A collaborative optimization configuration method and system for stabilizing new energy output fluctuation

Abstract

A collaborative optimization configuration method and system for stabilizing new energy output fluctuation, the method first performs frequency domain decomposition on the fluctuation power gap sequence, divides low-frequency trend power components and high-frequency fluctuation power components; then, the low-frequency trend power components are distributed to the pumped storage system; the interactive coupling power between the pumped storage system and the electrochemical energy storage system is calculated, and the interactive coupling power and the high-frequency fluctuation power components are distributed to the electrochemical energy storage system; finally, a multi-objective collaborative optimization configuration model is constructed, and the model is solved to obtain the optimal capacity configuration scheme of the new energy system in the next dispatching period and the operation scheduling strategy at each time in the dispatching period; and the real-time operation monitoring result is executed to perform an adaptive feedback correction process. Through the complementary collaboration of the pumped storage and the electrochemical energy storage under different time scales, the present application realizes efficient stabilization of new energy fluctuation and optimization configuration of energy storage capacity, and improves the dynamic adaptation and complementary regulation capacity between the two types of energy storage.

Description

Technical Field

[0001] This invention belongs to the field of new energy grid connection and energy storage dispatch optimization technology, specifically involving a collaborative optimization configuration method and system for smoothing out fluctuations in new energy output. Background Technology

[0002] With the acceleration of the global energy transition, the proportion of new energy sources such as wind and solar power in the power system continues to increase. However, the output of new energy sources is significantly affected by natural conditions, exhibiting strong intermittency, volatility, and unpredictability, posing significant challenges to the safe and stable operation of the power system. Large fluctuations in new energy output can easily lead to problems such as grid frequency deviation, voltage instability, and increased dispatch pressure, affecting the reliability of grid operation and the level of new energy absorption.

[0003] To mitigate fluctuations in renewable energy output, current technologies primarily employ single energy storage systems for regulation. Pumped hydro storage systems offer advantages such as large capacity, long lifespan, and environmental friendliness, but suffer from slow response times and low regulation precision, making them ill-suited for handling high-frequency transient fluctuations. Electrochemical energy storage systems (such as lithium-ion battery storage) offer fast response times and high regulation precision, effectively mitigating high-frequency fluctuations, but are hampered by high capacity costs, limited cycle life, and poor economic viability for large-scale energy storage. The limited regulation capabilities of single energy storage systems cannot simultaneously meet the dual demands of large-capacity low-frequency regulation and high-precision high-frequency mitigation, resulting in insufficient grid connection stability for renewable energy and poor system operational economics.

[0004] Furthermore, existing methods mostly employ simple filtering or empirical scheduling strategies, lacking refined decomposition and coordinated adjustment mechanisms for fluctuation characteristics across different time scales. This leads to low energy storage resource utilization efficiency and insufficient system operation economics. Moreover, existing optimization allocation methods often consider only a single objective, such as minimizing cost or fluctuation, without fully considering multi-dimensional indicators such as renewable energy curtailment rate, energy storage lifetime loss, and overall system economics. They also lack a hierarchical coordination mechanism across time scales, making it difficult to fully leverage the complementary advantages of the two types of energy storage, further impacting the reliability and economics of renewable energy grid connection. Therefore, a technical solution capable of achieving coordinated optimized allocation and scheduling of the two types of energy storage is urgently needed to address the shortcomings of existing technologies. Summary of the Invention

[0005] The purpose of this invention is to address the aforementioned problems in the existing technology by providing a collaborative optimization configuration method and system for smoothing out fluctuations in new energy output.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows:

[0007] Firstly, this invention proposes a collaborative optimization allocation method to smooth out fluctuations in new energy output, comprising:

[0008] S1. Based on the historical power output data of the new energy power generation system in the target area, obtain the fluctuating power gap sequence, and perform frequency domain decomposition on the fluctuating power gap sequence to divide the low-frequency trend power component and the high-frequency fluctuating power component.

[0009] S2. Allocate the low-frequency trend power component to the pumped storage system to form the planned output of the pumped storage system; calculate the interaction coupling power between the pumped storage system and the electrochemical energy storage system, and allocate the interaction coupling power and the high-frequency fluctuation power component to the electrochemical energy storage system to form the planned output of the electrochemical energy storage system.

[0010] S3. Based on the planned output demand of pumped storage system and electrochemical energy storage system, a multi-objective collaborative optimization configuration model is constructed with the joint optimization objectives of minimizing grid-connected power fluctuation residual, energy storage system life cycle cost, new energy curtailment rate and collaborative scheduling loss. The model is then solved to obtain the optimal capacity configuration scheme of the new energy system in the next scheduling cycle and the operation scheduling strategy at each time in the scheduling cycle.

[0011] In S2, the planned output of pumped storage is calculated using the following formula:

[0012] ;

[0013] ;

[0014] In the above formula, for The planned output of the pumped storage system at all times. For low-frequency trend power components, For the total scheduling cycle, for The actual output deviation is constantly limited by mechanical characteristics. The scheduling time step;

[0015] The planned output of the electrochemical energy storage is calculated using the following formula:

[0016] ;

[0017] ;

[0018] ;

[0019] In the above formula, for The total regulation power command undertaken by the electrochemical energy storage system at all times For high-frequency fluctuating power components, for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system The coupling adjustment coefficient is used to characterize the compensation ratio of electrochemical energy storage to the output deviation of pumped hydro storage. for Constant deviations in the planned execution of pumped storage systems for The state of charge of electrochemical energy storage at any given time. , These represent the minimum and maximum states of charge in electrochemical energy storage, respectively. for The actual output of the pumped storage system at all times. for The planned output of the pumped storage system at all times.

[0020] In S4, the objective function of the multi-objective collaborative optimization configuration model includes:

[0021] ;

[0022] ;

[0023] ;

[0024] ;

[0025] ;

[0026] In the above formula, The objective of the multi-objective collaborative optimization configuration model is... , , , These are the weight coefficients for the corresponding objectives. For grid-connected power fluctuation residuals, For the total lifecycle cost of energy storage systems, For the curtailment rate of new energy sources, To reduce the loss during coordinated scheduling, For the total scheduling cycle, for The final grid-connected power at any given moment, for The target power for grid connection at any given time. The investment cost of a pumped storage system, The investment cost of electrochemical energy storage systems, For the operation and maintenance costs of hybrid energy storage systems, for The curtailment power of the new energy system at any given time To schedule the time step, for The maximum predicted power that a new energy system can theoretically generate. for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system This is the additional depreciation cost factor incurred by the electrochemical energy storage system in response to interactive coupling commands;

[0027] The constraints of the multi-objective collaborative optimization configuration model include energy storage power capacity constraints, pumped storage power station output and energy evolution constraints, electrochemical energy storage system state of charge dynamic constraints, and interactive coupling constraints between pumped storage system and electrochemical energy storage system.

[0028] The energy storage capacity is:

[0029] ;

[0030] ;

[0031] In the above formula, This represents the maximum power capacity of the pumped storage system. This indicates taking the maximum value over the time set. for The planned output of the pumped storage system at all times. This represents the maximum power capacity of the electrochemical energy storage system. for The total regulation power command undertaken by the electrochemical energy storage system at any given time;

[0032] The output and energy evolution constraints of the pumped storage power station include:

[0033] ;

[0034] ;

[0035] ;

[0036] ;

[0037] In the above formula, for The power generation capacity of the pumped storage power station at all times. , These represent the minimum and maximum generating capacities of a pumped storage power station. for The pumping power of a pumped storage power station at all times. , These represent the minimum and maximum pumping power of a pumped storage power station. for The energy storage capacity of a pumped-storage hydroelectric power station at all times. , These represent the minimum and maximum energy storage capacities of a pumped storage power station. The efficiency of the pumping process. The efficiency of the power generation process;

[0038] The dynamic constraints on the state of charge of the electrochemical energy storage system include:

[0039] ;

[0040] ;

[0041] In the above formula, for The state of charge of electrochemical energy storage at any given time. For charging efficiency, for The charging power of electrochemical energy storage at all times. To schedule the time step, The rated capacity of electrochemical energy storage, for The discharge power of electrochemical energy storage at any given time. For discharge efficiency, , These represent the minimum and maximum states of charge for electrochemical energy storage, respectively.

[0042] The interaction coupling constraint between the pumped hydro storage system and the electrochemical energy storage system is:

[0043] ;

[0044] In the above formula, for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system The coupling adjustment coefficient is used to characterize the compensation ratio of electrochemical energy storage to the output deviation of pumped hydro storage. for Constant deviations in the planned execution of pumped storage systems for The state of charge of electrochemical energy storage at any given time. , These represent the minimum and maximum states of charge for electrochemical energy storage, respectively.

[0045] The method further includes:

[0046] S4. Based on the real-time operation monitoring results of the scheduling strategy at each moment within the scheduling cycle, execute the adaptive feedback correction process.

[0047] S4 includes:

[0048] S41. Real-time monitoring of the deviation between the final grid-connected power and the grid-connected target power at each moment within the scheduling cycle, the deviation between the state of charge of electrochemical energy storage and the safe operating range, and the proportion of high-frequency fluctuation power components in the fluctuation spectrum of new energy output, and weighted calculation of these three data to obtain the deviation evaluation index at each moment.

[0049] S42. Determine whether the deviation evaluation index at each time exceeds the preset threshold. When the deviation evaluation index does not exceed the preset threshold, the current optimal capacity configuration scheme and operation scheduling strategy are the optimal scheme to smooth out the fluctuation of new energy output. When the deviation evaluation index at a certain time exceeds the preset threshold, execute the long / short cycle hierarchical feedback correction.

[0050] The hierarchical feedback correction for long / short cycles is as follows:

[0051] Within a short period, the weight coefficients of the objective function of the multi-objective collaborative optimization configuration model, the boundary thresholds of the constraints, and the frequency thresholds or boundaries of the power gap frequency domain decomposition are adaptively updated through a negative feedback mechanism, and the current scheduling strategy continues to be executed. Within a long period, the deviation evaluation index is accumulated and statistically analyzed within a scheduling cycle based on the moment when the deviation evaluation index exceeds the preset threshold, forming a comprehensive evaluation index. The system operation effect is evaluated based on this comprehensive evaluation index. When the evaluation results show that the current capacity configuration is difficult to meet the operation requirements, the capacity configuration parameters are corrected, and the corrected capacity configuration parameters are input into the updated multi-objective collaborative optimization configuration model to solve and generate the capacity configuration scheme and operation scheduling strategy for the next scheduling cycle starting from the current moment.

[0052] S1 includes:

[0053] S11. Calculate the fluctuating power gap sequence using the following formula:

[0054] ;

[0055] In the above formula, for The fluctuating power gap sequence at time t, for The actual output sequence of new energy sources at any given time. for The target power for grid connection at any given time;

[0056] S12. Decompose the fluctuating power gap sequence into modal components with different center frequencies, and set frequency thresholds. The center frequency is lower than The modal components are divided into low-frequency trend power components. The center frequency is higher than The modal components are divided into high-frequency fluctuation power components. .

[0057] Secondly, this invention proposes a collaborative optimization configuration system for smoothing out fluctuations in new energy output, including a fluctuating power gap sequence decomposition module, a power component allocation module, and a multi-objective collaborative optimization configuration model construction module;

[0058] The fluctuating power gap sequence decomposition module is used to obtain the fluctuating power gap sequence based on the historical output data of the new energy power generation system in the target area, and to perform frequency domain decomposition on the fluctuating power gap sequence to divide it into low-frequency trend power components and high-frequency fluctuating power components.

[0059] The power component allocation module is used to allocate the low-frequency trend power component to the pumped storage system to form the planned output of the pumped storage system; calculate the interactive coupling power between the pumped storage system and the electrochemical energy storage system, and allocate the interactive coupling power and the high-frequency fluctuation power component to the electrochemical energy storage system to form the planned output of the electrochemical energy storage system.

[0060] The multi-objective collaborative optimization configuration model construction module is used to construct a multi-objective collaborative optimization configuration model based on the planned output demand of pumped storage system and electrochemical energy storage system, with the joint optimization objectives of minimizing grid-connected power fluctuation residual, energy storage system life cycle cost, new energy curtailment rate and collaborative scheduling loss. The module then solves the model to obtain the optimal capacity configuration scheme for the new energy system in the next scheduling cycle and the operation scheduling strategy at each time point within that scheduling cycle.

[0061] The fluctuating power gap sequence decomposition module includes a fluctuating power gap sequence calculation unit and a modal component partitioning unit.

[0062] The fluctuating power gap sequence calculation unit is used to calculate the fluctuating power gap sequence using the following formula:

[0063] ;

[0064] In the above formula, for The fluctuating power gap sequence at time t, for The actual output sequence of new energy sources at any given time. for The target power for grid connection at any given time;

[0065] The modal component segmentation unit is used to decompose the fluctuating power gap sequence into modal components with different center frequencies, and to set frequency thresholds. The center frequency is lower than The modal components are divided into low-frequency trend power components. The center frequency is higher than The modal components are divided into high-frequency fluctuation power components. .

[0066] The power component allocation module includes a pumped storage planned output calculation unit and an electrochemical energy storage planned output calculation unit.

[0067] The pumped storage planned output calculation unit is used to calculate the planned output of the pumped storage using the following formula:

[0068] ;

[0069] ;

[0070] In the above formula, for The planned output of the pumped storage system at all times. For low-frequency trend power components, For the total scheduling cycle, for The actual output deviation is constantly limited by mechanical characteristics. The scheduling time step;

[0071] The electrochemical energy storage planned output calculation unit is used to calculate the planned output of electrochemical energy storage using the following formula:

[0072] ;

[0073] ;

[0074] ;

[0075] In the above formula, for The total regulation power command undertaken by the electrochemical energy storage system at all times For high-frequency fluctuating power components, for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system The coupling adjustment coefficient is used to characterize the compensation ratio of electrochemical energy storage to the output deviation of pumped hydro storage. for Constant deviations in the planned execution of pumped storage systems for The state of charge of electrochemical energy storage at any given time. , These represent the minimum and maximum states of charge in electrochemical energy storage, respectively. for The actual output of the pumped storage system at all times. for The planned output of the pumped storage system at all times.

[0076] The multi-objective collaborative optimization configuration model construction module includes an objective function construction unit and a constraint condition construction unit;

[0077] The objective function construction unit is used to construct the objective function of the following multi-objective collaborative optimization configuration model:

[0078] ;

[0079] ;

[0080] ;

[0081] ;

[0082] ;

[0083] In the above formula, The objective of the multi-objective collaborative optimization configuration model is... , , , These are the weight coefficients for the corresponding objectives. For grid-connected power fluctuation residuals, For the total lifecycle cost of energy storage systems, For the curtailment rate of new energy sources, To reduce the loss during coordinated scheduling, For the total scheduling cycle, for The final grid-connected power at any given moment, for The target power for grid connection at any given time. The investment cost of a pumped storage system, The investment cost of electrochemical energy storage systems, For the operation and maintenance costs of hybrid energy storage systems, for The curtailment power of the new energy system at any given time To schedule the time step, for The maximum predicted power that a new energy system can theoretically generate. for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system This is the additional depreciation cost factor incurred by the electrochemical energy storage system in response to interactive coupling commands;

[0084] The constraint construction unit is used to construct the constraints of the multi-objective collaborative optimization configuration model, including energy storage power capacity constraints, pumped storage power station output and energy evolution constraints, electrochemical energy storage system state of charge dynamic constraints, and interactive coupling constraints between pumped storage system and electrochemical energy storage system.

[0085] The energy storage capacity is:

[0086] ;

[0087] ;

[0088] In the above formula, This represents the maximum power capacity of the pumped storage system. This indicates taking the maximum value over the time set. for The planned output of the pumped storage system at all times. This represents the maximum power capacity of the electrochemical energy storage system. for The total regulation power command undertaken by the electrochemical energy storage system at any given time;

[0089] The output and energy evolution constraints of the pumped storage power station include:

[0090] ;

[0091] ;

[0092] ;

[0093] ;

[0094] In the above formula, for The power generation capacity of the pumped storage power station at all times. , These represent the minimum and maximum generating capacities of a pumped storage power station. for The pumping power of a pumped storage power station at all times. , These represent the minimum and maximum pumping power of a pumped storage power station. for The energy storage capacity of a pumped-storage hydroelectric power station at all times. , These represent the minimum and maximum energy storage capacities of a pumped storage power station. The efficiency of the pumping process. The efficiency of the power generation process;

[0095] The dynamic constraints on the state of charge of the electrochemical energy storage system include:

[0096] ;

[0097] ;

[0098] In the above formula, for The state of charge of electrochemical energy storage at any given time. For charging efficiency, for The charging power of electrochemical energy storage at all times. To schedule the time step, The rated capacity of electrochemical energy storage, for The discharge power of electrochemical energy storage at any given time. For discharge efficiency, , These represent the minimum and maximum states of charge for electrochemical energy storage, respectively.

[0099] The interaction coupling constraint between the pumped hydro storage system and the electrochemical energy storage system is:

[0100] ;

[0101] In the above formula, for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system The coupling adjustment coefficient is used to characterize the compensation ratio of electrochemical energy storage to the output deviation of pumped hydro storage. for Constant deviations in the planned execution of pumped storage systems for The state of charge of electrochemical energy storage at any given time. , These represent the minimum and maximum states of charge for electrochemical energy storage, respectively.

[0102] The system also includes an adaptive feedback correction module;

[0103] The adaptive feedback correction module is used to perform an adaptive feedback correction process based on the real-time operation monitoring results of the scheduling strategy at each time within the scheduling cycle, including a deviation evaluation index real-time monitoring unit and a judgment unit.

[0104] The deviation evaluation index real-time monitoring unit is used to monitor in real time the deviation between the final grid-connected power and the grid-connected target power at each moment within the scheduling cycle, the degree of deviation between the state of charge of electrochemical energy storage and the safe operating range, and the proportion of high-frequency fluctuation power components in the fluctuation spectrum of new energy output, and to calculate the deviation evaluation index at each moment by weighting these three data.

[0105] The determination unit is used to determine whether the deviation evaluation index at each time exceeds the preset threshold. When the deviation evaluation index does not exceed the preset threshold, the current optimal capacity configuration scheme and operation scheduling strategy are the optimal scheme to smooth out the fluctuation of new energy output. When the deviation evaluation index at a certain time exceeds the preset threshold, long / short cycle hierarchical feedback correction is executed.

[0106] The hierarchical feedback correction for long / short cycles is as follows:

[0107] Within a short period, the weight coefficients of the objective function of the multi-objective collaborative optimization configuration model, the boundary thresholds of the constraints, and the frequency thresholds or boundaries of the power gap frequency domain decomposition are adaptively updated through a negative feedback mechanism, and the current scheduling strategy continues to be executed. Within a long period, the deviation evaluation index is accumulated and statistically analyzed within a scheduling cycle based on the moment when the deviation evaluation index exceeds the preset threshold, forming a comprehensive evaluation index. The system operation effect is evaluated based on this comprehensive evaluation index. When the evaluation results show that the current capacity configuration is difficult to meet the operation requirements, the capacity configuration parameters are corrected, and the corrected capacity configuration parameters are input into the updated multi-objective collaborative optimization configuration model to solve and generate the capacity configuration scheme and operation scheduling strategy for the next scheduling cycle starting from the current moment.

[0108] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0109] 1. This invention proposes a collaborative optimization configuration method and system for smoothing power output fluctuations of new energy sources. The method constructs an interactive coupling model between pumped storage systems and electrochemical energy storage systems. The electrochemical energy storage system can be used to compensate for the power output deviation of pumped storage caused by mechanical limitations. At the same time, when the state of charge of the electrochemical energy storage system touches the boundary, deviation feedback is triggered, realizing dynamic adaptation and complementary adjustment of pumped storage and electrochemical energy storage. This effectively avoids the shortcomings of single energy storage regulation and significantly improves the accuracy and stability of smoothing power output fluctuations of new energy sources.

[0110] 2. This invention proposes a collaborative optimization configuration method and system for smoothing fluctuations in renewable energy output. It constructs a four-dimensional multi-objective optimization model that covers residual power fluctuations, energy storage lifecycle costs, renewable energy curtailment rates, and collaborative scheduling losses. This model overcomes the limitations of single-objective or dual-objective optimization and achieves multiple objectives, including reducing energy storage costs, increasing renewable energy absorption rates, and minimizing scheduling losses, while ensuring stable grid-connected power. This significantly improves the economic efficiency and resource utilization efficiency of the system operation.

[0111] 3. This invention proposes a collaborative optimization configuration method and system for smoothing fluctuations in renewable energy output. It establishes a real-time evaluation and hierarchical feedback mechanism for operating status, which can adaptively adjust model parameters in the short period based on deviation evaluation indicators, and correct energy storage capacity configuration and re-optimize scheduling strategies in the long period. This enables energy storage collaborative scheduling to continuously adapt to the fluctuations and uncertainties in renewable energy output, improve grid connection control accuracy and the adaptability and robustness of system operation. Attached Figure Description

[0112] Figure 1 This is an overall flowchart of the method described in this invention.

[0113] Figure 2 The diagram shows the frequency component partitioning results of the fluctuation power gap sequence described in Example 1.

[0114] Figure 3 This is a schematic diagram illustrating the effect of smoothing the power output of new energy sources and grid-connected power as described in Example 1.

[0115] Figure 4 This is a schematic diagram of the hybrid energy storage power response and battery SOC evolution described in Example 1.

[0116] Figure 5 This is a structural diagram of the system described in this invention. Detailed Implementation

[0117] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings.

[0118] This invention proposes a collaborative optimization configuration method and system for mitigating fluctuations in renewable energy output. It collects historical renewable energy output data from the target region to construct a power gap sequence for renewable energy output fluctuations. Adaptive variational mode decomposition (ADMD) is used to decompose the power gap in the frequency domain, and low-frequency trend components and high-frequency fluctuation components are divided according to thresholds. Based on an interactively coupled power and cross-timescale hierarchical coordination and adjustment method, the power gap components are collaboratively decomposed and allocated. A multi-objective collaborative optimization configuration model is constructed, transforming the optimization problem into a mixed-integer linear programming model for solution, determining the optimal capacity configuration scheme for the renewable energy system in the next scheduling cycle and the operation scheduling strategy at each time point within that cycle. An adaptive feedback correction process is executed based on real-time operation monitoring results. Through the complementary synergy of pumped hydro storage and electrochemical energy storage at different time scales, efficient mitigation of renewable energy fluctuations and optimized configuration of energy storage capacity are achieved, improving the dynamic adaptation and complementary adjustment capabilities between the two types of energy storage.

[0119] Example 1:

[0120] like Figure 1 As shown, a collaborative optimization allocation method for smoothing fluctuations in new energy output is carried out in the following steps:

[0121] 1. Based on the historical power output data of the new energy power generation system in the target area, the fluctuating power gap sequence is obtained, and the fluctuating power gap sequence is decomposed in the frequency domain to divide the low-frequency trend power component and the high-frequency fluctuating power component.

[0122] Historical wind and solar power output data for the target area over the past year or more were collected. The time resolution of the collected data can be at the minute or hour level, and the data was aligned according to a unified timestamp. Outliers were detected using the 3σ criterion and replaced with the mean. Outliers exceeding the range [μ-3σ, μ+3σ] (where μ is the data mean and σ is the standard deviation) were identified and removed. Missing data were repaired using linear interpolation to ensure data integrity. Finally, the output data was normalized and mapped to the [0,1] interval to obtain a standardized sequence of actual renewable energy output. ;

[0123] Determine the target grid connection power based on grid dispatch requirements and system capacity. It meets the constraints of minimum grid-connected power and maximum acceptance capacity of the power grid.

[0124] Calculate the difference between the actual power output sequence of new energy sources and the grid-connected target power, and construct the power gap sequence of new energy output fluctuations:

[0125] ;

[0126] In the above formula, for The fluctuating power gap sequence at time t, for The actual output sequence of new energy sources at any given time. for The target power for grid connection at any given time;

[0127] like , indicating in At any given time, the actual power generation of the new energy power plant exceeds the grid connection target power required by the power grid. At this point, the system has excess energy, and the energy storage system (pumped hydro storage or electrochemical energy storage) tends to enter a charging / pumping state to convert the excess electrical energy into potential energy or chemical energy for storage; if , indicating in At any given time, the actual power generation of the new energy power plant is lower than the grid connection target power required by the grid, which cannot meet the dispatching needs. The energy storage system tends to enter the discharge / generation state to supplement the grid with energy to make up for the gap.

[0128] The wave power gap sequence is decomposed into modal components with different center frequencies using adaptive variational mode decomposition (VMD) technology, specifically including:

[0129] VMD parameters are set as follows: Based on the typical frequency domain characteristics of renewable energy output fluctuations (the fluctuation period of wind / solar power typically covers minutes to hours), the preset number of modal components K=4 (can be adjusted according to the fluctuation complexity of the actual scenario; for example, K=5 can be set when fluctuations are severe under extreme weather conditions); the penalty factor α is set to 2000 (this parameter determines the smoothness of the decomposed signal; the larger α is, the narrower the bandwidth of the component and the stronger the frequency domain focus, adapting to the separation requirements of high-frequency instantaneous fluctuations and low-frequency trend changes in renewable energy power shortages); the noise margin τ is set to 1e-7 (used to control the convergence accuracy of the decomposition process, ensuring that the superposition error of each modal component is sufficiently small).

[0130] Set frequency threshold It is 0.02Hz, and the center frequency is lower than The modal components are divided into low-frequency trend power components. The center frequency is higher than The modal components are divided into high-frequency fluctuation power components. If the response characteristics of the energy storage device change, adjustments can be made synchronously. ;

[0131] The frequency component partitioning results of the fluctuating power gap sequence are as follows: Figure 2 As shown, the low-frequency trend power component corresponds to the slower-changing power deviation, reflecting the trend over a longer time scale, while the high-frequency fluctuation power component corresponds to the faster-changing power fluctuation, reflecting the characteristics of changes over a shorter time scale. Time scale division is achieved by mapping the frequency scale to the time scale.

[0132] 2. Allocate the low-frequency trend power component to the pumped storage system to form the planned output of the pumped storage system; calculate the interaction coupling power between the pumped storage system and the electrochemical energy storage system, and allocate the interaction coupling power and the high-frequency fluctuation power component to the electrochemical energy storage system to form the planned output of the electrochemical energy storage system.

[0133] A hierarchical coordination and regulation method across time scales is adopted. Regulation tasks are assigned according to the frequency band of the power gap and the differences in the capacity of energy storage systems. The regulation requirements of different energy storage systems are determined, and complementary coordination between the two types of energy storage is achieved by introducing interactive coupling power.

[0134] In the upper-level planning and regulation, the low-frequency trend power component is allocated to the pumped storage system to form the planned output of pumped storage:

[0135] ;

[0136] Energy balance constraints for pumped storage systems are constructed, taking into account actual output deviations.

[0137] ;

[0138] In the above formula, for The planned output of the pumped storage system at all times. For low-frequency trend power components, For the total scheduling cycle, for The actual output deviation is constantly limited by mechanical characteristics. The scheduling time step;

[0139] In the real-time regulation at the lower level, the high-frequency fluctuation power component is allocated to the electrochemical energy storage system. At the same time, an interactive coupling power relationship is established between the pumped storage system and the electrochemical energy storage system. When there is a deviation between the actual output and the planned output of the pumped storage system, the electrochemical energy storage system compensates and regulates according to the coupling coefficient, thereby achieving coordinated regulation across different time scales.

[0140] The total planned output of the electrochemical energy storage system is obtained by superimposing high-frequency fluctuation components and interactively coupled power, and its output is limited by real-time constraints on the state of charge (SOC).

[0141] ;

[0142] ;

[0143] During scheduling The deviation between planned and actual output of a pumped storage system in the previous scheduling cycle is defined as...

[0144] ;

[0145] In the above formula, for The total regulation power command undertaken by the electrochemical energy storage system at all times For high-frequency fluctuating power components, for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system The coupling adjustment coefficient is used to characterize the compensation ratio of electrochemical energy storage to the output deviation of pumped hydro storage. Its value is determined based on the electrochemical energy storage system in The SOC, energy margin, and safety constraints at any given time are adaptively determined in this embodiment. The value range is [0, 0.8]. or hour, Stop compensation. for Constant deviations in the planned execution of pumped storage systems for The state of charge of electrochemical energy storage at any given time. , These represent the minimum and maximum states of charge in electrochemical energy storage, respectively. for The actual output of the pumped storage system at all times. for The planned output of the pumped storage system at all times.

[0146] and This reflects the system's adjustment needs at different time scales. The pumped storage system and the electrochemical energy storage system adjust their outputs according to their respective plans, achieving complementary mitigation of fluctuations in new energy output at different frequency bands. When the electrochemical energy storage system cannot fully bear the interactive coupling power due to operational constraints, the remaining uncompensated power is included in the grid-connected power residual, which is used for rolling correction in the next scheduling cycle. The grid-connected power residual refers to the instantaneous deviation between the actual grid-connected power and the target grid-connected power at a certain moment after the energy storage system participates in the adjustment, and is used to reflect the power deviation under the real-time operating state of the system.

[0147] 3. Based on the planned output demand of pumped storage and electrochemical energy storage systems, a multi-objective collaborative optimization configuration model is constructed with the joint optimization objectives of minimizing grid-connected power fluctuation residuals, the total life cycle cost of energy storage systems, the renewable energy curtailment rate, and collaborative scheduling losses. The model is then solved to obtain the optimal capacity configuration scheme for the renewable energy system in the next scheduling cycle and the operation scheduling strategy at each time point within that scheduling cycle.

[0148] A multi-objective function is established with the joint optimization objectives of minimizing grid-connected power fluctuation residuals, minimizing the total life cycle cost of energy storage systems, minimizing renewable energy curtailment rates, and minimizing collaborative scheduling losses.

[0149] The objective functions of the multi-objective collaborative optimization configuration model include:

[0150] ;

[0151] The residual objective term for grid-connected power fluctuation measures the deviation between the final grid-connected power and the target grid-connected power. It is an objective function index in the optimization model used to evaluate the smoothing effect of grid-connected power, describing the overall fluctuation of grid-connected power relative to the target grid-connected power throughout the entire scheduling cycle. Its expression is:

[0152] ;

[0153] ;

[0154] The renewable energy curtailment rate is used to measure the utilization efficiency of renewable energy power generation resources, and its expression is:

[0155] ;

[0156] ;

[0157] In the above formula, The objective of the multi-objective collaborative optimization configuration model is... , , , These are the weighting coefficients for the corresponding targets, which are dynamically updated based on grid-connected power deviation and energy storage state of charge, and satisfy the following conditions: If the primary task is to smooth out fluctuations, then the following can be set: , , , , For grid-connected power fluctuation residuals, For the total lifecycle cost of energy storage systems, For the curtailment rate of new energy sources, To reduce the loss during coordinated scheduling, For the total scheduling cycle, for The final grid-connected power at any given moment, for The target power for grid connection at any given time. The investment cost of a pumped storage system, The investment cost of electrochemical energy storage systems, For the operation and maintenance costs of hybrid energy storage systems, for The curtailment power of the new energy system at any given time, that is... The renewable energy system is already at energy saturation and cannot be absorbed, ultimately forcing it to discard the power it has been given. To schedule the time step, for The maximum predicted power that a new energy system can theoretically generate. for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system This is the additional depreciation cost factor incurred by the electrochemical energy storage system in response to interactive coupling commands;

[0158] The constraints of the multi-objective collaborative optimization configuration model include energy storage power capacity constraints, pumped storage power station output and energy evolution constraints, electrochemical energy storage system state of charge dynamic constraints, and interactive coupling constraints between pumped storage system and electrochemical energy storage system.

[0159] The power capacity of the pumped hydro storage system and the electrochemical energy storage system should meet their planned output demand during the dispatch cycle. The energy storage power capacity is:

[0160] ;

[0161] ;

[0162] In the above formula, This represents the maximum power capacity of the pumped storage system. This indicates taking the maximum value over the time set, that is, the maximum value among all times within the scheduling period. for The planned output of the pumped storage system at all times. This represents the maximum power capacity of the electrochemical energy storage system. for The total regulation power command undertaken by the electrochemical energy storage system at any given time;

[0163] The output and energy evolution constraints of the pumped storage power station include power generation constraints, pumping power constraints, energy storage capacity constraints, and energy state evolution constraints.

[0164] The power generation constraint is:

[0165] ;

[0166] Pumping power constraints are:

[0167] ;

[0168] Energy storage capacity constraints are:

[0169] ;

[0170] The energy state evolution constraint is:

[0171] ;

[0172] In the above formula, for The power generation capacity of the pumped storage power station at all times. , These represent the minimum and maximum generating capacities of a pumped storage power station. for The pumping power of a pumped storage power station at all times. , These represent the minimum and maximum pumping power of a pumped storage power station. for The energy storage capacity of a pumped-storage hydroelectric power station at all times. , These represent the minimum and maximum energy storage capacities of a pumped storage power station. The efficiency of the pumping process. The efficiency of the power generation process;

[0173] The dynamic constraints of the state of charge (SOC) of the electrochemical energy storage system include SOC state evolution constraints and SOC operation constraints.

[0174] The SOC state evolution constraint is:

[0175] ;

[0176] SOC (State of Charge) operating limits (typically 10%-90%) are set to prevent battery life degradation caused by overcharging or over-discharging.

[0177] ;

[0178] In the above formula, for The state of charge of electrochemical energy storage at any given time. For charging efficiency, take , for The charging power of electrochemical energy storage at all times. To schedule the time step, The rated capacity of electrochemical energy storage, for The discharge power of electrochemical energy storage at any given time. For discharge efficiency, take , , These represent the minimum and maximum states of charge for electrochemical energy storage, respectively.

[0179] Based on the planned execution deviation of the pumped hydro storage system and the available adjustment margin of the electrochemical energy storage system, an interactive coupling relationship between the two types of energy storage systems is established. The interactive coupling constraint between the pumped hydro storage system and the electrochemical energy storage system is as follows:

[0180] ;

[0181] In the above formula, for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system The coupling adjustment coefficient is used to characterize the compensation ratio of electrochemical energy storage to the output deviation of pumped hydro storage. for Constant deviations in the planned execution of pumped storage systems for The state of charge of electrochemical energy storage at any given time. , These represent the minimum and maximum states of charge for electrochemical energy storage, respectively.

[0182] By introducing energy storage operation state variables and 0-1 logical variables, and employing linearization techniques to handle nonlinear terms in the objective function and constraints, the multi-objective optimization problem is uniformly transformed into a mixed-integer linear programming (MILP) model. A branch-and-bound algorithm is then used to globally optimize the MILP model, obtaining the optimal capacity configuration scheme for the next scheduling cycle of the new energy system and the operation scheduling strategy at each time point within that scheduling cycle. The effect of smoothing out new energy output and grid-connected power is as follows: Figure 3 As shown, the original output curve of the new energy source, the target grid-connected power curve, and the grid-connected power curve after smoothing by the hybrid energy storage system are displayed; the power response of the hybrid energy storage system and the evolution of battery SOC are shown as follows. Figure 4 As shown, the dynamic changes in the power response of the pumped hydro storage system, the power response of the electrochemical energy storage system, and the state of charge (SOC) of the battery are illustrated.

[0183] 4. Based on the real-time operation monitoring results of the scheduling strategy at each time point within the scheduling cycle, an adaptive feedback correction process is executed.

[0184] The final grid-connected power is output based on the optimal configuration scheme:

[0185] ;

[0186] In the above formula, for The final grid-connected power at any given moment, for The maximum predicted power that a new energy system can theoretically generate. for The curtailment power of the new energy system at any given time for The pumped storage system is constantly generating power. for The preset regulation power of electrochemical energy storage is designed to smooth out high-frequency fluctuations. for The interactive coupling power between the pumped hydro storage system and the electrochemical energy storage system at all times;

[0187] The deviation between the final grid-connected power and the grid-connected target power at each moment within the scheduling cycle, the deviation between the state of charge of electrochemical energy storage and the safe operating range [0.1, 0.9], and the proportion of high-frequency fluctuating power components in the fluctuation spectrum of new energy output are monitored in real time. The deviation evaluation index at each moment is obtained by weighting these three data. The weights of each monitoring data are set to 0.5, 0.3, and 0.2, respectively, and the index value range is [0, 1]. The larger the value, the greater the operating deviation.

[0188] Determine whether the deviation evaluation index at each time exceeds the preset threshold of 0.6. When the deviation evaluation index does not exceed the preset threshold, the current optimal capacity configuration scheme and operation scheduling strategy are the optimal scheme to smooth out the fluctuation of new energy output. When the deviation evaluation index at a certain time exceeds the preset threshold, execute the long / short cycle hierarchical feedback correction.

[0189] The hierarchical feedback correction for long / short cycles is as follows:

[0190] Within a short period (hourly), the weight coefficients of the objective function of the multi-objective collaborative optimization configuration model, the boundary thresholds of the constraints, and the decomposition scale or frequency boundary of the power gap frequency domain decomposition are adaptively updated through a negative feedback mechanism, and the current scheduling strategy continues to be executed, specifically including:

[0191] After triggering short-cycle negative feedback correction, the weight coefficients of the objective function are adjusted as follows: when the grid-connected power deviation increases, the weight of the power fluctuation smoothing objective is increased; when the energy storage state of charge is close to the upper and lower limits, the weight of the energy storage operation safety objective is increased; when the high-frequency fluctuation of new energy output increases, the weight of the high-frequency fluctuation regulation related objective is increased.

[0192] The boundary thresholds of the constraints are adjusted as follows: when the state of charge of the energy storage system is continuously close to the upper or lower limit, the boundary thresholds of the energy storage operating range are appropriately tightened or relaxed through the negative feedback mechanism, so that the energy storage system can be kept in a safer and more stable operating range; when the system power regulation demand increases, the adjustable power range of the energy storage system can be appropriately expanded; when the system operation tends to be stable, it is restored to the original constraint range.

[0193] The update of the decomposition scale or frequency boundary for power notch frequency domain decomposition is as follows: the decomposition scale refers to the parameter used to adjust the granularity of the power notch signal frequency domain division. In this invention, this is achieved by setting a frequency threshold. The modal components obtained from variational mode decomposition are divided into low-frequency trend components and high-frequency fluctuation components. Therefore, the frequency threshold is... This can be seen as a specific implementation of the decomposition scale; the frequency boundary refers to the dividing line between different frequency bands, namely the low-frequency trend range and the high-frequency fluctuation range; when the proportion of high-frequency fluctuation energy in new energy output increases, the dividing threshold between low frequency and high frequency is appropriately reduced through the negative feedback mechanism, so that more fluctuation components are divided into high-frequency components, thereby enhancing the ability of electrochemical energy storage to regulate high-frequency fluctuations; when the fluctuation of new energy output tends to be flat, the frequency dividing threshold is appropriately increased, so that more power components are regulated by the pumped storage system;

[0194] Over a long period (daily to monthly), based on the moment when the deviation evaluation index exceeds a preset threshold, the deviation evaluation index within a scheduling cycle is accumulated to form a comprehensive evaluation index. The comprehensive evaluation index is obtained by performing a time-weighted average of the deviation evaluation index at each moment within a scheduling cycle. The system operation effect is evaluated based on this comprehensive evaluation index. When the evaluation results indicate that the current capacity configuration is difficult to meet the operation requirements, the capacity configuration parameters are corrected, and the corrected capacity configuration parameters are input into the updated multi-objective collaborative optimization configuration model to solve and generate the capacity configuration scheme and operation scheduling strategy for the next scheduling cycle starting from the current moment.

[0195] The evaluation of system performance based on comprehensive evaluation indicators includes: when the comprehensive evaluation indicator is less than the threshold, it indicates that the current capacity configuration meets the operational requirements; when the comprehensive evaluation indicator is higher than the threshold, it indicates that the system capacity configuration has a large deviation, and further determination of the system's over-limit frequency is required. If the threshold is exceeded, it indicates that the deviation frequency is small (occasional) and belongs to random fluctuation. It may be an abnormal situation caused by extreme fluctuation conditions, unreasonable model parameter configuration, or operation constraints. If the threshold is exceeded and the deviation cannot be effectively suppressed after short-cycle scheduling parameter adjustment, it indicates that the deviation frequency is large (frequent). It indicates that the long-term regulation capability of the system is insufficient. It can be determined that the regulation capability of the current energy storage system has reached the capacity boundary. That is, the existing capacity configuration is difficult to meet the operation requirements and the capacity configuration parameters need to be corrected.

[0196] The over-limit frequency The following formula is used to calculate:

[0197] ;

[0198] The capacity configuration parameters include the energy capacity parameters of the pumped hydro storage system and the electrochemical energy storage system, as well as their corresponding power parameters. When the proportion of high-frequency fluctuation power components in the power output fluctuation spectrum of new energy exceeds the threshold, the power or capacity of the electrochemical energy storage system is increased; when the proportion of low-frequency trend components exceeds the threshold, the energy capacity of the pumped hydro storage system is increased.

[0199] Example 2:

[0200] like Figure 5 As shown, a collaborative optimization configuration system for smoothing fluctuations in new energy output includes a fluctuating power gap sequence decomposition module, a power component allocation module, and a multi-objective collaborative optimization configuration model construction module.

[0201] The fluctuating power gap sequence decomposition module is used to obtain the fluctuating power gap sequence based on the historical output data of the new energy power generation system in the target area, and to perform frequency domain decomposition on the fluctuating power gap sequence to divide it into low-frequency trend power components and high-frequency fluctuating power components.

[0202] The power component allocation module is used to allocate the low-frequency trend power component to the pumped storage system to form the planned output of the pumped storage system; calculate the interactive coupling power between the pumped storage system and the electrochemical energy storage system, and allocate the interactive coupling power and the high-frequency fluctuation power component to the electrochemical energy storage system to form the planned output of the electrochemical energy storage system.

[0203] The multi-objective collaborative optimization configuration model construction module is used to construct a multi-objective collaborative optimization configuration model based on the planned output demand of pumped storage system and electrochemical energy storage system, with the joint optimization objectives of minimizing grid-connected power fluctuation residual, energy storage system life cycle cost, new energy curtailment rate and collaborative scheduling loss. The module then solves the model to obtain the optimal capacity configuration scheme for the new energy system in the next scheduling cycle and the operation scheduling strategy at each time point within that scheduling cycle.

[0204] The fluctuating power gap sequence decomposition module includes a fluctuating power gap sequence calculation unit and a modal component partitioning unit.

[0205] The fluctuating power gap sequence calculation unit is used to calculate the fluctuating power gap sequence using the following formula:

[0206] ;

[0207] In the above formula, for The fluctuating power gap sequence at time t, for The actual output sequence of new energy sources at any given time. for The target power for grid connection at any given time;

[0208] The modal component segmentation unit is used to decompose the fluctuating power gap sequence into modal components with different center frequencies, and to set frequency thresholds. The center frequency is lower than The modal components are divided into low-frequency trend power components. The center frequency is higher than The modal components are divided into high-frequency fluctuation power components. .

[0209] The power component allocation module includes a pumped storage planned output calculation unit and an electrochemical energy storage planned output calculation unit.

[0210] The pumped storage planned output calculation unit is used to calculate the planned output of the pumped storage using the following formula:

[0211] ;

[0212] ;

[0213] In the above formula, for The planned output of the pumped storage system at all times. For low-frequency trend power components, For the total scheduling cycle, for The actual output deviation is constantly limited by mechanical characteristics. The scheduling time step;

[0214] The electrochemical energy storage planned output calculation unit is used to calculate the planned output of electrochemical energy storage using the following formula:

[0215] ;

[0216] ;

[0217] ;

[0218] In the above formula, for The total regulation power command undertaken by the electrochemical energy storage system at all times For high-frequency fluctuating power components, for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system The coupling adjustment coefficient is used to characterize the compensation ratio of electrochemical energy storage to the output deviation of pumped hydro storage. for Constant deviations in the planned execution of pumped storage systems for The state of charge of electrochemical energy storage at any given time. , These represent the minimum and maximum states of charge in electrochemical energy storage, respectively. for The actual output of the pumped storage system at all times. for The planned output of the pumped storage system at all times.

[0219] The multi-objective collaborative optimization configuration model construction module includes an objective function construction unit and a constraint condition construction unit;

[0220] The objective function construction unit is used to construct the objective function of the following multi-objective collaborative optimization configuration model:

[0221] ;

[0222] ;

[0223] ;

[0224] ;

[0225] ;

[0226] In the above formula, The objective of the multi-objective collaborative optimization configuration model is... , , , These are the weight coefficients for the corresponding objectives. For grid-connected power fluctuation residuals, For the total lifecycle cost of energy storage systems, For the curtailment rate of new energy sources, To reduce the loss during coordinated scheduling, For the total scheduling cycle, for The final grid-connected power at any given moment, for The target power for grid connection at any given time. The investment cost of a pumped storage system, The investment cost of electrochemical energy storage systems, For the operation and maintenance costs of hybrid energy storage systems, for The curtailment power of the new energy system at any given time To schedule the time step, for The maximum predicted power that a new energy system can theoretically generate. for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system This is the additional depreciation cost factor incurred by the electrochemical energy storage system in response to interactive coupling commands;

[0227] The constraint construction unit is used to construct the constraints of the multi-objective collaborative optimization configuration model, including energy storage power capacity constraints, pumped storage power station output and energy evolution constraints, electrochemical energy storage system state of charge dynamic constraints, and interactive coupling constraints between pumped storage system and electrochemical energy storage system.

[0228] The energy storage capacity is:

[0229] ;

[0230] ;

[0231] In the above formula, This represents the maximum power capacity of the pumped storage system. This indicates taking the maximum value over the time set. for The planned output of the pumped storage system at all times. This represents the maximum power capacity of the electrochemical energy storage system. for The total regulation power command undertaken by the electrochemical energy storage system at any given time;

[0232] The output and energy evolution constraints of the pumped storage power station include:

[0233] ;

[0234] ;

[0235] ;

[0236] ;

[0237] In the above formula, for The power generation capacity of the pumped storage power station at all times. , These represent the minimum and maximum generating capacities of a pumped storage power station. for The pumping power of a pumped storage power station at all times. , These represent the minimum and maximum pumping power of a pumped storage power station. for The energy storage capacity of a pumped-storage hydroelectric power station at all times. , These represent the minimum and maximum energy storage capacities of a pumped storage power station. The efficiency of the pumping process. The efficiency of the power generation process;

[0238] The dynamic constraints on the state of charge of the electrochemical energy storage system include:

[0239] ;

[0240] ;

[0241] In the above formula, for The state of charge of electrochemical energy storage at any given time. For charging efficiency, for The charging power of electrochemical energy storage at all times. To schedule the time step, The rated capacity of electrochemical energy storage, for The discharge power of electrochemical energy storage at any given time. For discharge efficiency, , These represent the minimum and maximum states of charge for electrochemical energy storage, respectively.

[0242] The interaction coupling constraint between the pumped hydro storage system and the electrochemical energy storage system is:

[0243] ;

[0244] In the above formula, for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system The coupling adjustment coefficient is used to characterize the compensation ratio of electrochemical energy storage to the output deviation of pumped hydro storage. for Constant deviations in the planned execution of pumped storage systems for The state of charge of electrochemical energy storage at any given time. , These represent the minimum and maximum states of charge for electrochemical energy storage, respectively.

[0245] The system also includes an adaptive feedback correction module;

[0246] The adaptive feedback correction module is used to perform an adaptive feedback correction process based on the real-time operation monitoring results of the scheduling strategy at each time within the scheduling cycle, including a deviation evaluation index real-time monitoring unit and a judgment unit.

[0247] The deviation evaluation index real-time monitoring unit is used to monitor in real time the deviation between the final grid-connected power and the grid-connected target power at each moment within the scheduling cycle, the degree of deviation between the state of charge of electrochemical energy storage and the safe operating range, and the proportion of high-frequency fluctuation power components in the fluctuation spectrum of new energy output, and to calculate the deviation evaluation index at each moment by weighting these three data.

[0248] The determination unit is used to determine whether the deviation evaluation index at each time exceeds the preset threshold. When the deviation evaluation index does not exceed the preset threshold, the current optimal capacity configuration scheme and operation scheduling strategy are the optimal scheme to smooth out the fluctuation of new energy output. When the deviation evaluation index at a certain time exceeds the preset threshold, long / short cycle hierarchical feedback correction is executed.

[0249] The hierarchical feedback correction for long / short cycles is as follows:

[0250] Within a short period, the weight coefficients of the objective function of the multi-objective collaborative optimization configuration model, the boundary thresholds of the constraints, and the frequency thresholds or boundaries of the power gap frequency domain decomposition are adaptively updated through a negative feedback mechanism, and the current scheduling strategy continues to be executed. Within a long period, the deviation evaluation index is accumulated and statistically analyzed within a scheduling cycle based on the moment when the deviation evaluation index exceeds the preset threshold, forming a comprehensive evaluation index. The system operation effect is evaluated based on this comprehensive evaluation index. When the evaluation results show that the current capacity configuration is difficult to meet the operation requirements, the capacity configuration parameters are corrected, and the corrected capacity configuration parameters are input into the updated multi-objective collaborative optimization configuration model to solve and generate the capacity configuration scheme and operation scheduling strategy for the next scheduling cycle starting from the current moment.

Claims

1. A collaborative optimization allocation method for smoothing fluctuations in new energy output, characterized in that, The method includes: S1. Based on the historical power output data of the new energy power generation system in the target area, obtain the fluctuating power gap sequence, and perform frequency domain decomposition on the fluctuating power gap sequence to divide the low-frequency trend power component and the high-frequency fluctuating power component. S2. Allocate the low-frequency trend power component to the pumped storage system to form the planned output of the pumped storage system; calculate the interaction coupling power between the pumped storage system and the electrochemical energy storage system, and allocate the interaction coupling power and the high-frequency fluctuation power component to the electrochemical energy storage system to form the planned output of the electrochemical energy storage system. S3. Based on the planned output demand of pumped storage system and electrochemical energy storage system, a multi-objective collaborative optimization configuration model is constructed with the joint optimization objectives of minimizing grid-connected power fluctuation residual, energy storage system life cycle cost, new energy curtailment rate and collaborative scheduling loss. The model is then solved to obtain the optimal capacity configuration scheme of the new energy system in the next scheduling cycle and the operation scheduling strategy at each time in the scheduling cycle.

2. The collaborative optimization allocation method for smoothing fluctuations in new energy output according to claim 1, characterized in that, In S2, the planned output of pumped storage is calculated using the following formula: ； ； In the above formula, for The planned output of the pumped storage system at all times. For low-frequency trend power components, For the total scheduling cycle, for The actual output deviation is constantly limited by mechanical characteristics. The scheduling time step; The planned output of the electrochemical energy storage is calculated using the following formula: ； ； ； In the above formula, for The total regulation power command undertaken by the electrochemical energy storage system at all times For high-frequency fluctuating power components, for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system The coupling adjustment coefficient is used to characterize the compensation ratio of electrochemical energy storage to the output deviation of pumped hydro storage. for Constant deviations in the planned execution of pumped storage systems for The state of charge of electrochemical energy storage at any given time. , These represent the minimum and maximum states of charge in electrochemical energy storage, respectively. for The actual output of the pumped storage system at all times. for The planned output of the pumped storage system at all times.

3. The collaborative optimization allocation method for smoothing fluctuations in new energy output according to claim 1, characterized in that, In S4, the objective function of the multi-objective collaborative optimization configuration model includes: ； ； ； ； ； In the above formula, The objective of the multi-objective collaborative optimization configuration model is... , , , These are the weight coefficients for the corresponding objectives. For grid-connected power fluctuation residuals, For the total lifecycle cost of energy storage systems, For the curtailment rate of new energy sources, To reduce the loss during coordinated scheduling, For the total scheduling cycle, for The final grid-connected power at any given moment, for The target power for grid connection at any given time. The investment cost of a pumped storage system, The investment cost of electrochemical energy storage systems, For the operation and maintenance costs of hybrid energy storage systems, for The curtailment power of the new energy system at any given time To schedule the time step, for The maximum predicted power that a new energy system can theoretically generate. for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system This is the additional depreciation cost factor incurred by the electrochemical energy storage system in response to interactive coupling commands; The constraints of the multi-objective collaborative optimization configuration model include energy storage power capacity constraints, pumped storage power station output and energy evolution constraints, electrochemical energy storage system state of charge dynamic constraints, and interactive coupling constraints between pumped storage system and electrochemical energy storage system. The energy storage capacity is: ； ； In the above formula, This represents the maximum power capacity of the pumped storage system. This indicates taking the maximum value over the time set. for The planned output of the pumped storage system at all times. This represents the maximum power capacity of the electrochemical energy storage system. for The total regulation power command undertaken by the electrochemical energy storage system at any given time; The output and energy evolution constraints of the pumped storage power station include: ； ； ； ； In the above formula, for The power generation capacity of the pumped storage power station at all times. , These represent the minimum and maximum generating capacities of a pumped storage power station. for The pumping power of a pumped storage power station at all times. , These represent the minimum and maximum pumping power of a pumped storage power station. for The energy storage capacity of a pumped-storage hydroelectric power station at all times. , These represent the minimum and maximum energy storage capacities of a pumped storage power station. The efficiency of the pumping process. The efficiency of the power generation process; The dynamic constraints on the state of charge of the electrochemical energy storage system include: ； ； In the above formula, for The state of charge of electrochemical energy storage at any given time. For charging efficiency, for The charging power of electrochemical energy storage at all times. To schedule the time step, The rated capacity of electrochemical energy storage, for The discharge power of electrochemical energy storage at any given time. For discharge efficiency, , These represent the minimum and maximum states of charge for electrochemical energy storage, respectively. The interaction coupling constraint between the pumped hydro storage system and the electrochemical energy storage system is: ； In the above formula, for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system The coupling adjustment coefficient is used to characterize the compensation ratio of electrochemical energy storage to the output deviation of pumped hydro storage. for Constant deviations in the planned execution of pumped storage systems for The state of charge of electrochemical energy storage at any given time. , These represent the minimum and maximum states of charge for electrochemical energy storage, respectively.

4. The collaborative optimization allocation method for smoothing fluctuations in new energy output according to claim 1, characterized in that, The method further includes: S4. Based on the real-time operation monitoring results of the scheduling strategy at each moment within the scheduling cycle, execute the adaptive feedback correction process.

5. The collaborative optimization allocation method for smoothing fluctuations in new energy output according to claim 4, characterized in that, S4 includes: S41. Real-time monitoring of the deviation between the final grid-connected power and the grid-connected target power at each moment within the scheduling cycle, the deviation between the state of charge of electrochemical energy storage and the safe operating range, and the proportion of high-frequency fluctuation power components in the fluctuation spectrum of new energy output, and weighted calculation of these three data to obtain the deviation evaluation index at each moment. S42. Determine whether the deviation evaluation index at each time exceeds the preset threshold. When the deviation evaluation index does not exceed the preset threshold, the current optimal capacity configuration scheme and operation scheduling strategy are the optimal scheme to smooth out the fluctuation of new energy output. When the deviation evaluation index at a certain time exceeds the preset threshold, execute the long / short cycle hierarchical feedback correction. The hierarchical feedback correction for long / short cycles is as follows: Within a short period, the weight coefficients of the objective function of the multi-objective collaborative optimization configuration model, the boundary thresholds of the constraints, and the frequency thresholds or boundaries of the power gap frequency domain decomposition are adaptively updated through a negative feedback mechanism, and the current scheduling strategy continues to be executed. Within a long period, the deviation evaluation index is accumulated and statistically analyzed within a scheduling cycle based on the moment when the deviation evaluation index exceeds the preset threshold, forming a comprehensive evaluation index. The system operation effect is evaluated based on this comprehensive evaluation index. When the evaluation results show that the current capacity configuration is difficult to meet the operation requirements, the capacity configuration parameters are corrected, and the corrected capacity configuration parameters are input into the updated multi-objective collaborative optimization configuration model to solve and generate the capacity configuration scheme and operation scheduling strategy for the next scheduling cycle starting from the current moment.

6. The collaborative optimization allocation method for smoothing fluctuations in new energy output according to claim 1, characterized in that, S1 includes: S11. Calculate the fluctuating power gap sequence using the following formula: ； In the above formula, for The fluctuating power gap sequence at time t, for The actual output sequence of new energy sources at any given time. for The target power for grid connection at any given time; S12. Decompose the fluctuating power gap sequence into modal components with different center frequencies, and set frequency thresholds. The center frequency is lower than The modal components are divided into low-frequency trend power components. The center frequency is higher than The modal components are divided into high-frequency fluctuation power components. .

7. A collaborative optimization allocation system for smoothing fluctuations in new energy output, characterized in that, The system includes a fluctuating power gap sequence decomposition module, a power component allocation module, and a multi-objective collaborative optimization configuration model construction module. The fluctuating power gap sequence decomposition module is used to obtain the fluctuating power gap sequence based on the historical output data of the new energy power generation system in the target area, and to perform frequency domain decomposition on the fluctuating power gap sequence to divide it into low-frequency trend power components and high-frequency fluctuating power components. The power component allocation module is used to allocate the low-frequency trend power component to the pumped storage system to form the planned output of the pumped storage system; calculate the interactive coupling power between the pumped storage system and the electrochemical energy storage system, and allocate the interactive coupling power and the high-frequency fluctuation power component to the electrochemical energy storage system to form the planned output of the electrochemical energy storage system. The multi-objective collaborative optimization configuration model construction module is used to construct a multi-objective collaborative optimization configuration model based on the planned output demand of pumped storage system and electrochemical energy storage system, with the joint optimization objectives of minimizing grid-connected power fluctuation residual, energy storage system life cycle cost, new energy curtailment rate and collaborative scheduling loss. The module then solves the model to obtain the optimal capacity configuration scheme for the new energy system in the next scheduling cycle and the operation scheduling strategy at each time point within that scheduling cycle.

8. The collaborative optimization configuration system for smoothing fluctuations in new energy output according to claim 7, characterized in that, The fluctuating power gap sequence decomposition module includes a fluctuating power gap sequence calculation unit and a modal component partitioning unit. The fluctuating power gap sequence calculation unit is used to calculate the fluctuating power gap sequence using the following formula: ； In the above formula, for The fluctuating power gap sequence at time t, for The actual output sequence of new energy sources at any given time. for The target power for grid connection at any given time; The modal component segmentation unit is used to decompose the fluctuating power gap sequence into modal components with different center frequencies, and to set frequency thresholds. The center frequency is lower than The modal components are divided into low-frequency trend power components. The center frequency is higher than The modal components are divided into high-frequency fluctuation power components. ; The power component allocation module includes a pumped storage planned output calculation unit and an electrochemical energy storage planned output calculation unit. The pumped storage planned output calculation unit is used to calculate the planned output of the pumped storage using the following formula: ； ； In the above formula, for The planned output of the pumped storage system at all times. For low-frequency trend power components, For the total scheduling cycle, for The actual output deviation is constantly limited by mechanical characteristics. The scheduling time step; The electrochemical energy storage planned output calculation unit is used to calculate the planned output of electrochemical energy storage using the following formula: ； ； ； In the above formula, for The total regulation power command undertaken by the electrochemical energy storage system at all times For high-frequency fluctuating power components, for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system The coupling adjustment coefficient is used to characterize the compensation ratio of electrochemical energy storage to the output deviation of pumped hydro storage. for Constant deviations in the planned execution of pumped storage systems for The state of charge of electrochemical energy storage at any given time. , These represent the minimum and maximum states of charge in electrochemical energy storage, respectively. for The actual output of the pumped storage system at all times. for The planned output of the pumped storage system at all times.

9. A collaborative optimization configuration system for smoothing fluctuations in new energy output according to claim 7, characterized in that, The multi-objective collaborative optimization configuration model construction module includes an objective function construction unit and a constraint condition construction unit; The objective function construction unit is used to construct the objective function of the following multi-objective collaborative optimization configuration model: ； ； ； ； ； In the above formula, The objective of the multi-objective collaborative optimization configuration model is... , , , These are the weight coefficients for the corresponding objectives. For grid-connected power fluctuation residuals, For the total lifecycle cost of energy storage systems, For the curtailment rate of new energy sources, To reduce the loss during coordinated scheduling, For the total scheduling cycle, for The final grid-connected power at any given moment, for The target power for grid connection at any given time. The investment cost of a pumped storage system, The investment cost of electrochemical energy storage systems, For the operation and maintenance costs of hybrid energy storage systems, for The curtailment power of the new energy system at any given time To schedule the time step, for The maximum predicted power that a new energy system can theoretically generate. for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system This is the additional depreciation cost factor incurred by the electrochemical energy storage system in response to interactive coupling commands; The constraint construction unit is used to construct the constraints of the multi-objective collaborative optimization configuration model, including energy storage power capacity constraints, pumped storage power station output and energy evolution constraints, electrochemical energy storage system state of charge dynamic constraints, and interactive coupling constraints between pumped storage system and electrochemical energy storage system. The energy storage capacity is: ； ； In the above formula, This represents the maximum power capacity of the pumped storage system. This indicates taking the maximum value over the time set. for The planned output of the pumped storage system at all times. This represents the maximum power capacity of the electrochemical energy storage system. for The total regulation power command undertaken by the electrochemical energy storage system at any given time; The output and energy evolution constraints of the pumped storage power station include: ； ； ； ； In the above formula, for The power generation capacity of the pumped storage power station at all times. , These represent the minimum and maximum generating capacities of a pumped storage power station. for The pumping power of a pumped storage power station at all times. , These represent the minimum and maximum pumping power of a pumped storage power station. for The energy storage capacity of a pumped-storage hydroelectric power station at all times. , These represent the minimum and maximum energy storage capacities of a pumped storage power station. The efficiency of the pumping process. The efficiency of the power generation process; The dynamic constraints on the state of charge of the electrochemical energy storage system include: ； ； In the above formula, for The state of charge of electrochemical energy storage at any given time. For charging efficiency, for The charging power of electrochemical energy storage at all times. To schedule the time step, The rated capacity of electrochemical energy storage, for The discharge power of electrochemical energy storage at any given time. For discharge efficiency, , These represent the minimum and maximum states of charge for electrochemical energy storage, respectively. The interaction coupling constraint between the pumped hydro storage system and the electrochemical energy storage system is: ； In the above formula, for The constant interaction coupling power between the pumped hydro storage system and the electrochemical energy storage system The coupling adjustment coefficient is used to characterize the compensation ratio of electrochemical energy storage to the output deviation of pumped hydro storage. for Constant deviations in the planned execution of pumped storage systems for The state of charge of electrochemical energy storage at any given time. , These represent the minimum and maximum states of charge for electrochemical energy storage, respectively.

10. A collaborative optimization configuration system for smoothing fluctuations in new energy output according to claim 7, characterized in that, The system also includes an adaptive feedback correction module; The adaptive feedback correction module is used to perform an adaptive feedback correction process based on the real-time operation monitoring results of the scheduling strategy at each time within the scheduling cycle, including a deviation evaluation index real-time monitoring unit and a judgment unit. The deviation evaluation index real-time monitoring unit is used to monitor in real time the deviation between the final grid-connected power and the grid-connected target power at each moment within the scheduling cycle, the degree of deviation between the state of charge of electrochemical energy storage and the safe operating range, and the proportion of high-frequency fluctuation power components in the fluctuation spectrum of new energy output, and to calculate the deviation evaluation index at each moment by weighting these three data. The determination unit is used to determine whether the deviation evaluation index at each time exceeds the preset threshold. When the deviation evaluation index does not exceed the preset threshold, the current optimal capacity configuration scheme and operation scheduling strategy are the optimal scheme to smooth out the fluctuation of new energy output. When the deviation evaluation index at a certain time exceeds the preset threshold, long / short cycle hierarchical feedback correction is executed. The hierarchical feedback correction for long / short cycles is as follows: Within a short period, the weight coefficients of the objective function of the multi-objective collaborative optimization configuration model, the boundary thresholds of the constraints, and the frequency thresholds or boundaries of the power gap frequency domain decomposition are adaptively updated through a negative feedback mechanism, and the current scheduling strategy continues to be executed. Within a long period, the deviation evaluation index is accumulated and statistically analyzed within a scheduling cycle based on the moment when the deviation evaluation index exceeds the preset threshold, forming a comprehensive evaluation index. The system operation effect is evaluated based on this comprehensive evaluation index. When the evaluation results show that the current capacity configuration is difficult to meet the operation requirements, the capacity configuration parameters are corrected, and the corrected capacity configuration parameters are input into the updated multi-objective collaborative optimization configuration model to solve and generate the capacity configuration scheme and operation scheduling strategy for the next scheduling cycle starting from the current moment.

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