the initial decomposition signal; identifying the local maxima and local minima of the initial decomposition signal, and forming an upper envelope and a lower envelope through interpolation fitting; calculating the mean envelope of the upper and lower envelopes, and subtracting the mean envelope from the initial decomposition signal to obtain candidate mode components; determining whether the candidate mode components satisfy the intrinsic mode function conditions. If not, the candidate mode components are used as new initial decomposition signals, and the extreme value identification, envelope fitting, and mean elimination steps are repeated until fluctuation components that satisfy the intrinsic mode function conditions are obtained; the extracted fluctuation components are removed from the current decomposition signal, and the decomposition steps are continued on the remaining decomposition signal until the remaining decomposition signal is a monotonic trend term without fluctuations, resulting in multiple fluctuation components of different frequencies and one residual component.

[0045] Specifically, the original total output is directly used as the initial decomposition signal, serving as the sole input signal for empirical mode decomposition. Extreme value identification is performed on the initial decomposition signal. A signal processing algorithm scans the initial decomposition signal time-by-time to identify all local maxima and minima in the signal curve. Using cubic spline interpolation, an upper envelope is fitted based on all identified local maxima to completely encompass the upper limit of the initial decomposition signal's fluctuations; simultaneously, a lower envelope is fitted based on all local minima to completely encompass the lower limit of the initial decomposition signal's fluctuations, ensuring that both envelopes fully cover the entire fluctuation range of the initial decomposition signal. The corresponding means of the upper and lower envelopes at the same time are calculated mathematically, and the means at all times are connected to form a mean envelope. Subsequently, the initial decomposition signal is subtracted from the corresponding mean envelope value time-by-time to obtain a preliminary candidate mode component. The process involves determining whether a candidate modal component (IMF) satisfies the core condition of the Intrinsic Mode Function (IMF): the number of local maxima and local minima of the IMF is equal or differs by no more than 1 throughout the entire time series, and the mean of its upper and lower envelopes is zero. If the IMF does not meet this condition, it is used as a new initial decomposition signal. The process of extreme value identification, envelope fitting, and mean removal is repeated iteratively until a component that meets the IMF condition is obtained; this component is a qualified fluctuation component. The extracted qualified fluctuation components are then completely removed from the current decomposition signal, resulting in the remaining decomposition signal. This remaining decomposition signal is then subjected to the same process of repeating all decomposition steps from extreme value identification to candidate modal component verification, continuously extracting qualified fluctuation components. The above decomposition, elimination, and re-decomposition process is continuously repeated until the remaining decomposed signal presents a monotonic trend term without any obvious fluctuations (i.e., it is impossible to extract any fluctuation components that meet the intrinsic mode function conditions). At this point, all the qualified components extracted are fluctuation components of different frequencies, and the remaining monotonic trend term is the residual component.

[0046] S103. Based on the frequency characteristics, the fluctuation component is divided into a first unbalance, a second unbalance, and a smooth component.

[0047] The smooth component is not subjected to any smoothing process.

[0048] Specifically, frequency characteristics refer to the speed and period of change of each fluctuation component over time, mainly reflected in the frequency and amplitude of the fluctuations, used to distinguish output fluctuations at different time scales. The first imbalance consists of medium-frequency, medium-period fluctuation components, corresponding to the imbalance components with larger amplitudes and longer durations in the original total output, which are smoothed by cascade hydropower through virtual pumped storage. The second imbalance consists of high-frequency, short-period fluctuation components, corresponding to the imbalance components with faster changes and relatively smaller amplitudes in the original total output, which are quickly smoothed by battery energy storage. The smoothed components consist of low-frequency, slowly changing fluctuation components and residual components; their fluctuations are smooth and stable, without obvious rapid fluctuation characteristics, and are not smoothed and are directly retained.

[0049] In specific implementation, the fluctuation components are divided into a first imbalance, a second imbalance, and a smooth component based on frequency characteristics, including: selecting the first K fluctuation components as the second imbalance; selecting the last W fluctuation components and the residual component as smooth components; and selecting the middle NWK fluctuation components as the first imbalance; wherein the total number of fluctuation components is N.

[0050] Specifically, firstly, based on the empirical mode decomposition results, the total number of fluctuation components is determined to be N. The fluctuation components are sorted from highest to lowest frequency, and the top K fluctuation components are selected and classified as the second imbalance. The bottom W fluctuation components are selected and combined with the residual components to classify them as smooth components. The remaining NWK fluctuation components after removing the top K and bottom W are classified as the first imbalance.

[0051] S104. Based on the first imbalance, perform virtual pumping and storage regulation on the cascade hydropower to obtain the regulated hydropower output.

[0052] Specifically, cascade hydropower refers to a collective term for multiple hydropower stations built and connected in series on the same river, arranged from upstream to downstream. These stations form a cascade layout through upstream and downstream water flow, and can jointly regulate power output using reservoir capacity. Virtual pumped storage regulation refers to a two-way power regulation similar to pumped storage, achieved by controlling the power generation flow without adding physical pumping units and pumping loops: reducing power generation and storing water when the system has excess power; and increasing power generation and releasing water to replenish energy when the system has insufficient power. This smooths out the power output fluctuations corresponding to the first imbalance, resulting in regulated hydropower output.

[0053] In specific implementation, the cascade hydropower is virtually pumped and stored based on the first imbalance to obtain the adjusted hydropower output. This includes: determining whether the first imbalance is greater than zero; if the first imbalance is less than or equal to zero, controlling the cascade hydropower to release water to supplement the system output; if the first imbalance is greater than zero, determining whether there is runoff-type water abandonment; if there is runoff-type water abandonment, storing the runoff and absorbing the surplus output; if there is no runoff-type water abandonment, controlling the cascade reservoirs to store water to absorb the surplus output; and updating the adjusted hydropower output based on the power generation flow and reservoir capacity status after virtual pumping and storage adjustment.

[0054] Specifically, the first step is to determine the magnitude of the first imbalance quantity to see if it is greater than zero. If the first imbalance quantity is less than or equal to zero, it indicates a power output deficit in the system. In this case, the cascade hydropower stations are controlled to increase the power generation flow and release water to increase hydropower output and supplement the system's power output gap. If the first imbalance quantity is greater than zero, it indicates a power output surplus in the system. Further analysis is needed to determine if there is any runoff-type water abandonment. If there is runoff-type water abandonment, the abandoned water flow is stored by impounding the runoff, while simultaneously absorbing the system's surplus power output. If there is no runoff-type water abandonment, the cascade reservoirs are controlled to reduce the power generation flow and store water to reduce hydropower output and absorb the system's surplus power output. Based on the power generation flow determined after virtual pumping regulation, combined with the current real-time reservoir capacity and water level corresponding head characteristics of the cascade reservoirs, the power output calculation formula for hydropower stations is used. The power generation flow is multiplied by the net head and included in the comprehensive efficiency coefficient to calculate the power generation output value at the current moment. This value is the hydropower output after virtual pumping regulation.

[0055] S105. Based on the second imbalance, control the charging and discharging of the energy storage device to obtain the energy storage regulation power.

[0056] Specifically, energy storage devices refer to battery energy storage systems configured in hydro-wind-solar-storage complementary systems, including energy storage battery clusters, energy storage converters (PCS), and supporting control systems. These systems can rapidly absorb and release electrical energy to smooth out high-frequency fluctuations. Energy storage regulation power refers to the charging and discharging power presented externally after the energy storage device controls charging and discharging according to the second imbalance quantity: a positive value represents the energy absorption power (charging), and a negative value represents the energy release power (discharging). This power is used to smooth out high-frequency fluctuation components in the original total output.

[0057] In specific implementation, the energy storage device is charged and discharged based on the second imbalance to obtain the energy storage regulation power, including: determining whether the second imbalance is greater than zero; if the second imbalance is greater than zero, controlling the energy storage device to charge to absorb the surplus power of the system; if the second imbalance is less than or equal to zero, controlling the energy storage device to discharge to supplement the power deficit of the system; updating the energy storage state according to the charging and discharging results, and outputting the corresponding energy storage regulation power.

[0058] Specifically, the first step is to determine the magnitude of the second imbalance, specifically whether it is greater than zero. If the second imbalance is greater than zero, it indicates a power surplus in the system. A charging control command is then issued to the energy storage device, controlling it to charge at the corresponding power level, converting the surplus electrical energy into chemical energy for storage, thereby absorbing the system's surplus power. If the second imbalance is less than or equal to zero, it indicates a power deficit in the system. A discharging control command is then issued to the energy storage device, controlling it to discharge at the corresponding power level, converting the internally stored chemical energy into electrical energy for release, thereby supplementing the system's power deficit. Based on the actual charging or discharging operations performed by the energy storage device, the system updates the device's state of charge, cumulative charge / discharge amount, and other operating status information in real time, and uses the actual charging or discharging power output of the energy storage device at the current moment as the energy storage regulation power output.

[0059] Optionally, before controlling the charging and discharging of the energy storage device based on the second imbalance, the method further includes: performing typical day clustering on the annual second imbalance data; determining the energy storage capacity based on the standard deviation of the second imbalance fluctuation within the typical day; extracting a 24-hour second imbalance reduction ratio template for each typical day; generating hourly energy storage charging and discharging power based on the second imbalance reduction ratio template of the typical class to which each day belongs and the actual second imbalance of each day; and performing operational constraint correction on the energy storage charging and discharging power to obtain the annual energy storage regulation power sequence.

[0060] Specifically, before controlling the charging and discharging of energy storage devices based on the second imbalance quantity, the time-series data of the second imbalance quantity throughout the year is collected and clustered on typical days. The required energy storage capacity is determined according to the standard deviation of the fluctuation of the second imbalance quantity within each typical day. At the same time, a 24-hour second imbalance quantity reduction ratio template that can characterize the relative suppression intensity of high-frequency fluctuations at each time period within each typical day is extracted. For each day of the year, the corresponding energy storage charging and discharging power is calculated hourly based on the reduction ratio template corresponding to the typical class to which the day belongs, combined with the actual short-term second imbalance quantity of the day. The hourly generated energy storage charging and discharging power is then processed to correct the operating constraints, and finally a complete annual energy storage regulation power sequence that meets the operating requirements is obtained.

[0061] S106. Reconstruct the output of the regulated hydropower and the energy storage regulation power to obtain the final total output of the system.

[0062] Specifically, the regulated hydropower output refers to the actual power generated by the cascade hydropower stations and connected to the grid after virtual pumped storage regulation, and it is always a non-negative number. Energy storage regulation power refers to the power exchanged between the energy storage system and the grid, which can be positive, negative, or zero. The final total system output refers to the overall external output power obtained by superimposing the cascade hydropower output after virtual pumped storage regulation with the energy storage regulation power corresponding to the charging and discharging of the energy storage devices. This output has smoothed out the fluctuation components in the original wind, solar, and hydropower output, and can stably and smoothly meet the grid connection and load power supply requirements.

[0063] In practice, the regulated hydropower output and energy storage regulation power are unified to the same time segment (e.g., the same minute or the same 15-minute period). Based on the actual charging and discharging state of the energy storage, the energy storage regulation power is assigned a sign: a positive value during charging (representing absorbed power), a negative value during discharging (representing released power), and 0 when not in operation. The hydropower output and energy storage power are converted to the same unit (e.g., MW or kW). The regulated hydropower output and the signed energy storage regulation power at the same moment are algebraically added, and the calculated algebraic sum is taken as the final total output of the system at that moment.

[0064] Optionally, after obtaining the final total output of the system, the method further includes: constructing a multi-objective collaborative optimization model with the objectives of maximizing power generation, optimizing power quality, and minimizing the pressure of water-storage coordinated regulation, and incorporating operational constraints including installed capacity, outflow, reservoir capacity, and battery state of charge; solving the multi-objective collaborative optimization model using a multi-objective optimization algorithm to obtain a Pareto optimal solution set; and selecting the optimal collaborative control scheme from the Pareto optimal solution set through a comprehensive evaluation method.

[0065] Optionally, the multi-objective optimization algorithm includes NSGA-II, and the comprehensive evaluation method includes CRITIC-TOPSIS.

[0066] Specifically, optimal power quality includes minimizing the intensity of both short-term fluctuations (hourly fluctuations within a day) and long-term fluctuations (daily and weekly fluctuations within a month). The pressure of coordinated regulation between water and energy storage includes the pressure of energy storage capacity configuration and operational regulation, as well as the pressure of hydropower regulation. Specifically, energy storage capacity configuration refers to the energy storage capacity (capacity term) required to achieve the desired regulation effect against short-term fluctuations (hourly fluctuations within a day), while operational regulation pressure refers to the periods during which energy storage operates at its maximum power limit and the upper and lower limits of its State of Charge (SOC).

[0067] It should be noted that minimizing energy storage capacity configuration and operational pressure means achieving the best possible balance of imbalances with the smallest possible energy storage capacity. However, simply minimizing capacity can easily lead to optimization results that merely approach the lower limit of capacity configuration constraints, rather than obtaining a suitable energy storage capacity. Increasing operational pressure avoids the configured energy storage from operating at high power and the SOC boundary for extended periods (small capacity configurations tend to operate at high power and the SOC boundary), thus achieving a suitable (optimal) capacity configuration. Minimizing hydropower operational pressure aims to minimize the period of high-frequency, oscillating (repeated positive and negative regulation) regulation by hydropower. Since these configuration items are optimally allocated during the optimization process, hydropower's regulation capacity is greater than that of energy storage capacity (the reservoir acts as virtual energy storage), but it is not flexible enough. Moreover, high-frequency output regulation by hydropower is not conducive to its stable operation. Therefore, this optimization aims to reduce the period of high-frequency, oscillating regulation, minimizing it and reducing the operational pressure on hydropower.

[0068] In practical implementation, after obtaining the final total output of the system, a multi-objective collaborative optimization model is constructed with the optimization objectives of maximizing power generation, optimizing power quality, and minimizing the pressure of water-storage coordinated regulation. Operating conditions such as installed capacity limitations, hydropower unit discharge flow constraints, upper and lower limits of cascade reservoir capacity constraints, and battery state-of-charge safe operating range constraints are incorporated into the model as constraints. The NSGA-II algorithm is used to iteratively solve the constructed multi-objective collaborative optimization model, obtaining a set of non-dominated Pareto optimal solutions. The CRITIC-TOPSIS comprehensive evaluation method is used to assign index weights and rank the feasible solutions in the Pareto optimal solution set. Based on the ranking results, the solution with the best overall performance is selected as the optimal collaborative control scheme for the system.

[0069] The method provided in this embodiment has two aspects. First, it constructs a closed-loop control logic from the overall process: "original total output calculation—empirical mode decomposition and fluctuation component classification—categorized smoothing adjustment—output reconstruction." It first accurately calculates the original total output of wind power, photovoltaic power, and runoff hydropower using wind speed, solar irradiance, and inflow as inputs, providing a reliable data foundation for subsequent regulation. Then, it clarifies different fluctuation characteristics through decomposition and classification. Next, it performs virtual pumping and energy storage charging and discharging level suppression according to category, finally reconstructing a smooth and stable final total output of the system, effectively solving the problems of large fluctuations in wind, solar, and hydropower output and difficulties in grid connection. Second, it uses empirical mode decomposition to adaptively decompose the non-stationary and nonlinear original total output signal into different frequency fluctuation components and residual components according to its own time scale without the need for preset basis functions. This accurately extracts the fluctuation characteristics at each scale, avoiding the distortion and bias of traditional filtering methods, providing a precise basis for subsequent classification and smoothing, and improving the precision of fluctuation identification and processing. Thirdly, after power output reconfiguration, a multi-objective collaborative optimization model is constructed with the goals of maximizing power generation, optimizing power quality, and minimizing the pressure on water-storage coordinated regulation. Constraints such as installed capacity, outflow, reservoir capacity, and battery state of charge are incorporated. The NSGA-II algorithm is used to obtain the Pareto optimal solution set, and the optimal solution is then selected using the CRITIC-TOPSIS comprehensive evaluation method. This achieves a synergistic improvement in system economy, power quality, and operational safety, reducing energy storage configuration costs and increasing energy utilization. Fourthly, a differentiated mitigation strategy is adopted for imbalances with different frequency characteristics. The high-frequency, short-cycle second imbalance is mitigated by rapid charging and discharging of the energy storage device, while the medium-frequency, medium-cycle first imbalance is mitigated by the cascade hydropower virtual pumped storage regulation. Low-frequency, gentle components are not processed. This fully leverages the advantages of fast energy storage response and large hydropower regulation capacity, avoiding the problems of frequent high-frequency fluctuations exacerbating losses in hydropower units and shortening the lifespan of energy storage due to large energy fluctuations. This improves the mitigation effect while reducing equipment losses and operating costs.

[0070] Corresponding to the aforementioned embodiment of a virtual pumped storage coordinated control method for a cascade hydro-wind-solar-storage complementary system, this application also provides an embodiment of a virtual pumped storage coordinated control device for a cascade hydro-wind-solar-storage complementary system.

[0071] Figure 2 This is a schematic diagram of the virtual pumped-storage coordinated control device for the cascade hydro-wind-solar-storage complementary system provided in Embodiment 2 of this application. Please refer to... Figure 2 The apparatus provided in this embodiment includes a calculation module 210, a decomposition module 220, a division module 230, a processing module 240, and a reconstruction module 250.

[0072] The calculation module 210 is used to acquire system input data and calculate the original total output including wind power output, photovoltaic power output and runoff hydropower output.

[0073] The decomposition module 220 is used to perform empirical mode decomposition on the original total output to obtain fluctuation components and residual components of different frequencies.

[0074] The division module 230 is used to divide the fluctuation component into a first unbalanced quantity, a second unbalanced quantity, and a smooth component based on frequency characteristics; wherein the smooth component is not subjected to smoothing processing.

[0075] The processing module 240 is used to perform virtual pumping and storage regulation on the cascade hydropower based on the first imbalance, so as to obtain the regulated hydropower output.

[0076] The processing module 240 is also used to control the charging and discharging of the energy storage device based on the second imbalance to obtain the energy storage regulation power;

[0077] The reconfiguration module 250 is used to reconfigure the adjusted hydropower output and energy storage regulation power to obtain the final total output of the system.

[0078] The apparatus of this embodiment can be used to perform... Figure 1 The steps of the method embodiment shown are similar in principle and process, and will not be repeated here.

[0079] The specific implementation process of the functions and roles of each unit in the above device can be found in the implementation process of the corresponding steps in the above method, and will not be repeated here.

[0080] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0081] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A virtual pumped-storage coordinated control method for a cascade hydropower-wind-solar-storage complementary system, characterized in that, The method includes: Obtain system input data and calculate the original total output including wind power output, photovoltaic power output, and runoff hydropower output; Empirical mode decomposition is performed on the original total output to obtain fluctuation components and residual components of different frequencies; Based on frequency characteristics, the fluctuation component is divided into a first imbalance, a second imbalance, and a smooth component; wherein, the smooth component is not subjected to smoothing processing. Based on the first imbalance, the cascade hydropower is virtually pumped and stored to obtain the regulated hydropower output. Based on the second imbalance quantity, the energy storage device is charged and discharged to obtain the energy storage regulation power; The adjusted hydropower output and energy storage regulation power are reconstructed to obtain the final total output of the system.

2. The virtual pumped-storage coordinated control method for a cascade hydro-wind-solar-storage complementary system according to claim 1, characterized in that, Based on the first imbalance, virtual pumping and storage regulation is performed on the cascade hydropower to obtain the regulated hydropower output, including: Determine whether the first imbalance is greater than zero; If the first imbalance is less than or equal to zero, control the cascade hydropower to perform a water release operation to supplement the system output; If the first imbalance is greater than zero, determine whether there is runoff-type water abandonment; If runoff-type water waste exists, store the runoff and absorb the surplus power output; If there is no runoff-type water discharge, control the cascade reservoirs to perform water storage operations to absorb the surplus power output; Based on the power generation flow rate after virtual pumped storage adjustment and the reservoir capacity status, the adjusted hydropower output is updated.

3. The virtual pumping and storage coordinated control method for a cascade hydro-wind-solar-storage complementary system according to claim 1, characterized in that, Based on the second imbalance quantity, the charging and discharging of the energy storage device is controlled to obtain the energy storage regulation power, including: Determine whether the second imbalance is greater than zero; If the second imbalance is greater than zero, control the energy storage device to charge and absorb the system's surplus power; If the second imbalance is less than or equal to zero, control the energy storage device to discharge and replenish the system's power deficit. The energy storage state is updated based on the charging and discharging results, and the corresponding energy storage regulation power is output.

4. The virtual pumped-storage coordinated control method for a cascade hydro-wind-solar-storage complementary system according to claim 1, characterized in that, Based on frequency characteristics, the fluctuation component is divided into a first imbalance, a second imbalance, and a smooth component, including: The first K fluctuation components are selected as the second imbalance quantity; The last W fluctuation components and residual components are selected as smoothing components; The middle NWK fluctuation components are selected as the first imbalance quantity; where the total number of fluctuation components is N.

5. The virtual pumped-storage coordinated control method for a cascade hydro-wind-solar-storage complementary system according to claim 1, characterized in that, The system input data includes wind speed, solar irradiance, and inflow rate.

6. The virtual pumped-storage coordinated control method for a cascade hydro-wind-solar-storage complementary system according to claim 1, characterized in that, Empirical mode decomposition is performed on the original total output to obtain fluctuation components and residual components of different frequencies, including: The original total output was used as the initial decomposition signal; Identify the local maxima and local minima of the initial decomposed signal, and form the upper and lower envelopes through interpolation fitting; Calculate the mean envelope of the upper and lower envelopes, and subtract the mean envelope from the initial decomposed signal to obtain candidate mode components; Determine whether the candidate modal components satisfy the intrinsic mode function conditions. If not, use the candidate modal components as new initial decomposition signals and repeat the extreme value identification, envelope fitting, and mean removal steps until fluctuation components that satisfy the intrinsic mode function conditions are obtained. The extracted fluctuation components are removed from the current decomposed signal, and the decomposition steps are continued on the remaining decomposed signal until the remaining decomposed signal is a monotonic trend term without fluctuations, resulting in multiple fluctuation components of different frequencies and a residual component.

7. The virtual pumped-storage coordinated control method for a cascade hydro-wind-solar-storage complementary system according to claim 1, characterized in that, Before controlling the charging and discharging of the energy storage device based on the second imbalance, the method further includes: The annual second imbalance data is clustered by typical days. The energy storage capacity is determined based on the standard deviation of the second imbalance fluctuation within the typical day. A 24-hour second imbalance reduction ratio template is extracted for each typical day. Based on the template of the second imbalance reduction ratio of the typical category of each day within the year and the actual second imbalance of each day, the energy storage charging and discharging power is generated hourly. The energy storage charging and discharging power is adjusted for operational constraints to obtain the annual energy storage regulation power sequence.

8. The virtual pumping and storage coordinated control method for a cascade hydro-wind-solar-storage complementary system according to claim 1, characterized in that, After obtaining the final total output of the system, the method further includes: A multi-objective collaborative optimization model is constructed with the goals of maximizing power generation, optimizing power quality, and minimizing the pressure of water-storage coordinated regulation, and operational constraints including installed capacity, outflow, reservoir capacity, and battery state of charge are incorporated. The multi-objective cooperative optimization model is solved using a multi-objective optimization algorithm to obtain a Pareto optimal solution set. The optimal cooperative control scheme is then selected from the Pareto optimal solution set using a comprehensive evaluation method.

9. The method according to claim 8, characterized in that, The multi-objective optimization algorithm includes NSGA-II, and the comprehensive evaluation method includes CRITIC-TOPSIS.

10. A virtual pumped-storage coordinated control device for a cascade hydro-wind-solar-storage complementary system, characterized in that, The device includes a calculation module, a decomposition module, a partitioning module, a processing module, and a reconstruction module; The calculation module is used to acquire system input data and calculate the original total output including wind power output, photovoltaic power output and runoff hydropower output. The decomposition module is used to perform empirical mode decomposition on the original total output to obtain fluctuation components and residual components of different frequencies. The division module is used to divide the fluctuation component into a first imbalance, a second imbalance, and a smooth component based on frequency characteristics; wherein the smooth component is not subjected to smoothing processing. The processing module is used to perform virtual pumping and storage regulation on the cascade hydropower based on the first imbalance, so as to obtain the regulated hydropower output. The processing module is also used to control the charging and discharging of the energy storage device based on the second imbalance to obtain the energy storage regulation power; The reconfiguration module is used to reconfigure the adjusted hydropower output and energy storage regulation power to obtain the final total output of the system.

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