A flexible energy storage configuration method considering burst load impact scenarios

Abstract

The application provides a flexible energy storage configuration method considering burst load impact scenarios. The method is based on a hybrid energy storage system; the method comprises: decomposing original load data into a baseline component representing regular changes and an impact component reflecting burst disturbances; determining an impact identification threshold according to the statistical distribution characteristics of the impact component, and then extracting characteristic parameters of the impact event; according to the characteristic parameters and the energy storage recovery time threshold of the hybrid energy storage system, the operating conditions of the hybrid energy storage system are divided into three typical operating condition scenarios; a hybrid energy storage component quantization demand model is constructed; an operating feasibility checking model of the hybrid energy storage system is established; a hybrid energy storage capacity-operation collaborative optimization model is constructed, taking the sum of the equivalent configuration cost of the hybrid energy storage and the additional life loss cost of the impact as the target, and solving and outputting the optimal configuration scheme of the hybrid energy storage. The application improves the rationality, impact suppression capacity and operating safety of the hybrid energy storage configuration under the burst load impact and impact superposition scenarios.

Description

Technical Field

[0001] This invention relates to the field of power system energy storage configuration technology, and more specifically, to a flexible energy storage configuration method that takes into account sudden load impact scenarios. Background Technology

[0002] With the rapid integration of new energy generation, electronic loads, and impulsive industrial loads, the operating conditions of power systems are exhibiting greater randomness, volatility, and suddenness. Especially in scenarios involving electric arc furnaces, high-power traction loads, pulsed production equipment, and high proportions of new energy grid connection, load power may change drastically in a short period, forming sudden load surges with high amplitude, rapid ramp-up, and uncertain duration. These surges can easily cause bus voltage fluctuations, power oscillations, equipment overload, and localized power quality degradation, adversely affecting the safe and stable operation of the power grid and the reliability of power supply on the user side. Therefore, how to rationally configure energy storage systems to address the characteristics of sudden load surges, enabling them to possess rapid power response capabilities, continuous energy support capabilities, and continuous surge recovery capabilities, has become a crucial research issue in the field of energy storage planning and operation control.

[0003] In existing technologies, electrochemical energy storage is widely used in peak shaving, frequency regulation, and new energy power smoothing due to its advantages such as high energy density, flexible configuration, and mature engineering applications. Lithium iron phosphate (LFP) batteries, in particular, are characterized by good safety, long cycle life, and strong energy support capabilities, making them suitable for long-duration power compensation tasks. However, in sudden load surge scenarios, the surge power often exhibits characteristics such as rapid rise, large instantaneous power, and frequent recurrence. If only LFP batteries are used for all surge compensation tasks, it can easily lead to short-term high-rate charge-discharge cycles and frequent shallow-cycle operation, accelerating battery capacity decay and lifespan loss. It may also increase redundant energy storage capacity configuration, reducing the system's configuration economy.

[0004] Flywheel energy storage boasts advantages such as high power density, fast response speed, long cycle life, and strong short-term high-frequency charge and discharge capability. It can rapidly release or absorb power within millisecond to second timescales, making it suitable for rapid power compensation during the initial stages of sudden load surges and for high-ramp-rate following tasks. Compared to lithium iron phosphate batteries, flywheel energy storage is less affected by the number of cycles during frequent impact responses, effectively mitigating the lifespan loss caused by direct exposure to high-frequency impacts. However, flywheel energy storage has a relatively low energy density, making it suitable for short-term rapid responses but not for solely undertaking long-term energy support tasks. Therefore, a hybrid configuration of flywheel energy storage and lithium iron phosphate batteries can fully leverage the rapid response and high-frequency cycling advantages of flywheel energy storage, as well as the continuous support and energy capacity advantages of lithium iron phosphate batteries, achieving complementary synergy between power-type and energy-type energy storage.

[0005] Currently, energy storage configuration methods for sudden load shock scenarios still have certain shortcomings. On the one hand, some methods mainly determine energy storage capacity based on load peak or power fluctuation amplitude, without fully considering the multi-dimensional characteristics of the shock event, such as amplitude, ramp rate, duration, and interval between adjacent shocks, making it difficult to accurately reflect the differences in energy storage response requirements under different shock scenarios. On the other hand, existing methods often configure the energy storage system as a single energy storage unit, lacking differentiated modeling of the rapid response characteristics of flywheel energy storage and the continuous support characteristics of lithium iron phosphate batteries, which can easily lead to insufficient rapid response capability or redundant battery capacity configuration. In addition, for continuous shock or superimposed shock scenarios, existing energy storage configuration methods usually do not fully consider the energy recovery process and recovery margin requirements between adjacent shocks, which may result in the energy storage system failing to fully recover after the previous shock, thereby affecting the subsequent shock suppression effect and system operational safety.

[0006] Meanwhile, sudden load shocks cause batteries to operate in a state of frequent charging and discharging and non-steady power response. Battery life loss is closely related to factors such as the depth of shock discharge, charge / discharge rate, and degree of insufficient recovery. If only the initial capacity cost is considered during energy storage configuration, while ignoring the additional life loss under shock conditions, it is difficult to obtain an energy storage configuration scheme that balances safety, economy, and long-term operational reliability. Therefore, we need to coordinate flywheel energy storage with lithium iron phosphate batteries to improve the configuration rationality, shock suppression capability, and operational safety of hybrid energy storage systems under sudden load shocks and shock superposition scenarios. Summary of the Invention

[0007] The present invention aims to solve at least one of the technical problems existing in the prior art or related art.

[0008] Therefore, the purpose of this invention is to propose a flexible energy storage configuration method that takes into account sudden load impact scenarios.

[0009] To achieve the above objectives, the present invention provides a flexible energy storage configuration method considering sudden load impact scenarios. This method is based on a hybrid energy storage system; the hybrid energy storage system includes: flywheel energy storage and lithium iron phosphate battery energy storage; the flexible energy storage configuration method considering sudden load impact scenarios includes: Step S1: analyzing the original load data to decompose the original load data into a baseline component characterizing normal changes and an impact component reflecting sudden disturbances; Step S2: obtaining the statistical distribution characteristics of the impact component, and determining the impact identification threshold based on the statistical distribution characteristics of the impact component, then detecting the impact event and extracting the characteristic parameters of the impact event; wherein, the characteristic parameters of the impact event include: amplitude, ramp rate, duration, and adjacent impact interval time; Step S3: based on the characteristic parameters of the impact event and the energy storage recovery time threshold of the hybrid energy storage system, dividing the operating conditions of the hybrid energy storage system into normal operation, Three typical operating conditions are identified: non-superimposed impact scenarios and impact superimposed scenarios. Step S4: Based on the characteristic parameters of the impact event and the typical operating conditions, a hybrid energy storage segmentation demand model is constructed, including rapid response requirements, continuous support requirements, and recovery margin requirements. Step S5: Based on the hybrid energy storage segmentation demand model, and combining the rapid response characteristics of flywheel energy storage and the continuous support characteristics of lithium iron phosphate battery energy storage, an operational feasibility verification model for the hybrid energy storage system in terms of impact compensation, power operation, energy state, recovery margin, and lifespan loss is established. Step S6: Based on the hybrid energy storage segmentation demand model and the operational feasibility verification model, a hybrid energy storage capacity-operation collaborative optimization model is constructed. With the goal of minimizing the sum of the equivalent configuration cost of hybrid energy storage and the impact-added lifespan loss cost, the optimal configuration scheme for hybrid energy storage is solved and output.

[0010] Preferably, step S1 includes:

[0011] Step S1.1: Obtain the original load sequence within the analysis period, and extract the baseline component from the original load sequence using the sliding window averaging method:

[0012] ;

[0013] In the formula: Let be the reference component at time t. Used to characterize the typical fluctuation trend of load over time; is the original load value corresponding to the k-th sampling point within the sliding window; N is the length of the sliding window; t is the sampling time; k is the sampling point number within the sliding window;

[0014] Step S1.2: Subtract the original load value at time t from the reference component to obtain the impact component reflecting the characteristics of the sudden disturbance:

[0015] ;

[0016] In the formula: Let be the impact component at time t. Used to characterize sudden load disturbances that deviate from the normal load change trend; The original load value at time t.

[0017] Preferably, step S2 specifically includes:

[0018] Step S2.1: Calculate the statistical mean and standard deviation of the impact component during the analysis period to obtain the statistical distribution characteristics of the impact component:

[0019] ;

[0020] In the formula: This represents the total number of sampling points within the analysis period. This represents the statistical mean of the impact components; The standard deviation of the impact component;

[0021] Step S2.2: Based on the statistical mean and standard deviation of the impact components, determine the impact identification threshold as follows:

[0022] ;

[0023] In the formula: The threshold for impact identification; This is the threshold adjustment coefficient;

[0024] Step S2.3: Traverse the impact component sequence, merge consecutive sampling points exceeding the impact identification threshold into an impact event, and extract the amplitude, ramp rate, duration, and adjacent impact interval of the impact event as follows:

[0025] ;

[0026] In the formula: Let be the amplitude of the i-th impact event; Let be the ramp rate during the rising phase of the i-th impact event; Let be the duration of the i-th impact event; The interval between adjacent impact events is the time between the i-th impact event and the next impact event. Let i be the start time of the i-th impact event; Let i be the end time of the i-th impact event; This is the moment when the i-th impact event reaches its peak. Let be the multidimensional impact characteristic parameter vector of the i-th impact event.

[0027] Preferably, step S3 specifically includes:

[0028] Step S3.1: Based on the duration and impact components of the impact event, calculate the equivalent impact energy corresponding to each impact event:

[0029] ;

[0030] In the formula: Let be the equivalent impact energy corresponding to the i-th impact event;

[0031] Step S3.2: Based on the relationship between the adjacent impact interval time and the energy storage recovery time threshold, determine the recovery insufficiency coefficient corresponding to the adjacent impact interval as follows:

[0032] ;

[0033] In the formula: This is the inadequacy coefficient corresponding to the i-th adjacent impact interval; This is the energy storage recovery time threshold;

[0034] Step S3.3: Based on the insufficient recovery coefficient, calculate the impact superposition index within the analysis period as follows:

[0035] ;

[0036] In the formula: Γ is the index of the degree of impact superposition within the analysis period; NI is the number of impact events within the analysis period;

[0037] Step S3.4: Based on the number of impact events NI and the impact superposition index Γ during the analysis period, the operating conditions of the hybrid energy storage system are divided into three categories: normal operation, non-superposition impact scenario, and impact superposition scenario. Typical operating conditions of the hybrid energy storage system are as follows:

[0038] ;

[0039] Where: S represents a typical operating scenario for a hybrid energy storage system; This is a normal operating scenario; This is a non-cumulative impact scenario; To impact and overlay scenarios.

[0040] Preferably, step S4 specifically includes:

[0041] Step S4.1: Decompose the hybrid energy storage response demand into impact amplitude suppression power demand, power ramp-up following demand, continuous support energy demand, and recovery margin energy demand as follows:

[0042] ;

[0043] In the formula: This is a vector of quantified energy storage demand indicators; To suppress the power demand for impact amplitude; To meet the power ramp-following requirements of the energy storage system; To continuously support energy demand; To restore the margin of energy demand;

[0044] Step S4.2: Based on the impact amplitude, ramp rate, and equivalent impact energy, calculate the fractional energy storage requirements corresponding to each impact event:

[0045] ;

[0046] In the formula: The peak energy storage compensation power requirement corresponding to the i-th impact event; The percentage of residual impact that is allowed to remain after compensation; For the i-th impact event, the hill-climbing and following requirement is required. The continuous support energy requirement corresponding to the i-th impact event; For energy storage discharge efficiency;

[0047] Step S4.3: Based on the quantification requirements of each impact event, determine the power amplitude requirement, power ramp-up requirement, and continuous support energy requirement within the analysis period as follows:

[0048] ;

[0049] Step S4.4: Based on the recoverable energy within adjacent impact intervals and the unrecoverable energy from consecutive impacts, determine the recovery margin energy requirement as follows:

[0050] ;

[0051] In the formula: This represents the accumulated energy that the energy storage system has not yet recovered before the arrival of the i-th impact event; This represents the cumulative energy that the energy storage system has not yet recovered before the arrival of the (i+1)th impact event; Let be the recoverable energy of the energy storage system within the i-th adjacent impact interval; Let be the continuous support energy requirement corresponding to the i-th impact event.

[0052] Preferably, step S5 specifically includes:

[0053] Step S5.1: Establish the hybrid energy storage impact compensation power model as follows:

[0054] ;

[0055] In the formula: The total compensation power of the hybrid energy storage system at time t; The compensating operating power for flywheel energy storage at time t; This represents the compensated operating power of the lithium iron phosphate battery at time t.

[0056] Step S5.2: Establish the impact compensation deviation and impact suppression verification model as follows:

[0057] ;

[0058] In the formula: The impact compensation deviation at time t; Let t be the impact component at time t; The upper limit of residual impact power allowed to be retained after compensation; The percentage of residual impact that is allowed to remain after compensation; To analyze the peak characteristic quantities of the impact components within the time period; Let be the impact suppression rate for the i-th impact event; The residual impact peak value after compensation for the i-th impact event;

[0059] Step S5.3: Establish the power operation verification model for flywheel energy storage and lithium iron phosphate batteries as follows:

[0060] ;

[0061] In the formula: Rated power for flywheel energy storage; This refers to the rated power of lithium iron phosphate batteries; Δt represents the maximum power change rate of the flywheel energy storage at rated power; Δt is the sampling time interval. The recovery charging power of the lithium iron phosphate battery at time t; Let t be the available recovery power of the system for energy storage recovery at time t;

[0062] Step S5.4: Establish the energy state and state of charge verification models for lithium iron phosphate batteries as follows:

[0063] ;

[0064] In the formula: Let t be the available energy of the lithium iron phosphate battery at time t; The discharge efficiency of lithium iron phosphate batteries; The charging efficiency of lithium iron phosphate batteries; The state of charge of the lithium iron phosphate battery at time t; This refers to the rated capacity of lithium iron phosphate batteries. This is the state-of-charge limit for lithium iron phosphate batteries; This represents the upper limit of the state of charge (SOC) of lithium iron phosphate batteries.

[0065] Step S5.5: Establish the calculation models for the actual discharge energy and actual recovery energy of the lithium iron phosphate battery as follows:

[0066] ;

[0067] In the formula: Let be the actual discharge energy of the lithium iron phosphate battery during the i-th impact event; The actual recovered energy of the lithium iron phosphate battery within the i-th adjacent impact interval; The actual recovered energy of the lithium iron phosphate battery from the end of the last impact event to the end of the analysis period; Let i be the start time of the i-th impact event; Let be the end time of the i-th impact event; T is the end time of the analysis period;

[0068] Step S5.6: Establish the verification model for cumulative unrecovered energy and recovery margin under continuous impact conditions as follows:

[0069] ;

[0070] In the formula: This represents the actual cumulative unrecovered energy prior to the arrival of the i-th impact event; This represents the actual cumulative unrecovered energy prior to the arrival of the (i+1)th impact event; To analyze the actual cumulative unrecovered energy at the end of the analysis period;

[0071] Step S5.7: Establish a characterization model for the impact-induced life loss of lithium iron phosphate batteries, specifically as follows:

[0072] ;

[0073] In the formula: Let be the characteristic quantity of the battery discharge depth corresponding to the i-th impact event; This is a characterization of the battery charge / discharge rate corresponding to the i-th impact event; This represents the peak compensation power of the battery corresponding to the i-th impact event; This is the life loss correction coefficient corresponding to the i-th impact event, used to reflect the impact discharge depth, charge-discharge rate and insufficient recovery on battery life degradation. This is a characterization of the impact-induced life loss of lithium iron phosphate batteries.

[0074] Preferably, step S6 specifically includes:

[0075] Step S6.1: Establish the hybrid energy storage configuration decision vector as follows:

[0076] ;

[0077] In the formula: Z is the hybrid energy storage configuration decision vector; Rated power for flywheel energy storage; Rated capacity for flywheel energy storage; This refers to the rated power of lithium iron phosphate batteries; This refers to the rated capacity of lithium iron phosphate batteries.

[0078] Step S6.2: Establish the hybrid energy storage power amplitude configuration relationship as follows:

[0079] ;

[0080] Step S6.3: Establish the flywheel energy storage fast response configuration relationship as follows:

[0081] ;

[0082] In the formula: Energy boundaries for flywheel energy storage that can be used for rapid response;

[0083] Step S6.4: Establish the configuration relationship between the continuous support and recovery margin of the lithium iron phosphate battery as follows:

[0084] ;

[0085] Step S6.5: Establish the equivalent configuration cost model for hybrid energy storage as follows:

[0086] ;

[0087] In the formula: Cost of equivalent configuration for hybrid energy storage; Cost per unit power for flywheel energy storage; Cost per unit capacity of flywheel energy storage; Cost per unit power of lithium iron phosphate batteries; Cost per unit capacity of lithium iron phosphate batteries;

[0088] Step S6.6: Based on the characteristic quantities of impact-induced additional life loss in lithium iron phosphate batteries, establish the impact-induced additional life loss cost model as follows:

[0089] ;

[0090] In the formula: To reduce the additional lifespan loss costs associated with impact; This is the unit impact life loss cost coefficient for lithium iron phosphate batteries.

[0091] Step S6.7: Establish the hybrid energy storage capacity-operation co-optimization objective as follows:

[0092] ;

[0093] In the formula: C is the comprehensive optimization target cost of hybrid energy storage; This is the optimal configuration scheme for hybrid energy storage;

[0094] Step S6.8: Solve for and output the optimal configuration scheme for hybrid energy storage as follows:

[0095] ;

[0096] In the formula: The optimal rated power for flywheel energy storage; The optimal rated capacity for flywheel energy storage; This represents the optimal rated power for lithium iron phosphate batteries. This represents the optimal rated capacity for lithium iron phosphate batteries. The overall optimization cost corresponding to the optimal configuration scheme; The equivalent configuration cost of hybrid energy storage corresponding to the optimal configuration scheme; The impact-induced life loss cost corresponding to the optimal configuration scheme.

[0097] Compared with existing technologies, the flexible energy storage configuration method considering sudden load impact scenarios provided by this invention has the following advantages:

[0098] (1) The present invention can improve the rationality, shock suppression capability and operational safety of hybrid energy storage configuration under sudden load impact and impact superposition scenarios.

[0099] (2) Based on the multidimensional characteristics of impact and the energy storage recovery time, the present invention divides typical scenarios, which can improve the accuracy of energy storage demand analysis and capacity configuration.

[0100] (3) This invention leverages the complementary advantages of flywheel energy storage and lithium iron phosphate batteries, and takes into account battery life loss, which helps to reduce configuration costs and improve system reliability.

[0101] Additional aspects and advantages of the invention will become apparent from the description which follows, or may be learned by practice of the invention. Attached Figure Description

[0102] Figure 1 A schematic diagram of the overall process of a flexible energy storage configuration method considering sudden load shock scenarios according to an embodiment of the present invention is shown.

[0103] Figure 2 This diagram illustrates the identification of the original load reference component and the impact component according to an embodiment of the present invention.

[0104] Figure 3 A statistical graph of multidimensional impact characteristic parameters of an embodiment of the present invention is shown;

[0105] Figure 4 Three typical scenario diagrams of an embodiment of the present invention are shown;

[0106] Figure 5 A comparison diagram of impact compensation before and after an embodiment of the present invention is shown;

[0107] Figure 6 An impact compensation deviation verification diagram of an embodiment of the present invention is shown;

[0108] Figure 7 A diagram illustrating the flywheel energy storage and lithium iron phosphate battery power distribution and recharging process according to an embodiment of the present invention is shown.

[0109] Figure 8 The diagram shows the flywheel energy storage state of energy, lithium iron phosphate battery SOC and continuous impact recovery margin verification diagram according to an embodiment of the present invention;

[0110] Figure 9 A diagram showing the hybrid energy storage configuration result of one embodiment of the present invention is illustrated.

[0111] Figure 10 A comparison diagram of the impact suppression effects of the present invention for various impact events is shown. Detailed Implementation

[0112] To better understand the above-mentioned objects, features, and advantages of the present invention, such as Figures 1 to 10 As shown in the accompanying drawings and specific embodiments, the present invention will be further described in detail below. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0113] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0114] Figure 1 This diagram illustrates the overall flow of a flexible energy storage configuration method considering sudden load shock scenarios according to an embodiment of the present invention. The method is based on a hybrid energy storage system; the hybrid energy storage system includes: flywheel energy storage and lithium iron phosphate battery energy storage; such as... Figure 1 As shown, this flexible energy storage configuration method considering sudden load shock scenarios includes:

[0115] Step S1: Analyze the raw load data to decompose it into a baseline component that characterizes regular changes and an impact component that reflects sudden disturbances.

[0116] Step S2: Obtain the statistical distribution characteristics of the impact components, determine the impact identification threshold based on the statistical distribution characteristics of the impact components, then detect the impact event and extract the feature parameters of the impact event; wherein, the feature parameters of the impact event include: amplitude, ramp rate, duration and time interval between adjacent impacts;

[0117] Step S3: Based on the characteristic parameters of the impact event and the energy storage recovery time threshold of the hybrid energy storage system, the operating conditions of the hybrid energy storage system are divided into three typical operating conditions: normal operation, non-superimposed impact scenario, and impact superimposed scenario.

[0118] Step S4: Based on the characteristic parameters of the impact event and typical operating scenarios, construct a hybrid energy storage quantification demand model that includes the requirements for rapid response, continuous support, and recovery margin.

[0119] Step S5: Based on the hybrid energy storage fractional demand model, and combining the rapid response characteristics of flywheel energy storage and the continuous support characteristics of lithium iron phosphate battery energy storage, establish an operational feasibility verification model for the hybrid energy storage system in terms of impact compensation, power operation, energy state, recovery margin, and lifespan loss.

[0120] Step S6: Based on the hybrid energy storage quantification demand model and operation feasibility verification model, construct a hybrid energy storage capacity-operation collaborative optimization model. With the objective of minimizing the sum of the equivalent configuration cost of hybrid energy storage and the impact-added life loss cost, solve and output the optimal configuration scheme of hybrid energy storage.

[0121] In this embodiment, the basic idea of ​​the flexible energy storage configuration method considering sudden load impact scenarios is as follows: by analyzing the original load data, separating the baseline component and the impact component, identifying sudden load impact events and extracting characteristic parameters such as amplitude, ramp rate, duration, and adjacent impact intervals; combining the number of impact events and energy storage recovery time requirements, constructing three typical scenarios: normal operation, non-superimposed impact scenarios, and impact superimposed scenarios; further establishing a hybrid energy storage fractional demand model that includes rapid response, continuous support, and recovery margin requirements; based on this, combining the complementary characteristics of flywheel energy storage and lithium iron phosphate batteries, constructing a hybrid energy storage operation verification model and a capacity-operation collaborative optimization model, with the goal of minimizing the sum of equivalent configuration cost and impact-added life loss cost, solving for the optimal hybrid energy storage configuration scheme, thereby improving the system's configuration rationality, impact suppression capability, and operational safety under sudden load impact and impact superimposed scenarios.

[0122] The technical solution of the present invention will be illustrated below with a specific embodiment. This specific embodiment describes a flexible energy storage configuration method considering sudden load shock scenarios, which is implemented through the following steps:

[0123] (1) Step 1: By analyzing the original load data, the original load is decomposed into a baseline component that characterizes the normal changes and an impact component that reflects the sudden disturbances.

[0124] Step 1 specifically includes:

[0125] Step 1-1: Obtain the original load sequence within the analysis period, and extract the baseline component from the original load using the sliding window averaging method:

[0126] ;

[0127] In the formula: This is the baseline component at time t, used to characterize the regular fluctuation trend of load over time; is the original load value corresponding to the k-th sampling point within the sliding window; N is the length of the sliding window; t is the sampling time; k is the sampling point number within the sliding window;

[0128] Step 1-2: Subtract the original load from the reference component to obtain the impact component reflecting the characteristics of the sudden disturbance:

[0129] ;

[0130] In the formula: Let be the impact component at time t. Used to characterize sudden load disturbances that deviate from the normal load change trend; The original load value at time t.

[0131] The diagram showing the identification of the original load reference component and the impact component is as follows. Figure 2 As shown, through Figure 2 It can be seen that the decomposition method can extract the regular trend of the original load and separate the sudden load fluctuations into impact components, providing a data foundation for subsequent impact event identification and feature extraction.

[0132] (2) Step 2: Analyze the statistical distribution characteristics of the impact components, determine the impact identification threshold, then detect the impact event and extract the characteristic parameters of the impact event; wherein, the characteristic parameters of the impact event include: amplitude, ramp rate, duration and adjacent impact interval time;

[0133] Step 2 specifically includes:

[0134] Step 2-1: Calculate the statistical mean and standard deviation of the impact component during the analysis period to obtain the statistical distribution characteristics of the impact component:

[0135] ;

[0136] Where: M is the total number of sampling points during the analysis period; This represents the statistical mean of the impact components; The standard deviation of the impact component;

[0137] Step 2-2: Based on the statistical mean and standard deviation of the impact components, determine the impact identification threshold as follows:

[0138] ;

[0139] In the formula: The threshold for impact identification; This is the threshold adjustment coefficient;

[0140] Steps 2-3: Traverse the impact component sequence, merge consecutive sampling points exceeding the impact identification threshold into impact events, and extract the feature parameters of the impact events as follows:

[0141] ;

[0142] In the formula: Let be the amplitude of the i-th impact event; Let be the ramp rate during the rising phase of the i-th impact event; Let be the duration of the i-th impact event; The interval between adjacent impact events is the time between the i-th impact event and the next impact event. Let i be the start time of the i-th impact event; Let i be the end time of the i-th impact event; This is the moment when the i-th impact event reaches its peak. Let be the multidimensional impact characteristic parameter vector of the i-th impact event.

[0143] Statistics of multidimensional impact characteristic parameters, such as Figure 3 As shown, through Figure 3 It can be seen that the impact events differ in amplitude, ramp rate, duration and interval between adjacent impacts, which can provide a basis for classifying typical working conditions and calculating energy storage demand.

[0144] (3) Step 3: Based on the characteristic parameters of the impact event and the energy storage recovery time threshold of the hybrid energy storage system, classify the operating conditions of the hybrid energy storage system to construct typical operating conditions of three types of hybrid energy storage systems: normal operation, non-superimposed impact scenario, and impact superimposed scenario.

[0145] Step S3 specifically includes:

[0146] Step 3-1: Based on the duration and impact components of the impact event, calculate the equivalent impact energy corresponding to each impact event:

[0147] ;

[0148] In the formula: Let be the equivalent impact energy corresponding to the i-th impact event;

[0149] Step 3-2: Based on the relationship between the adjacent impact interval time and the energy storage recovery time threshold, determine the recovery insufficiency coefficient corresponding to the adjacent impact interval as follows:

[0150] ;

[0151] In the formula: The insufficient recovery coefficient corresponding to the i-th adjacent impact interval; This is the energy storage recovery time threshold;

[0152] Step 3-3: Based on the insufficient recovery coefficient, calculate the impact superposition index within the analysis period as follows:

[0153] ;

[0154] In the formula: Γ is the index of the degree of impact superposition within the analysis period; NI is the number of impact events within the analysis period;

[0155] Steps 3-4: Based on the number of impact events (NI) and the impact superposition index (Γ) within the analysis period, the operating conditions of the hybrid energy storage system are divided into three typical operating scenarios: normal operation, non-superposition impact scenario, and impact superposition scenario.

[0156] ;

[0157] Where: S represents a typical operating scenario for the energy storage system; This is a normal operating scenario; This is a non-cumulative impact scenario; To impact and overlay scenarios.

[0158] Three typical scenario diagrams are shown below. Figure 4 As shown. (Through) Figure 4 It can be seen that, based on the number of impact events and the recovery between adjacent impacts, the operating conditions can be divided into three categories: normal operation, non-superimposed impact, and impact superposition.

[0159] (4) Step 4: Based on the characteristic parameters of the impact event and typical operating scenarios, construct a hybrid energy storage quantification demand model that includes rapid response, continuous support, and recovery margin requirements:

[0160] Step S4 specifically includes:

[0161] Step 4-1: Decompose the hybrid energy storage response demand into impact amplitude suppression power demand, power ramp-up following demand, continuous support energy demand, and recovery margin energy demand as follows:

[0162] ;

[0163] In the formula: This is a vector of quantified energy storage demand indicators; To suppress the power demand for impact amplitude; To meet the power ramp-following requirements of the energy storage system; To continuously support energy demand; To restore the margin of energy demand;

[0164] Step 4-2: Based on the impact amplitude, ramp rate, and equivalent impact energy, calculate the fractional energy storage requirements corresponding to each impact event:

[0165] ;

[0166] In the formula: The peak energy storage compensation power requirement corresponding to the i-th impact event; The percentage of residual impact that is allowed to remain after compensation; For the i-th impact event, the hill-climbing and following requirement is required. The continuous support energy requirement corresponding to the i-th impact event; For energy storage discharge efficiency;

[0167] Step 4-3: Based on the quantification requirements of each impact event, determine the power amplitude requirement, power ramp-up requirement, and continuous support energy requirement within the analysis period as follows:

[0168] ;

[0169] Step 4-4: Based on the recoverable energy within adjacent impact intervals and the unrecoverable energy from consecutive impacts, determine the recovery margin energy requirement as follows:

[0170] ;

[0171] In the formula: This represents the accumulated energy that the energy storage system has not yet recovered before the arrival of the i-th impact event; This represents the cumulative energy that the energy storage system has not yet recovered before the arrival of the (i+1)th impact event; Let be the recoverable energy of the energy storage system within the i-th adjacent impact interval; Let be the continuous support energy requirement corresponding to the i-th impact event.

[0172] (5) Step 5: Based on the rapid response requirements, continuous support requirements and recovery margin requirements obtained in step 4), and combining the rapid response characteristics of flywheel energy storage and the continuous support characteristics of lithium iron phosphate battery energy storage, establish an operational feasibility verification model for the hybrid energy storage system in terms of impact compensation, power distribution, energy state, recovery margin and life loss.

[0173] Step S5 specifically includes:

[0174] Step 5-1: Establish a hybrid energy storage impact compensation power model, specifically as follows:

[0175] ;

[0176] In the formula: The total compensation power of the hybrid energy storage system at time t; The compensating operating power for flywheel energy storage at time t; The compensation operating power of the lithium iron phosphate battery at time t; where flywheel energy storage is used to undertake the task of rapid power change and high-speed compensation in the initial stage of the impact, and lithium iron phosphate battery is used to undertake the task of energy support in the continuous stage of the impact. Together, they form a synergistic compensation power for sudden load impact.

[0177] Comparison of impact compensation before and after is shown in the figure. Figure 5 As shown. (Through) Figure 5 It can be seen that the total compensation power of the hybrid energy storage system can follow the impact component well, and the residual impact after compensation is significantly reduced, indicating that the synergistic compensation of flywheel energy storage and lithium iron phosphate battery can effectively suppress sudden load impact.

[0178] Step 5-2: Establish the impact compensation deviation and impact suppression verification model as follows:

[0179] ;

[0180] In the formula: The impact compensation deviation at time t; Let t be the impact component at time t; The upper limit of residual impact power allowed to be retained after compensation; The percentage of residual impact that is allowed to remain after compensation; To analyze the peak characteristic quantities of the impact components within the time period; Let be the impact suppression rate for the i-th impact event; The residual impact peak value after compensation for the i-th impact event;

[0181] Impact compensation deviation verification as follows Figure 6 As shown. (Through) Figure 6It can be seen that the compensation deviations corresponding to each impact event are all within the upper and lower limits of the allowable residuals, indicating that the established impact suppression constraints are satisfied.

[0182] Step 5-3: Establish a power operation verification model for flywheel energy storage and lithium iron phosphate batteries, specifically as follows:

[0183] ;

[0184] In the formula: Rated power for flywheel energy storage; This refers to the rated power of lithium iron phosphate batteries; Δt represents the maximum power change rate of the flywheel energy storage at rated power; Δt is the sampling time interval. The recovery charging power of the lithium iron phosphate battery at time t; Let t be the available recovery power of the system for energy storage recovery at time t;

[0185] Step 5-4: Establish a verification model for the energy state and state of charge of lithium iron phosphate batteries, specifically as follows:

[0186] ;

[0187] In the formula: Let t be the available energy of the lithium iron phosphate battery at time t; The discharge efficiency of lithium iron phosphate batteries; The charging efficiency of lithium iron phosphate batteries; The state of charge of the lithium iron phosphate battery at time t; This refers to the rated capacity of lithium iron phosphate batteries; This is the state-of-charge limit for lithium iron phosphate batteries; This represents the upper limit of the state of charge (SOC) of lithium iron phosphate batteries.

[0188] Step 5-5: Establish the calculation models for the actual discharge energy and actual recovery energy of the lithium iron phosphate battery as follows:

[0189] ;

[0190] In the formula: Let be the actual discharge energy of the lithium iron phosphate battery during the i-th impact event; The actual recovered energy of the lithium iron phosphate battery within the i-th adjacent impact interval; The actual recovered energy of the lithium iron phosphate battery from the end of the last impact event to the end of the analysis period; Let i be the start time of the i-th impact event; Let be the end time of the i-th impact event; T is the end time of the analysis period;

[0191] Steps 5-6: Establish a verification model for cumulative unrecovered energy and recovery margin under continuous impact conditions, specifically as follows:

[0192] ;

[0193] In the formula: This represents the actual cumulative unrecovered energy prior to the arrival of the i-th impact event; This represents the actual cumulative unrecovered energy prior to the arrival of the (i+1)th impact event; To analyze the actual cumulative unrecovered energy at the end of the analysis period;

[0194] Flywheel energy storage and the power distribution and recharging process of lithium iron phosphate batteries, as follows Figure 7 As shown, through Figure 7 It can be seen that flywheel energy storage mainly undertakes the rapid power response in the initial stage of the impact, while lithium iron phosphate batteries provide continuous support and perform recovery charging at the end of the impact interval and analysis period, thus achieving the coordinated operation of the two types of energy storage.

[0195] Steps 5-7: Establish a characterization model for the impact-induced life loss of lithium iron phosphate batteries, specifically as follows:

[0196] ;

[0197] In the formula: Let be the characteristic quantity of the battery discharge depth corresponding to the i-th impact event; This is a characterization of the battery charge / discharge rate corresponding to the i-th impact event; This represents the peak compensation power of the battery corresponding to the i-th impact event; is the life loss correction coefficient corresponding to the i-th impact event, used to reflect the impact discharge depth, charge-discharge rate and insufficient recovery on battery life degradation; This is a characterization of the impact-induced life loss of lithium iron phosphate batteries.

[0198] (6) Step 6: Based on the power amplitude demand, power ramp-following demand, continuous support energy demand, and recovery margin energy demand obtained in Step 4), and combined with the hybrid energy storage operation feasibility verification relationship established in Step 5), construct a hybrid energy storage capacity-operation collaborative optimization model. Under the condition of meeting the requirements of capacity configuration, impact suppression, power operation, state of charge, recovery margin, and safe operation, and with the objective of minimizing the sum of the equivalent configuration cost of hybrid energy storage and the impact-added lifetime loss cost, solve and output the optimal configuration scheme of hybrid energy storage:

[0199] Step S6 specifically includes:

[0200] Step 6-1: Establish the hybrid energy storage configuration decision vector, specifically as follows:

[0201] ;

[0202] In the formula: Z is the hybrid energy storage configuration decision vector; Rated power for flywheel energy storage; Rated capacity for flywheel energy storage; This refers to the rated power of lithium iron phosphate batteries; This refers to the rated capacity of lithium iron phosphate batteries;

[0203] Step 6-2: Establish the power amplitude configuration relationship for hybrid energy storage, specifically as follows:

[0204] ;

[0205] Flywheel energy storage and lithium iron phosphate batteries jointly undertake the power compensation task of sudden load impact, and their rated power configuration should meet the power requirements for suppressing the impact amplitude.

[0206] Step 6-3: Establish the flywheel energy storage fast response configuration relationship, specifically as follows:

[0207] ;

[0208] In the formula: Flywheel energy storage can be used for rapid response energy boundaries. By meeting power ramp-up requirements and short-term rapid response energy boundaries, flywheel energy storage can undertake rapid dynamic compensation tasks in the initial stage of sudden shocks.

[0209] Step 6-4: Establish the configuration relationship between the continuous support and recovery margin of the lithium iron phosphate battery, specifically as follows:

[0210] ;

[0211] Step 6-5: Establish an equivalent configuration cost model for hybrid energy storage, specifically as follows:

[0212] ;

[0213] In the formula: Cost of equivalent configuration for hybrid energy storage; Cost per unit power for flywheel energy storage; Cost per unit capacity of flywheel energy storage; Cost per unit power of lithium iron phosphate batteries; Cost per unit capacity of lithium iron phosphate batteries;

[0214] Step 6-6: Based on the characteristic quantities of impact-induced additional life loss in lithium iron phosphate batteries, establish an impact-induced additional life loss cost model, specifically as follows:

[0215] ;

[0216] In the formula: To reduce the additional lifespan loss costs associated with impact; This is the unit impact life loss cost coefficient for lithium iron phosphate batteries.

[0217] Steps 6-7: Establish hybrid energy storage capacity-operation co-optimization objectives, specifically:

[0218] ;

[0219] In the formula: C is the comprehensive optimization target cost of hybrid energy storage; This is the optimal configuration scheme for hybrid energy storage;

[0220] Steps 6-8: Solve for and output the optimal configuration scheme for hybrid energy storage, specifically:

[0221] ;

[0222] In the formula: The optimal rated power for flywheel energy storage; The optimal rated capacity for flywheel energy storage; This represents the optimal rated power for lithium iron phosphate batteries. This represents the optimal rated capacity for lithium iron phosphate batteries. The overall optimization cost corresponding to the optimal configuration scheme; The equivalent configuration cost of hybrid energy storage corresponding to the optimal configuration scheme; The impact-induced life loss cost corresponding to the optimal configuration scheme.

[0223] Verification of flywheel energy storage state of energy, lithium iron phosphate battery SOC and continuous impact recovery margin, as follows: Figure 8 As shown. (Through) Figure 8 It can be seen that the flywheel energy storage energy and the SOC of the lithium iron phosphate battery are both kept within the allowable range, and the cumulative unrecovered energy is lower than the recovery margin requirement, indicating that the configuration scheme meets the energy state and continuous impact recovery constraints.

[0224] The result diagram of the hybrid energy storage configuration is shown below. Figure 9 As shown. (Through) Figure 9 It can be seen that the rated power configuration can cover the maximum operational impact demand, and the rated capacity of both types of energy storage can meet the corresponding capacity requirements, indicating that the obtained configuration scheme has the necessary power and energy margin.

[0225] The impact suppression effect of various impact events, for example Figure 10 As shown. By Figure 10 As can be seen, the residual impact peak value after each compensation is lower than the upper limit of the allowable residual impact, the impact suppression rate is stable at 95.4% to 95.5%, and the average impact suppression rate is about 95.4%, indicating that the configuration scheme has a stable impact suppression effect.

[0226] In this specific embodiment, a flexible energy storage configuration method considering sudden load impact scenarios is proposed. For a hybrid energy storage system composed of flywheel energy storage and lithium iron phosphate battery energy storage, the power and capacity of the hybrid energy storage system are optimized based on sudden load impact identification, typical impact scenario classification, and a hybrid energy storage capacity-operation collaborative optimization model. This method can improve the impact suppression capability, recovery support capability, and operational safety of the hybrid energy storage system under sudden load impact and impact superposition scenarios.

[0227] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A flexible energy storage configuration method considering sudden load impact scenarios, based on a hybrid energy storage system; The hybrid energy storage system includes: Flywheel energy storage and lithium iron phosphate battery energy storage; characterized in that the flexible energy storage configuration method includes: Step S1: Analyze the raw load data to decompose it into a baseline component characterizing regular changes and an impact component reflecting sudden disturbances. Step S2: Obtain the statistical distribution characteristics of the impact components, and determine the impact identification threshold based on the statistical distribution characteristics of the impact components. Then, detect the impact event and extract the feature parameters of the impact event. The feature parameters of the impact event include: amplitude, ramp rate, duration, and time interval between adjacent impacts. Step S3: Based on the characteristic parameters of the impact event and the energy storage recovery time threshold of the hybrid energy storage system, the operating conditions of the hybrid energy storage system are divided into three typical operating conditions: normal operation, non-superimposed impact scenario, and impact superimposed scenario. Step S4: Based on the characteristic parameters of the impact event and typical operating scenarios, construct a hybrid energy storage quantification demand model that includes rapid response requirements, continuous support requirements, and recovery margin requirements; Step S5: Based on the hybrid energy storage fractional demand model, and combining the rapid response characteristics of flywheel energy storage and the continuous support characteristics of lithium iron phosphate battery energy storage, establish an operational feasibility verification model for the hybrid energy storage system in terms of impact compensation, power operation, energy state, recovery margin, and lifespan loss. Step S6: Based on the hybrid energy storage quantification demand model and operation feasibility verification model, construct a hybrid energy storage capacity-operation collaborative optimization model. With the goal of minimizing the sum of the equivalent configuration cost of hybrid energy storage and the impact-added life loss cost, solve and output the optimal configuration scheme of hybrid energy storage.

2. The flexible energy storage configuration method considering sudden load shock scenarios according to claim 1, characterized in that, Step S1 includes: Step S1.1: Obtain the original load sequence within the analysis period, and extract the baseline component from the original load sequence using the sliding window averaging method: ； In the formula: Let be the reference component at time t. Used to characterize the typical fluctuation trend of load over time; is the original load value corresponding to the k-th sampling point within the sliding window; N is the length of the sliding window; t is the sampling time; k is the sampling point number within the sliding window; Step S1.2: Subtract the original load value at time t from the reference component to obtain the impact component reflecting the characteristics of the sudden disturbance: ； In the formula: Let be the impact component at time t. Used to characterize sudden load disturbances that deviate from the normal load change trend; The original load value at time t.

3. The flexible energy storage configuration method considering sudden load shock scenarios according to claim 2, characterized in that, Step S2 specifically includes: Step S2.1: Calculate the statistical mean and standard deviation of the impact component during the analysis period to obtain the statistical distribution characteristics of the impact component: ； In the formula: This represents the total number of sampling points within the analysis period. This represents the statistical mean of the impact components; The standard deviation of the impact component; Step S2.2: Based on the statistical mean and standard deviation of the impact components, determine the impact identification threshold as follows: ； In the formula: The threshold for impact identification; This is the threshold adjustment coefficient; Step S2.3: Traverse the impact component sequence, merge consecutive sampling points exceeding the impact identification threshold into impact events, and extract the amplitude, ramp rate, duration, and adjacent impact interval of the impact events as follows: ； In the formula: Let be the amplitude of the i-th impact event; Let be the ramp rate during the rising phase of the i-th impact event; Let be the duration of the i-th impact event; The interval between adjacent impact events is the time between the i-th impact event and the next impact event. Let i be the start time of the i-th impact event; Let i be the end time of the i-th impact event; This is the moment when the i-th impact event reaches its peak. Let be the multidimensional impact characteristic parameter vector of the i-th impact event.

4. The flexible energy storage configuration method considering sudden load shock scenarios according to claim 3, characterized in that, Step S3 specifically includes: Step S3.1: Based on the duration and impact components of the impact event, calculate the equivalent impact energy corresponding to each impact event: ； In the formula: Let be the equivalent impact energy corresponding to the i-th impact event; Step S3.2: Based on the relationship between the adjacent impact interval time and the energy storage recovery time threshold, determine the recovery insufficiency coefficient corresponding to the adjacent impact interval as follows: ； In the formula: This is the inadequacy coefficient corresponding to the i-th adjacent impact interval; This is the energy storage recovery time threshold; Step S3.3: Based on the insufficient recovery coefficient, calculate the impact superposition index within the analysis period as follows: ； In the formula: Γ is the index of the degree of impact superposition within the analysis period; NI is the number of impact events within the analysis period; Step S3.4: Based on the number of impact events NI and the impact superposition index Γ during the analysis period, the operating conditions of the hybrid energy storage system are divided into three categories: normal operation, non-superposition impact scenario, and impact superposition scenario. Typical operating conditions of the hybrid energy storage system are as follows: ； Where: S represents a typical operating scenario for a hybrid energy storage system; This is a normal operating scenario; This is a non-cumulative impact scenario; To impact and superimpose scenes.

5. The flexible energy storage configuration method considering sudden load shock scenarios according to claim 4, characterized in that, Step S4 specifically includes: Step S4.1: Decompose the hybrid energy storage response demand into impact amplitude suppression power demand, power ramp-up following demand, continuous support energy demand, and recovery margin energy demand as follows: ； In the formula: This is a vector of quantified energy storage demand indicators; To suppress the power demand for impact amplitude; To meet the power ramp-following requirements of the energy storage system; To continuously support energy demand; To restore the margin of energy demand; Step S4.2: Based on the impact amplitude, ramp rate, and equivalent impact energy, calculate the fractional energy storage requirements corresponding to each impact event: ； In the formula: The peak energy storage compensation power requirement corresponding to the i-th impact event; The percentage of residual impact that is allowed to remain after compensation; For the i-th impact event, the hill-climbing and following requirement is required. The continuous support energy requirement corresponding to the i-th impact event; For energy storage discharge efficiency; Step S4.3: Based on the quantification requirements of each impact event, determine the power amplitude requirement, power ramp-up requirement, and continuous support energy requirement within the analysis period as follows: ； Step S4.4: Based on the recoverable energy within adjacent impact intervals and the unrecoverable energy from consecutive impacts, determine the recovery margin energy requirement as follows: ； In the formula: This represents the accumulated energy that the energy storage system has not yet recovered before the arrival of the i-th impact event; This represents the cumulative energy that the energy storage system has not yet recovered before the arrival of the (i+1)th impact event; Let be the recoverable energy of the energy storage system within the i-th adjacent impact interval; Let be the continuous support energy requirement corresponding to the i-th impact event.

6. The flexible energy storage configuration method considering sudden load shock scenarios according to claim 5, characterized in that, Step S5 specifically includes: Step S5.1: Establish the hybrid energy storage impact compensation power model as follows: ； In the formula: The total compensation power of the hybrid energy storage system at time t; The compensating operating power for flywheel energy storage at time t; This represents the compensated operating power of the lithium iron phosphate battery at time t. Step S5.2: Establish the impact compensation deviation and impact suppression verification model as follows: ； In the formula: The impact compensation deviation at time t; Let t be the impact component at time t; The upper limit of residual impact power allowed to be retained after compensation; The percentage of residual impact that is allowed to remain after compensation; To analyze the peak characteristic quantities of the impact components within the time period; Let be the impact suppression rate for the i-th impact event; The residual impact peak value after compensation for the i-th impact event; Step S5.3: Establish the power operation verification model for flywheel energy storage and lithium iron phosphate batteries as follows: ； In the formula: Rated power for flywheel energy storage; This refers to the rated power of lithium iron phosphate batteries; Δt represents the maximum power change rate of the flywheel energy storage at rated power; Δt is the sampling time interval. The recovery charging power of the lithium iron phosphate battery at time t; Let t be the available recovery power of the system for energy storage recovery at time t; Step S5.4: Establish the energy state and state of charge verification models for lithium iron phosphate batteries as follows: ； In the formula: Let t be the available energy of the lithium iron phosphate battery at time t; The discharge efficiency of lithium iron phosphate batteries; The charging efficiency of lithium iron phosphate batteries; The state of charge of the lithium iron phosphate battery at time t; This refers to the rated capacity of lithium iron phosphate batteries; This is the state-of-charge limit for lithium iron phosphate batteries; This represents the upper limit of the state of charge (SOC) of lithium iron phosphate batteries. Step S5.5: Establish the calculation models for the actual discharge energy and actual recovery energy of the lithium iron phosphate battery as follows: ； In the formula: Let be the actual discharge energy of the lithium iron phosphate battery during the i-th impact event; The actual recovered energy of the lithium iron phosphate battery within the i-th adjacent impact interval; The actual recovered energy of the lithium iron phosphate battery from the end of the last impact event to the end of the analysis period; Let i be the start time of the i-th impact event; Let be the end time of the i-th impact event; T is the end time of the analysis period; Step S5.6: Establish the verification model for cumulative unrecovered energy and recovery margin under continuous impact conditions as follows: ； In the formula: This represents the actual cumulative unrecovered energy prior to the arrival of the i-th impact event; This represents the actual cumulative unrecovered energy prior to the arrival of the (i+1)th impact event; To analyze the actual cumulative unrecovered energy at the end of the analysis period; Step S5.7: Establish a characterization model for the impact-induced life loss of lithium iron phosphate batteries, specifically as follows: ； In the formula: Let be the characteristic quantity of the battery discharge depth corresponding to the i-th impact event; This is a characterization of the battery charge / discharge rate corresponding to the i-th impact event; This represents the peak compensation power of the battery corresponding to the i-th impact event; is the life loss correction coefficient corresponding to the i-th impact event, used to reflect the impact discharge depth, charge-discharge rate and insufficient recovery on battery life degradation; This is a characterization of the impact-induced life loss of lithium iron phosphate batteries.

7. The flexible energy storage configuration method considering sudden load impact scenarios according to claim 6, characterized in that, Step S6 specifically includes: Step S6.1: Establish the hybrid energy storage configuration decision vector as follows: ； In the formula: Z is the hybrid energy storage configuration decision vector; Rated power for flywheel energy storage; Rated capacity for flywheel energy storage; This refers to the rated power of lithium iron phosphate batteries; This refers to the rated capacity of lithium iron phosphate batteries; Step S6.2: Establish the hybrid energy storage power amplitude configuration relationship as follows: ； Step S6.3: Establish the flywheel energy storage fast response configuration relationship as follows: ； In the formula: Energy boundaries for flywheel energy storage that can be used for rapid response; Step S6.4: Establish the configuration relationship between the continuous support and recovery margin of the lithium iron phosphate battery as follows: ； Step S6.5: Establish the equivalent configuration cost model for hybrid energy storage as follows: ； In the formula: Cost of equivalent configuration for hybrid energy storage; Cost per unit power for flywheel energy storage; Cost per unit capacity of flywheel energy storage; Cost per unit power of lithium iron phosphate batteries; Cost per unit capacity of lithium iron phosphate batteries; Step S6.6: Based on the characteristic quantities of impact-induced additional life loss in lithium iron phosphate batteries, establish the impact-induced additional life loss cost model as follows: ； In the formula: To reduce the additional lifespan loss costs associated with impact; This is the unit impact life loss cost coefficient for lithium iron phosphate batteries. Step S6.7: Establish the hybrid energy storage capacity-operation co-optimization objective as follows: ； In the formula: C is the comprehensive optimization target cost of hybrid energy storage; This is the optimal configuration scheme for hybrid energy storage; Step S6.8: Solve for and output the optimal configuration scheme for hybrid energy storage as follows: ； In the formula: The optimal rated power for flywheel energy storage; The optimal rated capacity for flywheel energy storage; This represents the optimal rated power for lithium iron phosphate batteries. This represents the optimal rated capacity for lithium iron phosphate batteries. The overall optimization cost corresponding to the optimal configuration scheme; The equivalent configuration cost of hybrid energy storage corresponding to the optimal configuration scheme; The impact-induced life loss cost corresponding to the optimal configuration scheme.

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