A multi-dimensional wind storage combined system frequency modulation capability evaluation method, system, device and medium

Abstract

The application provides a multi-dimensional wind storage combined system frequency modulation capability evaluation method, system, device and medium, and belongs to the technical field of power system operation and control. The method comprises the following steps: obtaining wind speed randomness parameters, load fluctuation parameters and energy storage SOC limitation parameters as input basis; constructing a system frequency response model; determining evaluation indexes of frequency regulation reserve dimensions based on the wind speed randomness parameters and the energy storage SOC limitation parameters; determining evaluation indexes of frequency regulation strategy dimensions based on power regulation characteristics of each energy in the system frequency response model; determining evaluation indexes of frequency regulation effect dimensions through deviation statistics of actual frequency fluctuation data and rated frequency; and quantitatively analyzing the evaluation indexes to output a comprehensive evaluation result of the wind storage combined system frequency modulation capability.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of power system operation and control, and particularly relates to a multi-dimensional wind-storage combined system frequency modulation capability evaluation method, system, device and medium. BACKGROUND

[0002] With the increasing penetration of wind power in power systems, its randomness and volatility pose great challenges to the frequency modulation of power systems. When wind turbines are operating, due to the large fluctuations in wind power output with wind speed and the difficulty in accurate prediction, it is difficult to quickly and effectively respond to system frequency changes and provide stable and reliable frequency modulation support. The energy storage system has the characteristics of fast charging and discharging, bidirectional regulation, etc. The wind-storage combined system formed by combining wind turbines and energy storage has become an effective way to solve the frequency modulation problem of high wind power penetration systems. However, how to scientifically and accurately evaluate the frequency modulation capability of the combined system has become a key problem to be solved.

[0003] The frequency modulation capability evaluation methods of traditional power systems are mostly for conventional energy sources such as thermal power and hydropower, which have stable power generation characteristics and strong controllability. The evaluation index and system cannot be directly applied to the wind-storage combined system. Unlike synchronous generators, the wind speed inside the wind-storage combined system is complex and the state of energy storage changes dynamically, which is affected by wind resources and its own operating conditions, making it difficult to accurately quantify and estimate.

[0004] The existing wind-storage combined frequency modulation evaluation system lacks consideration of multiple uncertain factors, and based on deterministic scenarios, it is difficult to reflect the real performance of the control strategy under complex operating conditions. The index cannot accurately evaluate the frequency modulation contribution rate of the wind-storage combined system under different wind speed conditions, and there is also a lack of evaluation method for the dynamic cooperation effect of wind turbines and energy storage during frequency modulation.

[0005] Related methods fail to fully integrate the cross-influence of wind speed fluctuations, energy storage state of charge, equipment operating parameters and other multi-dimensional variables on frequency modulation capability, resulting in deviations between the evaluation model and the actual system characteristics, and making it difficult to fully depict the real frequency modulation potential of the system.

[0006] The wind-storage combined system shows significant differences in frequency modulation effect under different wind speed intervals, energy storage charging and discharging stages, and grid load scenarios, while related methods are mostly based on static models or fixed operating condition assumptions, making it difficult to capture the dynamic frequency modulation performance of the system under complex and variable operating conditions.

[0007] In summary, the existing wind-storage combined system frequency modulation capability evaluation methods have many limitations and cannot meet the current demand for accurate and comprehensive evaluation of the frequency modulation capability of wind-storage combined systems in power systems. SUMMARY

[0008] The application provides a multi-dimensional wind storage combined system frequency modulation capability evaluation method, which integrates multi-factor coupling analysis and multi-dimensional and multi-index frequency modulation capability, constructs a precise evaluation system covering full operation conditions and multiple performance dimensions, and provides a scientific basis for optimal configuration of frequency modulation resources of the wind storage combined system, and comprehensively quantifies the frequency modulation capability of the wind storage combined system from the front, middle and back of frequency modulation.

[0009] The method comprises:

[0010] Step S101: Obtain wind speed randomness parameters, load fluctuation parameters and energy storage SOC limitation parameters as input basis;

[0011] Step S102: Based on the parameters obtained in step S101, a system frequency response model is constructed to describe the process of adjusting mechanical power through a speed governor-turbine transfer function of a conventional generator set, adjusting electromagnetic power through rotor kinetic energy conversion and virtual inertia control of a wind turbine, and adjusting charging and discharging power of an energy storage system through virtual droop control under frequency deviation;

[0012] Step S103: Based on the wind speed randomness parameters and the energy storage SOC limitation parameters, the evaluation indexes of the frequency regulation reserve dimension are determined;

[0013] Step S104: Based on the power regulation characteristics of each energy in the system frequency response model, the evaluation indexes of the frequency regulation strategy dimension are determined;

[0014] Step S105: The evaluation indexes of the frequency regulation effect dimension are determined by the deviation statistics of the actual frequency fluctuation data and the rated frequency;

[0015] Step S106: The frequency regulation reserve dimension evaluation indexes, the frequency regulation strategy dimension evaluation indexes and the frequency regulation effect dimension evaluation indexes are quantitatively analyzed, and the comprehensive evaluation result of the frequency modulation capability of the wind storage combined system is output.

[0016] Further, in step S101, the wind speed randomness parameters are represented by a Weibull distribution function, and the probability density function of the wind speed is represented as:

[0017]

[0018] In the formula, v V represents the wind speed, k is a shape parameter, c is a scale parameter;

[0019] The energy storage SOC limitation parameter is represented as:

[0020]

[0021] In the formula, E res,Bis the estimated value of the energy storage regulation energy; SOC is the state of charge value; SOC min is the minimum state of charge limit of the energy storage; SOC max is the maximum state of charge limit of the energy storage; E B is the rated capacity of the energy storage system; η d is the discharge efficiency of the energy storage; η c is the charging efficiency of the energy storage; η is the capacity proportion of the energy storage configured in the wind farm; P is the discharge power of the energy storage system.

[0022] It should be further explained that in step S101, the energy storage discharge regulation power based on the state of charge is represented as:

[0023]

[0024]

[0025]

[0026] In the formula, SOC < SOC min , S SOC1 = 0; SOC 1≤ SOC , S SOC1 = 1; SOC min ≤ SOC < SOC 1; P res,B1 is the energy storage discharge regulation power value; P B1 is the rated discharge power of the energy storage; S SOC1 is the discharge correction coefficient; SOC 1 is the critical value between the over-discharge state and the normal operation state of the energy storage; n is the energy storage adaptive regulation coefficient;

[0027] The energy storage charging regulation power based on the state of charge is represented as:

[0028]

[0029]

[0030]

[0031] In the formula, SOC > SOC max , S SOC2 = 0; SOC ≤ SOC 2, S SOC2 = 1; SOC 2 < n < 3 SOC ≤ SOC max ,

[0032] In the formula, P res,B2 is the energy storage charging adjustment power value; P B2 is the rated charging power of the energy storage; S SOC2 is the charging correction coefficient; SOC 2 is the critical value of the normal working state and the overcharging state of the energy storage unit, n is the energy storage adaptive adjustment coefficient.

[0033] It should be further explained that the system frequency response model of step S102 is represented as:

[0034]

[0035] In the formula, T b is the response time constant of the energy storage system control, s is the complex frequency variable of Laplace transform, K b is the virtual droop coefficient.

[0036] It should be further explained that step S103 further includes: the frequency regulation standby dimension measures the adjustable ability of the system before the disturbance occurs;

[0037] The wind turbine standby kinetic energy / power is configured, which represents the rotational kinetic energy margin that can be released by the rotor of the wind turbine, and its value depends on the difference between the rotor speed and the safety threshold, indicating the standby kinetic energy and power of the wind turbine for participating in frequency modulation;

[0038] The energy storage standby energy / power is configured, which is represented as the energy / power adjustment margin calculated by the state of charge safety domain.

[0039] It should be further explained that step S104 further includes configuring the frequency regulation strategy dimension evaluation control algorithm, which is a coordinated allocation method for wind and energy storage resources;

[0040] Specifically, it includes:

[0041] The support power of the wind storage combined system is defined as the active output power of the wind turbine increased in response to the frequency deviation of the system and the real-time charge / discharge power of the energy storage used to compensate for the power shortage caused by the frequency fluctuation;

[0042] The frequency modulation contribution rate of the energy storage is defined as the total charge / discharge amount of the energy storage E sup and the total charge / discharge power P sup ;

[0043] The contribution rate calculation formula is C 1= E sup / E total ×100%, C 2= P sup / P total ×100%

[0044] Wherein, C 1and C 2are the contribution rates of the energy storage; E total is the total energy change of the wind storage combined system; P total is the total power change of the wind storage combined system.

[0045] Further, in step S105, the evaluation index of the frequency regulation effect dimension includes:

[0046] The wind turbine utilization rate is defined μ ; the ratio of the actual rotor kinetic energy released by the wind turbine to the maximum rotor kinetic energy reserve available during the frequency regulation process; the wind turbine energy utilization rate calculation formula is μ 1 = Δ E W / Δ E k；

[0047] The ratio of the actual maximum power output of the wind turbine to the average adjustable output power during the frequency regulation process; the wind turbine power utilization rate calculation formula is μ 2 = max{Δ P W} / Δ P ω ;

[0048] The root mean square error of frequency fluctuation is defined, which represents the dispersion degree of the frequency deviation in the statistical period, and the calculation formula is as follows:

[0049]

[0050] wherein, f i is the current actual system frequency; f N is the rated system frequency, N is the number of sampling points in the frequency fluctuation process;

[0051] The mean absolute error (MAE) of the frequency fluctuation is defined: reflecting the average level of the absolute deviation of the frequency in the statistical period, calculated by the following formula:

[0052] .

[0053] The application also provides a multi-dimensional wind storage combined system frequency modulation capability evaluation system, the system comprising:

[0054] A parameter acquisition module is configured to acquire wind speed randomness parameters, load fluctuation parameters, and energy storage SOC limitation parameters as input basis.

[0055] A frequency response construction module is configured to acquire the parameters and construct a system frequency response model to describe the process of adjusting mechanical power by a speed governor-turbine transfer function of a conventional generator set, adjusting electromagnetic power by rotor kinetic energy conversion and virtual inertia control of a wind turbine, and adjusting charging and discharging power by virtual droop control of an energy storage system under frequency deviation.

[0056] A backup index evaluation module is configured to determine evaluation indexes of frequency regulation backup dimensions based on the wind speed randomness parameters and the energy storage SOC limitation parameters.

[0057] A strategy index evaluation module is configured to determine evaluation indexes of frequency regulation strategy dimensions based on power regulation characteristics of each energy in the system frequency response model.

[0058] An effect index determination module is configured to determine evaluation indexes of frequency regulation effect dimensions by deviation statistics of actual frequency fluctuation data and rated frequency.

[0059] A comprehensive evaluation module is configured to quantitatively analyze the evaluation indexes of the frequency regulation backup dimensions, the evaluation indexes of the frequency regulation strategy dimensions, and the evaluation indexes of the frequency regulation effect dimensions, and output a comprehensive evaluation result of the wind storage combined system frequency modulation capability.

[0060] According to another embodiment of the application, an electronic device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the multi-dimensional wind storage combined system frequency modulation capability evaluation method when executing the program.

[0061] According to still another embodiment of the present application, a storage medium having a computer program stored thereon is also provided, the computer program being executed by a processor to implement the steps of the method for evaluating the frequency regulation capability of the multi-dimensional wind storage combined system.

[0062] From the above technical solutions, the present application has the following advantages:

[0063] The method for evaluating the frequency regulation capability of the multi-dimensional wind storage combined system provided by the present application quantifies the randomness of wind speed, load fluctuation and SOC limitation of energy storage, constructs a frequency response model containing traditional units, wind turbines and energy storage, and realizes dynamic description of mechanical power, electromagnetic power and energy storage power regulation in the frequency regulation process.

[0064] The strategy dimension of the present application evaluates the strategy rationality of wind storage collaborative frequency regulation through joint support power and energy storage contribution rate.

[0065] The quantification of wind speed randomness and energy storage SOC operating state in the present application combines wind speed, rotor speed and energy storage state of charge randomness parameters with wind turbine rotor speed safety threshold and energy storage SOC minimum and maximum values, so that the evaluation index can reflect the constraint conditions in actual operation. When the energy storage SOC is close to the upper limit, the available charging power is automatically limited, and when the energy storage SOC is close to the lower limit, the available discharging power is automatically limited.

[0066] The present application combines the rotor kinetic energy of the wind turbine and the rapid charging and discharging characteristics of the energy storage through strategies such as virtual inertia control and virtual droop control, and forms a complement in the frequency response model.

[0067] The root mean square error RMSE and the mean absolute error MAE are used to quantify the transient impact and steady-state deviation of frequency fluctuation, and the wind turbine utilization rate index is combined to verify the effectiveness of the frequency regulation strategy in actual operation. BRIEF DESCRIPTION OF DRAWINGS

[0068] In order to make the technical solutions of the present application clearer, the drawings needed to be used in the description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained according to these drawings without creative labor for those skilled in the art.

[0069] Figure 1 Flow chart for frequency regulation capability evaluation method of multi-dimensional wind storage combined system

[0070] Figure 2 Schematic diagram of system frequency response model

[0071] Figure 3 Maximum power point tracking curve of wind turbine

[0072] Figure 4 Schematic diagram of four-machine two-area system containing wind storage

[0073] Figure 5 Load continuous step disturbance diagram

[0074] Figure 6 System frequency response diagram

[0075] Figure 7 Schematic diagram of wind turbine output under different scenarios

[0076] Figure 8 Schematic diagram of energy storage output under different scenarios

[0077] Figure 9 Schematic diagram of energy storage frequency regulation contribution rate under different scenarios

[0078] Figure 10 Load and wind speed continuous step disturbance diagram

[0079] Figure 11 System frequency response diagram

[0080] Figure 12 Schematic diagram of wind turbine regulation reserve before frequency regulation

[0081] Figure 13 Schematic diagram of energy storage regulation reserve before frequency regulation

[0082] Figure 14 Schematic diagram of wind turbine output under different scenarios

[0083] Figure 15 Schematic diagram of energy storage output under different scenarios of frequency regulation strategy dimension

[0084] Figure 16 Schematic diagram of energy storage frequency regulation contribution rate under different scenarios

[0085] Figure 17 schematic diagram of an electronic device. DETAILED DESCRIPTION

[0086] The present application aims at multiple uncertainties in frequency modulation control of a wind storage combined system, and a comprehensive evaluation index system covering three dimensions of frequency modulation reserve-strategy-effect is constructed to realize stereoscopic and dynamic evaluation of the wind storage collaborative frequency modulation capability.

[0087] The multi-dimensional wind storage combined system frequency modulation capability evaluation method relates to quantification of dynamic coupling characteristics of wind turbine rotor kinetic energy and energy storage state of charge, proposes a reserve evaluation method based on wind storage combined adjustable margin, and accurately depicts the frequency modulation resource basis before system frequency modulation. By introducing parameters such as energy storage regulation power contribution rate, the optimization potential of the wind storage collaborative control strategy is deeply analyzed, and theoretical support is provided for control algorithm design. Combined with frequency dynamic change root mean square error, average absolute error, capacity utilization rate and other indicators, the actual efficiency of the control strategy is comprehensively measured, and the advantages and disadvantages of different strategies under complex working conditions are effectively identified.

[0088] The multi-dimensional wind storage combined system frequency modulation capability evaluation method related to the present application will be described in detail below. In order to illustrate but not to limit, specific details such as specific system structure, technology, etc. are proposed to thoroughly understand the embodiments of the present application. However, it should be clear to those skilled in the art that the present application can also be implemented in other embodiments without these specific details.

[0089] It should be understood that when used in the specification of the present application, the term "comprising" indicates the presence of described features, whole, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, whole, steps, operations, elements, components and / or sets thereof. The terms "comprise", "include", "have" and their variants mean "including but not limited to", unless otherwise specifically emphasized.

[0090] The phrase "one embodiment" or "some embodiments" or the like appearing in the present application means that the specific feature, structure or characteristic described in the embodiment is included in one or more embodiments of the present application. Therefore, the phrases "in one embodiment", "in some embodiments", "in other some embodiments", "in other some embodiments" and the like appearing in the present application do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized.

[0091] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described, obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0092] Please refer to Figure 1 The flow chart of the frequency regulation capability evaluation method of the multi-dimensional wind and storage combined system in some embodiments is shown in FIG. 1, and the method comprises the following steps:

[0093] Step S101: Obtain the randomness parameters of wind speed, the fluctuation parameters of load and the SOC limitation parameters of storage as input basis.

[0094] In some embodiments, the spatiotemporal randomness parameters of wind speed are collected, such as the probability distribution characteristics of wind speed, which covers the distribution rules of wind speed at different times and different geographical locations, such as normal distribution, Weibull distribution and other parameters, which can accurately describe the variation characteristics of wind speed.

[0095] For the fluctuation characteristic parameters of power load, the range and frequency of load mutation are obtained, and the amplitude and periodicity of load variation are determined. The state of charge limitation parameters of the storage system include the minimum value, the maximum value and the rated capacity of the SOC, which determine the working range and the maximum storable and releasable electric energy of the storage system.

[0096] Step S102: Based on the parameters obtained in step S101, a system frequency response model is constructed to describe the process of adjusting mechanical power by the governor-turbine transfer function of the traditional generator set, adjusting electromagnetic power by the rotor kinetic energy conversion and virtual inertia control of the wind turbine generator set, and adjusting charging and discharging power by the virtual droop control of the storage system under frequency deviation.

[0097] In some embodiments, a comprehensive model is constructed to integrate the adjustment characteristics of the traditional generator set, the wind turbine generator set and the storage system. For the traditional generator set part, the governor-turbine transfer function is described in detail, including its gain, time constant and other parameters, and how the unit responds to frequency changes to adjust mechanical power is determined. The virtual droop control here is to set the droop coefficient so that the charging and discharging power of the storage is proportional to the frequency deviation, simulating the frequency regulation characteristics of the traditional unit.

[0098] For the wind turbine generator set part, the related equations and parameters of rotor kinetic energy conversion, as well as the strategy and control parameters of virtual inertia control, are described to determine the adjustment process of electromagnetic power.

[0099] For the storage system part, the control principle and related coefficients of virtual droop control are determined to describe the dynamic adjustment mechanism of charging and discharging power.

[0100] It can be seen that, according to the physical characteristics and control strategies of each energy device, the power regulation process of each energy device under frequency deviation is expressed by mathematical equations and logical relationships by using the mechanism modeling method, and a model capable of overall describing the frequency response of the system is constructed, and the power output change of each energy can be simulated by inputting the frequency deviation.

[0101] Step S103: Based on the wind speed randomness parameter and the energy storage SOC limit parameter, determine the evaluation index of the frequency regulation reserve dimension.

[0102] In some embodiments, based on the wind speed uncertainty parameter, the available reserve kinetic energy of the wind turbine is calculated, considering the difference between the rotor speed safety threshold and the current rotor speed, and the difference between the maximum power tracking capability and the current output power to determine the reserve power.

[0103] For the energy storage system, the available regulation energy is dynamically calculated according to the current SOC value, the rated capacity, and the minimum and maximum limits of the SOC, and the available regulation power is determined according to the rated charge and discharge power and the SOC limit, which together constitute the evaluation content of the frequency regulation reserve dimension.

[0104] The embodiment uses the uncertainty of wind speed to calculate the potential adjustable power of the wind turbine under different conditions, and determines the actual releasable reserve in combination with the physical limitations of the device. For energy storage, the maximum energy and power support that can be provided when frequency regulation is needed are calculated according to the physical principles of energy storage and power output and safety constraints.

[0105] Step S104: Based on the power regulation characteristics of each energy in the system frequency response model, determine the evaluation index of the frequency regulation strategy dimension.

[0106] The embodiment calculates the support power provided by the wind storage system in combination, i.e., the cumulative value of the wind turbine power and the energy storage charge and discharge power, according to the power regulation characteristics of each energy in the system frequency response model under different operating conditions.

[0107] At the same time, the total charge and discharge amount of the energy storage in the entire frequency regulation process and the proportion of the total charge and discharge power amount of the wind storage combined system in the total frequency regulation amount are counted to determine the contribution rate of the energy storage in the combined frequency regulation.

[0108] The embodiment obtains the power support of the wind storage combined system and the contribution degree of the energy storage by analyzing the time sequence data of the power regulation of each energy in the model according to certain calculation methods and logic, reflecting the collaborative working effect of each energy under the current frequency regulation strategy.

[0109] Step S105: Determine an evaluation index of the frequency regulation effect dimension by calculating the deviation between the actual frequency fluctuation data and the rated frequency.

[0110] This embodiment collects actual frequency fluctuation data, calculates the deviation between the actual frequency fluctuation data and the rated frequency, and statistically analyzes the deviation data to determine the evaluation index of the frequency regulation effect dimension.

[0111] Specifically, it includes calculating the utilization rate of wind turbines, that is, the ratio of actual maximum output power to adjustable capacity; obtaining the root mean square error of frequency fluctuations to reflect the intensity of transient frequency impact; and calculating the mean absolute error to reflect the steady-state frequency offset level.

[0112] Step S106: Quantitatively analyze the frequency regulation standby dimension evaluation index, the frequency regulation strategy dimension evaluation index, and the frequency regulation effect dimension evaluation index, and output a comprehensive evaluation result of the frequency regulation capability of the wind-storage combined system.

[0113] This embodiment summarizes the evaluation indicators of the frequency regulation reserve dimension, the frequency regulation strategy dimension, and the frequency regulation effect dimension, and uses certain quantitative analysis methods, such as weighted summation, to calculate the comprehensive evaluation results of the frequency regulation capability of the wind-storage combined system based on the importance and weight of each indicator, and outputs them in a clear and easy-to-understand manner, such as generating an evaluation report or a visual chart.

[0114] By establishing a quantitative assessment model, comprehensively considering the impact of various dimensional indicators and converting the data from each indicator into a comprehensive assessment result according to the established rules and algorithms, a comprehensive and quantitative evaluation of the frequency regulation capability of the wind-storage combined system can be achieved. This provides a strong basis for power system planning, operation, and decision-making, and improves the stability and reliability of the power system.

[0115] Furthermore, as a refinement and expansion of the specific implementation method of the above-mentioned multi-dimensional wind-storage combined system frequency regulation capability evaluation method embodiment, in order to fully illustrate the specific implementation process of the multi-dimensional wind-storage combined system frequency regulation capability evaluation method, the method of the present application also includes the following steps:

[0116] Obtain wind speed randomness parameters, load fluctuation parameters and energy storage SOC limit parameters as input basis.

[0117] Specifically, we first analyze the multiple uncertainties of frequency regulation in a wind-storage combined system. Wind speed exhibits significant temporal and spatial randomness, making its variation difficult to accurately predict.

[0118] In this embodiment, according to the Weibull distribution function, the probability density function of wind speed can be expressed as:

[0119]

[0120] In the formula,v Indicates wind speed, k is the shape parameter, c This randomness causes the output power of wind turbines to fluctuate significantly, making it difficult to stably provide the expected regulated power during frequency regulation, increasing the difficulty of system frequency control.

[0121] In this example, electricity user behavior is highly uncertain, influenced by multiple factors such as time of day, weather, and economic activity. Sudden increases or decreases in load can disrupt the system's power balance and lead to significant frequency deviations. Load and frequency fluctuations are particularly pronounced in areas with concentrated industrial production or during peak commercial electricity demand periods, posing a challenge to the rapid response capabilities of the wind-storage combined system.

[0122] During frequency regulation, the regulation capacity and regulation power of the energy storage system will change with its state of charge. The regulation energy of the energy storage system based on SOC can be expressed as:

[0123]

[0124] In this formula, E res,B It is the estimated value of energy storage regulation energy; SOC is the state of charge value; SOC min is the minimum state of charge limit for energy storage; SOC max is the maximum state of charge limit of the energy storage; E B is the rated capacity of the energy storage system; η d is the discharge efficiency of the energy storage; η c is the charging efficiency of the energy storage; η is the capacity ratio of energy storage configured in the wind farm; P It is the discharge power of the energy storage system. A positive value indicates discharge, and a negative value indicates charge.

[0125] To prevent overcharging and over-discharging of the energy storage system (ESS), the charging power must be limited when the SOC continues to increase; and the discharging power must be limited when the SOC continues to decrease. The energy storage discharge regulation power based on the state of charge is expressed as:

[0126]

[0127] Where, SOC < SOC min , S SOC1 =0; SOC 1≤ SOC , SSOC1 =1; SOC min ≤ SOC < SOC 1,

[0128]

[0129] Where, P res,B1 is the energy storage discharge regulation power value; P B1 is the rated discharge power of the energy storage; S SOC1 is the discharge correction factor; SOC 1 is the critical value between the over-discharge state and the normal operation state of the energy storage; n is the energy storage adaptive adjustment coefficient.

[0130] The energy storage charging regulation power based on the state of charge is expressed as:

[0131]

[0132] Where, SOC > SOC max , S SOC2 =0; SOC ≤ SOC 2, S SOC2 =1; SOC 2< SOC ≤ SOC max ,

[0133]

[0134] Where, P res,B2 It is the energy storage charging regulation power value; P B2 is the rated charging power of the energy storage; S SOC2 is the charging correction factor; SOC 2 is the critical value between the normal working state and overcharge state of the energy storage unit, n is the energy storage adaptive adjustment coefficient.

[0135] In the method, a system frequency response model is constructed.

[0136] Specifically, when the load fluctuates, the system active power is unbalanced and the frequency changes. Various energy sources such as thermal power, hydropower, wind power and energy storage change their own output active power to participate in primary frequency regulation. The system frequency response model is as follows: Figure 2 shown.

[0137] In the frequency modulation process, the principle of the system equation set is mainly based on the dynamic characteristics of the traditional unit, the operating characteristics of the wind turbine and the control characteristics of the energy storage system, which is usually described by the following equations:

[0138]

[0139]

[0140] In the formula, H is the inertia constant, which represents the inertia response ability of the system to frequency change; p is is the wind power penetration rate; D is the damping coefficient of the system, which represents the damping effect of the system to frequency change; f is the frequency deviation, i.e. the difference between the actual frequency and the rated frequency; P m is the mechanical power change, which represents the mechanical power adjustment amount of the generator set; P e is the electrical power change; P g , Δ P B , Δ P W respectively, are the output power change amounts of the traditional generator set, the energy storage system and the wind turbine; P L is the disturbance power in the power system, including two aspects. On the one hand, the disturbance is caused by the volatility of the load, and on the other hand, the disturbance is caused by the randomness of the wind power generation.

[0141] Therefore, the system frequency characteristic model is:

[0142]

[0143] The frequency modulation response characteristics of the traditional generator set involved in the embodiment are based on the equivalent transfer function of the traditional generator set shown in FIG. 1. Figure 2 The frequency modulation control characteristics of the traditional generator set are an important guarantee for the frequency stability of the power system. The characteristic equation of the output power of the traditional generator set participating in frequency modulation is:

[0144]

[0145] In the formula, G gov s , G gen s are respectively the equivalent transfer functions of the governor and the turbine; R ​​The frequency modulation adjustment coefficient of the traditional generator set is the frequency modulation adjustment coefficient of the traditional generator set. The function of the speed regulator is to adjust the mechanical power output of the generator set according to the frequency deviation. The function of the turbine is to convert the mechanical power command output by the speed regulator into actual mechanical power output. The dynamic characteristics can be shown by the following transfer function:

[0146]

[0147]

[0148] In the formula, K g is the gain of the speed regulator, which represents the response strength of the speed regulator to the frequency deviation; T g is the time constant of the speed regulator, which represents the response speed of the speed regulator; T CH is the time constant of the main inlet chamber; T RH is the reheater time constant; F RH is the high-pressure turbine mechanical power ratio.

[0149] The frequency modulation response characteristics of the wind turbine of the embodiment are based on the rotation of the rotor of the wind turbine under the action of wind, the transmission of mechanical energy to the generator through the transmission system, and the conversion of mechanical energy to electrical energy by the generator. The maximum power tracking curve of the wind turbine is as shown in Figure 3 , wherein each line represents the power of the wind turbine under different wind speeds, and the output power P W can be calculated by the following formula:

[0150]

[0151] In the formula: k opt is the maximum power point tracking (MPPT) curve proportionality coefficient of the wind turbine; ω r is the rotor speed of the wind turbine; ω 0、 ω 1、 ω max are the minimum electrical angular velocity, constant speed zone electrical angular velocity and maximum electrical angular velocity of the wind turbine, respectively; P max is the maximum output power of the wind turbine.

[0152] When the rotor kinetic energy of the doubly-fed wind turbine is converted into electromagnetic power to respond to fluctuations in system frequency, it enables the doubly-fed wind turbine to have inertia support capability similar to synchronous generators, providing frequency modulation support. The doubly-fed wind turbine needs to be able to adjust its output electromagnetic power according to changes in the grid frequency, and the rotor releases kinetic energy and power is described by the following formula:

[0153]

[0154]

[0155] wherein, E 0 is the initial rotational speed ω 0 corresponds to the rotor kinetic energy; E r is the rotor speed after the unit participates in frequency modulation ω r corresponds to the rotor kinetic energy; J is the rotational inertia of the wind turbine; Δ P ω is the frequency modulation active support power released by the rotor kinetic energy.

[0156] In order to enable the wind turbine to participate in the transient frequency adjustment of the power grid, the active increment using differential control is added to the basis of the wind turbine. Its expression is as follows:

[0157]

[0158] wherein, K d is the virtual inertia response coefficient; d f / d t is the frequency change rate.

[0159] The wind turbine rotor kinetic energy control is suitable for using the following frequency model to simulate the inertia response model of conventional power sources:

[0160]

[0161] wherein, T ω is the rotor inertia response time constant; Δ P W is the inertia support power provided by the rotor kinetic energy control.

[0162] The energy storage frequency modulation response characteristic configuration method of the embodiment is based on the energy storage system participating in system frequency modulation through virtual droop control to reduce frequency deviation, simulating traditional synchronous generators and enhancing grid stability, which is described by the following formula:

[0163]

[0164] wherein,K b is the virtual droop coefficient, Δ f Indicates frequency deviation.

[0165] The frequency response model can be obtained as:

[0166]

[0167] Where, T b is the response time constant of the energy storage system control. s is the complex frequency variable of the Laplace transform and is used to construct a frequency-domain model of the dynamic system. Its function is to convert frequency changes and dynamic power adjustments into algebraic form, facilitating analysis of the system's amplitude-frequency and phase-frequency responses. In the inertial response model, s, combined with the time constant, collectively characterizes the inertial support capacity and dynamic response speed of the wind turbine rotor kinetic energy control.

[0168] The energy storage system in this embodiment stabilizes the frequency by directly adjusting the grid power balance through rapid charging and discharging. When the grid frequency decreases, that is, when the load increases, the energy storage system discharges, injecting active power into the grid to make up for the power shortfall. When the grid frequency increases, that is, when the load decreases, the energy storage system charges, absorbing excess grid power and suppressing the frequency increase. Because SOC is closely related to parameters such as voltage, current, and internal resistance, the charge of the energy storage battery can be described by SOC, expressed as follows:

[0169]

[0170] Where, SOC 0 is the initial SOC value of the energy storage battery; E B is the rated capacity of energy storage; P It is the current charging and discharging power of the energy storage, which is positive when discharging and negative when charging.

[0171] This embodiment configures multi-dimensional evaluation indicators based on wind power energy storage coordinated frequency regulation.

[0172] Specifically, the frequency regulation capability of a combined wind and energy storage system is affected by multiple factors, including wind speed fluctuations and the state of the energy storage. Traditional single indicators are insufficient to fully assess its dynamic response characteristics. To address this issue, this paper constructs a comprehensive evaluation system based on three dimensions: frequency regulation reserve, strategy, and effectiveness. This system quantitatively analyzes the coordinated frequency regulation capabilities of wind turbines and energy storage, providing data support for optimizing control strategies.

[0173] For the frequency regulation reserve dimension indicator, when evaluating the frequency regulation capability of a high-proportion renewable energy power system, it is necessary to dynamically model the physical reserve resources of wind and storage coordinated frequency regulation. The frequency regulation reserve dimension measures the system's ability to regulate before a disturbance occurs, including:

[0174] Wind turbine standby kinetic energy / power (Δ E k and Δ P ω ): It characterizes the rotational kinetic energy margin that can be released by the wind turbine rotor. Its value depends on the difference between the rotor speed and the safety threshold, indicating the reserve kinetic energy and power of the wind turbine used to participate in frequency regulation.

[0175] Energy storage backup energy / power ( E res,B and P res,B Energy / power regulation margin dynamically calculated based on the state-of-charge (SOC) safety domain. This dimension dynamically assesses the energy storage's regulation margin by integrating SOC and charge / discharge power limits. This dimension reflects the system's inherent ability to cope with frequency disturbances and is a fundamental guarantee for frequency regulation control.

[0176] Regarding the frequency regulation strategy dimension, the frequency regulation strategy dimension evaluates the effect of the control algorithm on the coordinated allocation of wind power and energy storage resources, covering:

[0177] Support power of wind-storage combined system (Δ P W and Δ P B ): It represents the increased active output power of wind turbines in response to system frequency deviations, as well as the real-time charging / discharging power of energy storage used to compensate for power shortages caused by frequency fluctuations.

[0178] Energy storage frequency regulation contribution rate ( C 1 and C 2): The proportion of energy storage output in the total frequency regulation output of the wind-storage combined system during frequency regulation. This includes the total charge / discharge of energy storage ( E sup ) and total charge / discharge power ( P sup ). The contribution rate calculation formula is: C 1= E sup / E total ×100%, C 2= P sup / P total ×100%, where C 1 and C 2 is the contribution rate of energy storage; E total is the total energy change of the wind-storage combined system; P totalis the total power variation of the wind storage combined system. This dimension reveals the rationality of resource scheduling under different control strategies and guides parameter optimization.

[0179] For the frequency regulation effect dimension index of the embodiment, the frequency regulation effect dimension quantifies the actual dynamic response performance of the system, including: defining the wind turbine utilization rate μ ; in the frequency regulation process, the ratio of the actual maximum power output of the wind turbine to the average adjustable output power; the wind turbine power utilization rate calculation formula is, μ= max{Δ P W} / Δ P ω ; μ= Δ E W / Δ E k 。

[0180] Root mean square error (RMSE) of frequency fluctuation: evaluate the suppression effect of frequency fluctuation, represent the dispersion degree of frequency deviation in the statistical period, the larger the value, the more intense the system frequency fluctuation amplitude. RMSE amplifies the weight of larger deviation through squaring operation, has higher sensitivity to extreme frequency events (such as sudden rise / sudden drop), directly reflects the stability margin of the system resisting large disturbance impact. It is used to capture the transient frequency impact intensity caused by power mutation in high wind speed fluctuation scenarios, and its value below the threshold is a necessary condition to ensure system safety.

[0181] The calculation formula is as follows:

[0182]

[0183] Among them, f i is the current actual system frequency; f N is the rated system frequency, N is the number of sampling points in the frequency fluctuation process.

[0184] Mean absolute error (MAE) of frequency fluctuation: reflects the average level of absolute frequency deviation in the statistical period, the larger the value, the more significant the overall frequency deviation of the system.

[0185] MAE gives linear weight to all deviations, more directly describes the cumulative impact of continuous small amplitude frequency fluctuation, and is the core index for evaluating the steady state accuracy of frequency modulation control. Then it is used to evaluate the steady state regulation accuracy of frequency modulation resources in load gradual change scenarios, the smaller the value, the better the tracking ability of wind storage collaborative control to frequency reference point. It is calculated by the following formula:

[0186] .

[0187] It can be seen that by comparing the ratio of the actual maximum power output of the fan to the adjustable capacity, the degree of mining the potential of the fan in the frequency regulation process is measured. Reflecting the depth of wind turbine participation under frequency disturbance, the higher the utilization rate, the greater the contribution of the fan to the system frequency support through virtual inertia control, kinetic energy release, etc. Provide a basis for wind turbine control strategy optimization, avoid insufficient utilization due to excessive reserve of kinetic energy, or secondary frequency drop and equipment safety risk caused by excessive regulation.

[0188] This embodiment amplifies the weight of high-frequency large deviation through square operation, and describes the fluctuation amplitude of extreme events such as frequency sudden rise / sudden drop. Quantitative evaluation of transient stability of system load mutation and fan off-grid, the lower the RMSE value, the smaller the frequency fluctuation of the system in the transient process, the higher the safety; It can be used as a fast verification index for wind storage combined frequency regulation strategy, such as virtual droop control parameter optimization, and the RMSE reduction directly reflects the improvement effect of transient response.

[0189] For the frequency fluctuation average absolute error (MAE), the absolute value of all frequency deviations is averaged to eliminate the influence of positive and negative deviations canceling out, focusing on the overall level of long-term frequency deviation. Reflecting the steady-state tracking ability of the wind storage combined system under load gradual change, wind speed gradual change and other scenarios, the smaller the MAE value, the closer the system frequency to the rated value, the higher the power supply quality; Provide a basis for the frequency regulation task allocation of traditional units and wind storage systems, such as when MAE is high, optimize the virtual droop coefficient of energy storage or increase the power support ratio of wind turbines. Help identify the frequency regulation capability degradation problem of the wind storage system in long-term operation (such as frequent fluctuations in the SOC of energy storage, which leads to a decrease in available capacity, and then gradually increases the MAE, providing an auxiliary index for system economic evaluation.

[0190] In order to verify that the multi-dimensional wind storage combined system frequency regulation capability evaluation method involved in the present application can significantly improve the scientificity of frequency regulation strategy evaluation, and provide quantifiable and verifiable decision basis for the optimization design of wind storage combined system frequency regulation control scheme. The specific verification steps are as follows.

[0191] A four-machine two-area frequency response model containing a wind storage combined system is developed in MATLAB / Simulink, such as Figure 4The rated frequency of the grid is set to 50 Hz. The test system includes three synchronous generators (SG1, SG2 and SG4) representing conventional thermal and hydro units, each with a rated power of 200 MW. The wind farm consists of 100 aggregated 2 MW wind turbines, modeled as individual units, with a total installed capacity of 200 MW. The energy storage units are configured in a 25-module parallel architecture, with a single module rated capacity of 1 MWh / 0.5 MW, aggregated to form a cluster system with a total rated capacity of 25 MWh and a total output power of 12.5 MW. The energy storage scale is equivalent to 12.5% of the rated installed capacity of the wind farm (wind-storage capacity ratio 1:0.125), serving a regional grid with a wind power penetration of about 25%. The rated wind speed is 12 m / s.

[0192] This embodiment evaluates the frequency regulation control strategy under load disturbance. Specifically, when the wind speed is 12 m / s and the simulation time is 24 seconds, a 0.02 p.u. step load disturbance occurs at 1 second, followed by a 0.03 p.u. step disturbance at 3 seconds, and a 0.05 p.u. step disturbance at 5 seconds, as shown in Figure 5 .

[0193] This embodiment defines scenario 1 as only traditional generators participating in frequency regulation. Scenario 2 is only wind turbines participating in frequency regulation. Scenario 3 is the wind-storage joint system participating in frequency regulation. Scenario 4 is the wind-storage joint system participating in frequency regulation based on model predictive control (MPC). The state of charge of the energy storage system is set to 0.8 at the beginning of the simulation. The capacity ratio of the wind farm with energy storage is 0.5, and the charge / discharge efficiency of the energy storage is 0.9. When the system experiences the above disturbances, the frequency dynamic characteristics under the four frequency regulation control scenarios are as shown in Figure 6 , and the regulation performance under these scenarios is comprehensively evaluated in multiple dimensions in Table 1.

[0194] Table 1: Multi-dimensional comprehensive evaluation index

[0195]

[0196] When the system experiences step load fluctuations, the frequency dynamic characteristics of the system under different frequency regulation strategies are different. Before frequency regulation, wind turbines store kinetic energy in their rotors, while energy storage systems exhibit adjustable power and fast charge / discharge capabilities according to their state of charge, ensuring a clear and controllable frequency regulation margin.

[0197] In the dynamic response process, Table 1 and Figure 7 (Δ P W ), Figure 8 (Δ P B ) andFigure 9 C 1 and C 2) reveals that although Short-term inertia support can be provided by releasing rotor kinetic energy, its reserve capacity is constrained by the blade mass and rotational speed limit. This results in limited energy release in each frequency regulation event and requires a rotor speed recovery margin to be reserved.

[0198] In scenario 2, repeated load steps can force wind turbines to disengage from frequency regulation due to speed recovery requirements, resulting in power gaps and secondary frequency drops.

[0199] In contrast, energy storage systems (ESS) dominate power compensation during medium and long-term frequency disturbances due to their large energy storage capacity and flexible power regulation capability, effectively suppressing steady-state frequency deviation.

[0200] In scenario 3, coordinated wind-ESS joint system frequency regulation compensates for power gaps when wind turbines disengage, achieves time complementarity, and enhances system frequency stability.

[0201] Scenario 4 integrates model predictive control to optimize power allocation between wind turbines and ESS through multi-time scale prediction. This method improves the power utilization rate of wind turbines and prevents secondary frequency drops by utilizing ESS in the later stages of regulation.

[0202] At the same time, it reduces the frequency root mean square error to 0.0681 and the frequency average absolute error to 0.0640, as shown in FRMSE and FMAE in Table 1.

[0203] This embodiment also evaluates the frequency regulation control strategy under step load wind speed disturbance. Specifically, when the simulation time is 24 seconds, a step load disturbance of 0.06 p.u. occurs at 4 seconds, followed by a step disturbance of -0.02 p.u. at 6 seconds, a step disturbance of 0.05 p.u. at 7 seconds, and a step disturbance of 0.02 p.u. at 8 seconds. The initial wind speed of the wind turbine is 8.5 m / s, which decreases to 7.5 m / s at 4 seconds, increases to 10 m / s at 6 seconds, decreases to 9.5 m / s at 7 seconds, and decreases to 8.5 m / s at 8 seconds, as shown in Figure 10 .

[0204] The system frequency response curve is shown in Figure 11 . The initial state of charge of the energy storage system is set to 0.8. The capacity proportion of the energy storage in the wind farm is 0.5, and the charge and discharge efficiency of the energy storage is 0.9.

[0205] Table 2: Multi-dimensional comprehensive evaluation index

[0206] ​

[0207] Figure 11 The significant differences in frequency dynamic characteristics under the four scenarios are demonstrated. Table 2 comprehensively evaluates the regulation performance under these scenarios. The frequency regulation reserve dimension indicators in Table 2, combined with the visualization results in Figure 12 and Figure 13 , show that the inertia support potential of the kinetic energy stored in the wind turbine rotor is affected by wind speed and rotational speed.

[0208] Under high wind speed conditions, the rotational speed of the wind turbine rotor increases, thereby storing more kinetic energy. However, this energy reserve is still limited by mechanical structure and operational safety thresholds. The regulation capacity of the energy storage system changes dynamically with the state of charge, and its available energy and power reserve exhibit nonlinear variation characteristics during frequency regulation. The frequency regulation strategy dimension indicators and Figure 14 and Figure 15 show that scenario 1, which relies solely on traditional synchronous generators, is limited by limited reserve capacity.

[0209] Due to insufficient support power, the root mean square error (RMSE) is 0.147, and the mean absolute error (MAE) is 0.109 HZ, making it difficult to meet the frequency regulation requirements. In scenario 2, although the kinetic energy of the wind turbine can be quickly released, the limited reserve capacity leads to poor persistence, causing secondary frequency fluctuations and low utilization efficiency. The total kinetic energy stored in the rotor is still much smaller than the energy storage, so the wind turbine alone cannot meet the system's frequency regulation needs, and the frequency regulation strategy of the wind turbine needs to be optimized. Based on its high reserve energy / power, the energy storage system provides a flexible regulation basis for scenarios 3 and 4.

[0210] Figure 16 show that in scenarios 3 and 4, the wind turbine and energy storage system cooperatively provide short-term frequency support and medium and long-term power compensation, and the frequency regulation contribution rate of the energy storage system exceeds 80%. At the same time, the frequency regulation effect indicators in Table 2 show that scenarios 1 and 2 have slow recovery speed and large steady-state deviation, while scenarios 3 and 4 effectively maintain frequency stability through continuous regulation. Scenario 4, based on model predictive control (MPC), optimizes the power distribution of the wind- energy storage system and achieves efficient coordination of frequency regulation resources. It consumes more energy storage energy to make up for the power gap during the rotor speed recovery process. It reduces the root mean square error of frequency fluctuations to 0.0782 and the mean absolute error of frequency to 0.0673 HZ, verifying that this strategy has significant advantages in enhancing system frequency dynamic characteristics.

[0211] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0212] The following is an embodiment of the multi-dimensional wind-storage combined system frequency regulation capability evaluation system provided by the embodiments of the present disclosure. This system and the multi-dimensional wind-storage combined system frequency regulation capability evaluation method of the above-mentioned embodiments belong to the same inventive concept. For details not fully described in the embodiments of the multi-dimensional wind-storage combined system frequency regulation capability evaluation system, please refer to the embodiments of the above-mentioned multi-dimensional wind-storage combined system frequency regulation capability evaluation method.

[0213] The system includes:

[0214] The parameter acquisition module is used to obtain wind speed randomness parameters, load fluctuation parameters and energy storage SOC limit parameters as input basis;

[0215] The frequency response construction module is used to obtain parameters and construct a system frequency response model to describe the process of traditional generators regulating mechanical power through the governor-turbine transfer function under frequency deviation, wind turbines regulating electromagnetic power through rotor kinetic energy conversion and virtual inertia control, and energy storage systems regulating charging and discharging power through virtual droop control;

[0216] The backup index evaluation module determines the evaluation index of the frequency regulation backup dimension based on the wind speed randomness parameter and the energy storage SOC limit parameter;

[0217] The strategy indicator evaluation module determines the evaluation indicators of the frequency regulation strategy dimension based on the power regulation characteristics of each energy source in the system frequency response model;

[0218] The effect index determination module determines the evaluation index of the frequency regulation effect dimension through the deviation statistics of the actual frequency fluctuation data and the rated frequency;

[0219] The comprehensive evaluation module is used to quantitatively analyze the frequency regulation reserve dimension evaluation indicators, frequency regulation strategy dimension evaluation indicators and frequency regulation effect dimension evaluation indicators, and output the comprehensive evaluation results of the frequency regulation capability of the wind-storage combined system.

[0220] like Figure 17 As shown, the present application also provides an electronic device, including a display module 103, a memory 102, a processor 101, and a computer program stored in the memory and executable on the processor 101. When the processor 101 executes the program, the steps of the method for evaluating the frequency regulation capability of a multi-dimensional wind-storage combined system are implemented.

[0221] In embodiments of the application, electronic devices include, but are not limited to, laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. Electronic devices can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components, their connections, and relationships, and their functions, as described herein, are meant to be examples only, and are not intended to limit implementations of the present application described and / or claimed in this document.

[0222] In embodiments of the application, the processor 101 can be implemented by using at least one of application specific integrated circuits, programmable logic devices, field programmable gate arrays, processors, controllers, micro-controllers, microprocessors, electronic devices, which are designed to perform the functions described herein, and in some cases, such an implementation can be implemented in a controller. For software implementation, the embodiments of such processes or functions can be implemented by separate software modules, such as procedures, functions, and the like, which perform one or more functions or operations. Software codes can be implemented by a software application (or program) written in any suitable programming language to be executed by the controller, which can be stored in the memory.

[0223] The display module 103 is configured to display information input by a user or information provided to the user. The display module 103 can include a display panel, which can be configured in the form of a liquid crystal display, an organic light emitting diode, or the like.

[0224] The memory 102 can be used to store software programs as well as various data. The memory 102 can include a high-speed random access memory, and can further include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state memory devices.

[0225] The present application also provides a storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the steps of the multi-dimensional wind storage joint system frequency regulation capability evaluation method.

[0226] The storage medium can employ any combination of one or more of a readable medium. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium may, for example, be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the above. More specific examples (a non-exhaustive list) of the readable storage medium include an electrical connection having one or more wires, a portable disc, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0227] In the context of storage media, a readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0228] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A multi-dimensional wind-storage combined system frequency regulation capability evaluation method, characterized by: Methods include: Step S101: obtaining a wind speed randomness parameter, a load fluctuation parameter, and an energy storage SOC limit parameter as input basis; The randomness parameter of wind speed is based on the Weibull distribution function, and the probability density function of wind speed is expressed as: Where, v Indicates wind speed, k is the shape parameter, c is the scale parameter; The energy storage SOC limit parameter is expressed as: Where, E res,B It is the estimated value of energy storage regulation energy; SOC is the state of charge value; SOC min is the minimum state of charge limit for energy storage; SOC max is the maximum state of charge limit of the energy storage; E B is the rated capacity of the energy storage system; η d is the discharge efficiency of the energy storage; η c is the charging efficiency of the energy storage; η is the capacity ratio of energy storage configured in the wind farm; P is the discharge power of the energy storage system; The energy storage discharge regulation power based on the state of charge is expressed as: Where, SOC < SOC min , S SOC1 =0; SOC 1≤ SOC , S SOC1 =1; SOC min ≤ SOC < SOC 1; P res,B1 is the energy storage discharge regulation power value; P B1 is the rated discharge power of the energy storage; S SOC1 is the discharge correction factor; SOC 1 is the critical value between the over-discharge state and the normal operation state of the energy storage; n is the energy storage adaptive regulation coefficient; The energy storage charging regulation power based on the state of charge is expressed as: Where, SOC>SOC max , S SOC2 =0; SOC ≤ SOC 2, S SOC2 =1; SOC 2< SOC ≤ SOC max , P res,B2 It is the energy storage charging regulation power value; P B2 is the rated charging power of the energy storage; S SOC2 is the charging correction factor; SOC 2 is the critical value between the normal working state and overcharge state of the energy storage unit, n is the energy storage adaptive regulation coefficient; Step S102: Based on the parameters obtained in step S101, a system frequency response model is constructed to describe the process in which the conventional generator set regulates mechanical power through the governor-turbine transfer function, the wind turbine set regulates electromagnetic power through rotor kinetic energy conversion and virtual inertia control, and the energy storage system regulates charge and discharge power through virtual droop control under frequency deviation. Step S103: determining an evaluation index of a frequency regulation standby dimension based on a wind speed randomness parameter and an energy storage SOC limit parameter; Based on the wind speed uncertainty parameter, the reserve kinetic energy that can be released by the wind turbine is calculated. The reserve power is determined by considering the difference between the rotor speed safety threshold and the current speed, as well as the difference between the maximum power tracking capability and the current output power. For energy storage systems, the available regulating energy is dynamically calculated based on the current SOC value, rated capacity, and minimum and maximum SOC limits. The available regulating power is also determined based on the rated charge and discharge power and SOC limits. These indicators together constitute the evaluation content of the frequency regulation reserve dimension. Step S104: determining an evaluation index of a frequency regulation strategy dimension based on the power regulation characteristics of each energy source in the system frequency response model; Based on the power regulation characteristics of each energy source in the system frequency response model under different operating conditions, the support power provided by the wind and energy storage system is calculated, that is, the cumulative value of the additional power generated by the wind turbine and the charging and discharging power of the energy storage system; At the same time, the total charge and discharge amount of energy storage during the entire frequency regulation process, as well as the proportion of total charge and discharge power in the total frequency regulation amount of the wind-storage combined system, are counted to determine the contribution rate of energy storage to the combined frequency regulation. Step S105: Determine an evaluation index of the frequency regulation effect dimension by calculating the deviation between the actual frequency fluctuation data and the rated frequency; Step S106: Quantitatively analyze the frequency regulation standby dimension evaluation index, the frequency regulation strategy dimension evaluation index, and the frequency regulation effect dimension evaluation index, and output a comprehensive evaluation result of the frequency regulation capability of the wind-storage combined system.

2. The multi-dimensional wind-storage combined system frequency regulation capability evaluation method according to claim 1 is characterized in that: The system frequency response model of step S102 is expressed as: Where, T b is the response time constant of the energy storage system control, s is the complex frequency variable of the Laplace transform, K b is the virtual droop coefficient.

3. The multi-dimensional wind-storage combined system frequency regulation capability evaluation method according to claim 1 is characterized in that: Step S103 further includes: Configure the wind turbine's reserve kinetic energy / power, which represents the rotational kinetic energy margin that can be released by the wind turbine's rotor. Its value depends on the difference between the rotor speed and the safety threshold, indicating the wind turbine's reserve kinetic energy and power for participating in frequency regulation. Configure the energy storage backup energy / power, which is expressed as the energy / power regulation margin calculated for the state of charge safety domain.

4. The multi-dimensional wind-storage combined system frequency regulation capability evaluation method according to claim 1 is characterized in that: Step S104 also configures a frequency regulation strategy dimension evaluation control algorithm to coordinate and allocate wind power and energy storage resources. The specific methods include: Define the support power of the wind-storage combined system, which represents the increased active output power of wind turbines in response to system frequency deviations, and the real-time charging / discharging power of energy storage to compensate for power shortages caused by frequency fluctuations; Define the energy storage frequency regulation contribution rate, including the total charge / discharge capacity of the energy storage E sup and total charge / discharge power P sup ; The contribution rate calculation formula is: C 1= E sup / E total ×100%, C 2= P sup / P total ×100% in, C 1 and C 2 is the contribution rate of energy storage; E total is the total energy change of the wind-storage combined system; P total is the total power change of the wind-storage combined system.

5. The multi-dimensional wind-storage combined system frequency regulation capability evaluation method according to claim 1 is characterized in that: In step S105, the evaluation indicators of the frequency regulation effect dimension include: Defining wind turbine utilization μ During the frequency regulation process, the ratio of the rotor kinetic energy actually released by the wind turbine to the maximum rotor kinetic energy reserve that can be called upon is: μ 1 = Δ E W / Δ E k； During the frequency regulation process, the ratio of the actual maximum power output of the wind turbine to the average adjustable output power; the power utilization rate of the wind turbine is calculated as follows: μ 2 = max{Δ P W } / Δ P ω ; The frequency fluctuation root mean square error is defined to characterize the discrete degree of frequency deviation within the statistical period. The calculation formula is as follows: in, f i is the current actual system frequency; f N is the rated system frequency, N is the number of sampling points during the frequency fluctuation process; Definition of the mean absolute error (MAE) of frequency fluctuation: It reflects the average level of absolute frequency deviation within the statistical period and is calculated using the following formula: 。 6. A multi-dimensional wind-storage combined system frequency regulation capability evaluation system, characterized by: The system is used to implement the multi-dimensional wind-storage combined system frequency regulation capability evaluation method according to any one of claims 1 to 5; The system includes: The parameter acquisition module is used to obtain wind speed randomness parameters, load fluctuation parameters and energy storage SOC limit parameters as input basis; The frequency response construction module is used to obtain parameters and construct a system frequency response model to describe the process of traditional generators regulating mechanical power through the governor-turbine transfer function under frequency deviation, wind turbines regulating electromagnetic power through rotor kinetic energy conversion and virtual inertia control, and energy storage systems regulating charging and discharging power through virtual droop control; The backup index evaluation module determines the evaluation index of the frequency regulation backup dimension based on the wind speed randomness parameter and the energy storage SOC limit parameter; The strategy indicator evaluation module determines the evaluation indicators of the frequency regulation strategy dimension based on the power regulation characteristics of each energy source in the system frequency response model; The effect index determination module determines the evaluation index of the frequency regulation effect dimension through the deviation statistics of the actual frequency fluctuation data and the rated frequency; The comprehensive evaluation module is used to quantitatively analyze the frequency regulation reserve dimension evaluation indicators, frequency regulation strategy dimension evaluation indicators and frequency regulation effect dimension evaluation indicators, and output the comprehensive evaluation results of the frequency regulation capability of the wind-storage combined system.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method for evaluating the frequency regulation capability of a multi-dimensional wind-storage combined system as described in any one of claims 1 to 5 are implemented.

8. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for evaluating the frequency regulation capability of a multi-dimensional wind-storage combined system as described in any one of claims 1 to 5 are implemented.

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