Method, system and equipment for evaluating frequency modulation capability of multi-dimensional wind storage combined system, and medium

Abstract

The invention provides a multi-dimensional wind storage combined system frequency modulation capability evaluation method, system and device and a medium, and belongs to the technical field of power system operation and control, and the method comprises the steps: obtaining a wind speed randomness parameter, a load fluctuation parameter and an energy storage SOC limit parameter, and taking the parameters as an input basis; constructing a system frequency response model; based on the wind speed randomness parameter and the energy storage SOC limit parameter, determining an evaluation index of the frequency regulation standby dimension; determining an evaluation index of a frequency regulation strategy dimension based on the power regulation characteristics of each energy in the system frequency response model; determining an evaluation index of a frequency regulation effect dimension through deviation statistics of actual frequency fluctuation data and rated frequency; and performing quantitative analysis on the evaluation indexes, and outputting a comprehensive evaluation result of the frequency modulation capability of the wind storage combined system.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system operation and control, and specifically relates to a method, system, equipment and medium for evaluating the frequency regulation capability of a multi-dimensional wind-storage combined system. Background Art

[0002] As wind power penetration in power systems continues to increase, its randomness and volatility pose significant challenges to power system frequency regulation. During wind turbine operation, wind power output fluctuates significantly with wind speed and is difficult to accurately predict, making it difficult to quickly and effectively respond to system frequency changes and providing stable and reliable frequency regulation support. Energy storage systems offer rapid charging and discharging, as well as bidirectional regulation. Combining wind turbines with energy storage to form a wind-storage combined system is an effective way to address frequency regulation issues in systems with high wind power penetration. However, how to scientifically and accurately evaluate the frequency regulation capabilities of this combined system remains a critical issue that needs to be addressed.

[0003] Traditional power system frequency regulation capability assessment methods are mostly targeted at conventional energy sources like thermal and hydropower, which have stable and controllable generation characteristics. These assessment indicators and systems cannot be directly applied to wind-storage systems. Unlike synchronous generators, wind-storage systems experience complex wind speed variations and dynamic energy storage states, influenced by factors such as wind resources and their own operating conditions, making accurate quantitative estimation difficult.

[0004] The existing wind-storage combined frequency regulation evaluation system fails to consider multiple uncertainties. Based on deterministic scenarios, it is difficult to reflect the true performance of the control strategy in complex operating environments. The indicators cannot accurately evaluate the frequency regulation contribution rate of the wind-storage combined system under different wind speed conditions. There is also a lack of evaluation methods for the dynamic coordination effect of wind turbines and energy storage during the frequency regulation process.

[0005] The relevant methods fail to fully integrate the cross-influence of multi-dimensional variables such as wind speed fluctuations, energy storage charge state, and equipment operating parameters on frequency regulation capabilities, resulting in deviations between the evaluation model and the actual system characteristics, making it difficult to fully characterize the system's true frequency regulation potential.

[0006] The wind-storage combined system shows significant differences in frequency regulation effects under different wind speed ranges, energy storage charging and discharging stages, and grid load scenarios. However, related methods are mostly based on static models or fixed operating condition assumptions, which makes it difficult to capture the dynamic frequency regulation performance of the system under complex and changeable operating conditions.

[0007] In summary, the existing methods for evaluating the frequency regulation capability of wind-storage combined systems have many limitations and cannot meet the current power system's demand for accurate and comprehensive evaluation of the frequency regulation capability of wind-storage combined systems. Summary of the Invention

[0008] The present invention provides a multi-dimensional frequency regulation capability assessment method for a combined wind and storage system. The method integrates multi-factor coupling analysis with multi-dimensional and multi-indicator frequency regulation capabilities, constructs a precise assessment system covering all operating conditions and multiple performance dimensions, provides a scientific basis for the optimal configuration of frequency regulation resources of the combined wind and storage system, and comprehensively quantifies the frequency regulation capability of the combined wind and storage system from the front, middle and back of frequency regulation.

[0009] Methods include: Step S101: obtaining a wind speed randomness parameter, a load fluctuation parameter, and an energy storage SOC limit parameter as input basis; 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; 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; 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.

[0010] It should be further explained that, in step S101, the wind speed randomness parameter is based on the Weibull distribution function, and the probability density function of the wind speed is expressed as:

[0011] Where, v Indicates wind speed, k is the shape parameter, c is the scale parameter; The energy storage SOC limit parameter is expressed as:

[0012] 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; EB 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.

[0013] It should be further explained that in step S101, the energy storage discharge adjustment power based on the state of charge is expressed as:

[0014]

[0015]

[0016] 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:

[0017]

[0018]

[0019] Where, SOC>SOC max , S SOC2 =0; SOC ≤ SOC 2, S SOC2 =1; SOC 2< SOC ≤ SOC max , 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.

[0020] It should be further explained that the system frequency response model of step S102 is expressed as:

[0021] 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.

[0022] It should be further explained that step S103 also includes: the frequency adjustment standby dimension measures the adjustable capability of the system before the interference occurs; 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.

[0023] It should be further noted that step S104 also includes configuring a frequency regulation strategy dimension evaluation control algorithm to coordinate the allocation of wind power and energy storage resources; Specifically 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.

[0024] It should be further explained 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:

[0025] 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: .

[0026] This application also provides a multi-dimensional wind-storage combined system frequency regulation capability evaluation system, the system comprising: 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.

[0027] According to another embodiment of the present 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 method for evaluating the frequency regulation capability of a multi-dimensional wind-storage combined system when executing the program.

[0028] According to another embodiment of the present application, a storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the multi-dimensional wind-storage combined system frequency regulation capability evaluation method are implemented.

[0029] It can be seen from the above technical solutions that the present invention has the following advantages: The multi-dimensional frequency regulation capability assessment method for a combined wind and energy storage system, proposed in this paper, quantifies wind speed randomness, load fluctuations, and energy storage SOC limitations. It constructs a frequency response model encompassing traditional turbines, wind turbines, and energy storage, dynamically describing the regulation of mechanical power, electromagnetic power, and energy storage power during the frequency regulation process. From a reserve perspective, this method quantifies the system's potential to cope with sudden frequency fluctuations using indicators such as wind turbine reserve kinetic energy and energy storage available regulation energy.

[0030] The strategic dimension of this invention uses the combined support power and energy storage contribution rate to evaluate the rationality of the wind-storage coordinated frequency regulation strategy. From the effectiveness dimension, this invention uses indicators such as wind turbine utilization and frequency fluctuation error to directly measure the actual performance of frequency regulation control.

[0031] The present invention quantifies wind speed randomness and energy storage SOC operating status by combining random parameters such as wind turbine wind speed, rotor speed, and energy storage state of charge with wind turbine rotor speed safety thresholds and minimum and maximum energy storage SOC values, enabling evaluation indicators to reflect actual operational constraints. When the energy storage SOC approaches its upper limit, available charging power is automatically limited; when the energy storage SOC approaches its lower limit, available discharge power is automatically limited. This evaluation indicator reflects the impact of these constraints on frequency regulation capability in real time, avoiding a disconnect between theoretical evaluation and actual operation.

[0032] This invention combines the wind turbine's rotor kinetic energy with the rapid charge and discharge characteristics of energy storage through strategies such as virtual inertia control and virtual droop control, creating a complementary effect within the frequency response model. For example, when the system frequency suddenly drops, the wind turbine rapidly releases kinetic energy through virtual inertia, while the energy storage provides power support through droop control. The combined support power and energy storage contribution rate can be used to quantify the effectiveness of this synergistic strategy in suppressing frequency fluctuations.

[0033] The root mean square error (RMSE) and mean absolute error (MAE) are used to quantify the transient impact and steady-state deviation of frequency fluctuations. Combined with the wind turbine utilization index, the effectiveness of the frequency regulation strategy in actual operation is verified. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for the description. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0035] Figure 1 This is a flow chart of the frequency regulation capability assessment method for a multi-dimensional wind-storage combined system; Figure 2 It is a schematic diagram of the system frequency response model; Figure 3 It is the maximum power point tracking curve of wind turbine; Figure 4 This is a schematic diagram of a four-turbine, two-area system with wind and storage; Figure 5 is the load continuous step disturbance diagram; Figure 6 is the system frequency response diagram; Figure 7 Schematic diagram of wind turbine output in different scenarios; Figure 8 Schematic diagram of energy storage output in different scenarios; Figure 9 Schematic diagram of energy storage frequency regulation contribution rate in different scenarios; Figure 10is the disturbance diagram for continuous steps of load and wind speed; Figure 11 is the system frequency response diagram; Figure 12 This is a schematic diagram of the wind turbine regulation reserve before frequency regulation; Figure 13 This is a schematic diagram of energy storage regulation reserve before frequency regulation; Figure 14 Schematic diagram of wind turbine output in different scenarios; Figure 15 This is a schematic diagram of energy storage output under different scenarios in the frequency regulation strategy dimension; Figure 16 Schematic diagram of energy storage frequency regulation contribution rate in different scenarios; Figure 17 Schematic diagram of an electronic device. DETAILED DESCRIPTION

[0036] Aiming at the multiple uncertainty problems in the frequency regulation control of the wind-storage combined system, the present invention constructs a comprehensive evaluation index system covering the three dimensions of frequency regulation reserve, strategy and effect, and realizes a three-dimensional and dynamic evaluation of the wind-storage collaborative frequency regulation capability.

[0037] The multi-dimensional wind-storage combined system frequency regulation capability assessment method involved in this invention quantifies the dynamic coupling characteristics of the wind turbine rotor kinetic energy and the energy storage charge state, and proposes a reserve assessment method based on the wind-storage combined adjustable margin to accurately characterize the frequency regulation resource foundation before the system frequency regulation. By introducing parameters such as the energy storage regulation power contribution rate, the optimization potential of the wind-storage coordinated regulation strategy is deeply analyzed, providing theoretical support for the design of control algorithms. Combined with indicators such as the root mean square error of frequency dynamic changes, the mean absolute error, and capacity utilization rate, the actual effectiveness of the control strategy is comprehensively measured, and the advantages and disadvantages of different strategies under complex working conditions are effectively identified.

[0038] The following describes in detail the multi-dimensional wind-storage system frequency regulation capability assessment method involved in this application. Specific details, such as specific system structures and technologies, are provided for illustrative purposes, not for limitation, to facilitate a thorough understanding of the embodiments of this application. However, those skilled in the art will appreciate that this application may also be implemented in other embodiments without these specific details.

[0039] It should be understood that when used in this specification, the term "comprising" indicates the presence of the described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or their collections. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0040] The phrases "one embodiment" or "some embodiments" described in this application mean that the specific features, structures, or characteristics described in the embodiment are included in one or more embodiments of the application. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in other embodiments," etc. that appear in different places in this application do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized.

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0042] See also Figure 1 FIG2 is a flow chart of a method for evaluating the frequency regulation capability of a multi-dimensional wind-storage combined system in a specific embodiment, the method comprising: Step S101: Obtain wind speed randomness parameters, load fluctuation parameters, and energy storage SOC limit parameters as input basis.

[0043] In some embodiments, spatiotemporal randomness parameters of wind speed are collected, such as the probability distribution characteristics of wind speed, which covers the distribution pattern of wind speed at different times and geographical locations. Parameters such as normal distribution and Weibull distribution can accurately describe the changing characteristics of wind speed.

[0044] For load fluctuation parameters, it's important to understand the range and frequency of sudden load changes, as well as the magnitude and periodicity of load fluctuations. The energy storage system's state-of-charge (SOC) limiting parameters include the minimum and maximum SOC values and rated capacity. These parameters determine the system's operating range and the maximum amount of energy that can be stored and released.

[0045] Step S102: Based on the parameters obtained in step S101, a system frequency response model is constructed to describe the process in which the traditional generator set regulates mechanical power through the governor-turbine transfer function under frequency deviation, the wind turbine set regulates electromagnetic power through rotor kinetic energy conversion and virtual inertia control, and the energy storage system regulates charging and discharging power through virtual droop control.

[0046] In some embodiments, a comprehensive model is constructed that incorporates the regulation characteristics of traditional generator sets, wind turbines, and energy storage systems. For traditional generator sets, the governor-turbine transfer function is described in detail, including parameters such as gain and time constant, to clarify how the generator adjusts mechanical power in response to frequency changes. Virtual droop control is implemented here by setting a droop coefficient so that the energy storage charge and discharge power is proportional to the frequency deviation, simulating the frequency regulation characteristics of traditional generator sets.

[0047] In the wind turbine part, the relevant equations and parameters of rotor kinetic energy conversion, as well as the strategy and control parameters of virtual inertia control, are explained to determine the regulation process of its electromagnetic power.

[0048] In the energy storage system part, the control principle and correlation coefficient of virtual droop control are clarified, and the dynamic adjustment mechanism of its charging and discharging power is described.

[0049] It can be seen that this embodiment uses a mechanism modeling method based on the physical characteristics and control strategies of each energy device to express their power regulation process under frequency deviation using mathematical equations and logical relationships, and integrates them to construct a model that can comprehensively describe the system frequency response. By inputting the frequency deviation, the power output changes of each energy source can be simulated.

[0050] Step S103: Determine an evaluation index of the frequency regulation standby dimension based on the wind speed randomness parameter and the energy storage SOC limit parameter.

[0051] In some embodiments, the reserve kinetic energy that can be released by the wind turbine is calculated based on the wind speed uncertainty parameter, and the reserve power is determined by considering the difference between the rotor speed safety threshold and the current speed, and the difference between the maximum power tracking capability and the current output power.

[0052] For energy storage systems, the available regulation energy is dynamically calculated based on the current SOC value, rated capacity, and the minimum and maximum SOC limits. At the same time, the available regulation power is determined based on the rated charge and discharge power and SOC limits. These indicators together constitute the evaluation content of the frequency regulation backup dimension.

[0053] This embodiment uses wind speed uncertainty to estimate the potential adjustable power of wind turbines under different conditions, and then determines the actual available reserve capacity based on the physical limitations of the equipment. For energy storage, the maximum energy and power support that can be provided when frequency regulation is required is calculated based on the physical principles of energy storage and power output, as well as safety constraints.

[0054] Step S104: Determine an evaluation index of the frequency regulation strategy dimension based on the power regulation characteristics of each energy source in the system frequency response model.

[0055] This embodiment calculates the support power provided by the wind and energy storage system based on the power regulation characteristics of each energy source in the system frequency response model under different working conditions, that is, the cumulative value of the additional power generated by the wind turbine and the energy storage charging and discharging power.

[0056] At the same time, the total charging and discharging amount of energy storage during the entire frequency regulation process and the proportion of the total charging and discharging power to the total frequency regulation amount of the wind-storage combined system are counted to determine the contribution rate of energy storage in the combined frequency regulation.

[0057] This embodiment analyzes the time series data of power regulation of each energy source in the model and, according to certain calculation methods and logic, obtains the power support status of the wind-storage combined system and the contribution of energy storage, reflecting the collaborative working effect of each energy source under the current frequency regulation strategy.

[0058] 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.

[0059] 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.

[0060] 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.

[0061] 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.

[0062] 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.

[0063] 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.

[0064] 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: Obtain wind speed randomness parameters, load fluctuation parameters and energy storage SOC limit parameters as input basis.

[0065] 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.

[0066] In this embodiment, according to the Weibull distribution function, the probability density function of wind speed can be expressed as:

[0067] 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.

[0068] 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.

[0069] 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:

[0070] 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.

[0071] 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:

[0072] Where, SOC < SOC min , S SOC1 =0; SOC 1≤ SOC , S SOC1 =1; SOC min ≤ SOC < SOC 1,

[0073] 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.

[0074] The energy storage charging regulation power based on the state of charge is expressed as:

[0075] Where, SOC>SOC max , S SOC2 =0; SOC ≤ SOC 2, S SOC2 =1; SOC 2< SOC ≤ SOC max ,

[0076] 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.

[0077] In the method, a system frequency response model is constructed.

[0078] 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.

[0079] During the frequency regulation process, the principle of the system equations is mainly based on the dynamic characteristics of traditional units, the operating characteristics of wind turbines, and the control characteristics of energy storage systems. It is usually described by the following equations:

[0080]

[0081] Where, H is the inertia constant, which indicates the system's inertial response capability to frequency changes; p is wind power penetration rate; D is the damping coefficient of the system, which indicates the damping effect of the system on frequency changes; Δ f is the frequency deviation, that is, the difference between the actual frequency and the rated frequency; Δ P m is the mechanical power change, indicating the mechanical power adjustment of the generator set; Δ P e is the change in electrical power; Δ P g , Δ P B , Δ P W are the output power changes of traditional generator sets, energy storage systems, and wind turbine sets respectively; Δ P L is the disturbance power in the power system, which includes two aspects: on the one hand, the disturbance is caused by the fluctuation of the load, and on the other hand, the disturbance is caused by the randomness of wind power generation.

[0082] Therefore, the system frequency characteristic model is:

[0083] The frequency regulation response characteristics of the traditional generator set involved in this embodiment are based on Figure 2As shown in Figure 2, the frequency regulation control characteristics of traditional generator sets are an important guarantee for the stability of power system frequency. The characteristic equation of the output power of traditional generator sets participating in frequency regulation is:

[0084] Where, G gov ( s ), G gen ( s ) are the equivalent transfer functions of the governor and turbine respectively; R is the frequency regulation coefficient of a traditional generator set. The speed governor adjusts the mechanical power output of the generator set according to the frequency deviation, and the turbine converts the mechanical power command output by the speed governor into actual mechanical power output. Its dynamic characteristics can be expressed by the following transfer function:

[0085]

[0086] Where, K g is the gain of the speed regulator, which indicates the response strength of the speed regulator to frequency deviation; T g is the time constant of the speed regulator, which indicates the response speed of the speed regulator; T CH is the time constant of the main steam inlet chamber; T RH is the reheater time constant; F RH is the proportion of high-pressure turbine mechanical power.

[0087] The frequency modulation response characteristics of the wind turbine in this embodiment are based on the fact that the rotor of the wind turbine rotates under the action of wind power, transmits mechanical energy to the generator through the transmission system, and the generator converts the mechanical energy into electrical energy for output. The maximum power tracking curve of the wind turbine is as follows: Figure 3 As shown, each line represents the power of wind turbines at different wind speeds, and the output power P W It can be calculated by the following formula:

[0088] Where: k opt is the scale factor of the maximum power point tracking (MPPT) curve of the wind turbine; ω r is the rotor speed of the wind turbine; ω 0. ω1. ω max They are the minimum electrical angular velocity, the electrical angular velocity in the constant speed zone, and the maximum electrical angular velocity of the wind turbine respectively; P max The maximum output power of the wind turbine.

[0089] When the rotor kinetic energy of a doubly-fed wind turbine is converted into electromagnetic power in response to fluctuations in the system frequency, it enables the doubly-fed wind turbine to have an inertial support capability similar to that of a synchronous generator, providing frequency regulation support. The doubly-fed wind turbine needs to be able to adjust its output electromagnetic power according to changes in the grid frequency. The rotor kinetic energy and power released are described by the following formula:

[0090]

[0091] Where, E 0 is the initial speed ω The rotor kinetic energy corresponding to 0; E r The rotor speed after the unit participates in frequency regulation ω r The corresponding rotor kinetic energy; J is the moment of inertia of the wind turbine; Δ P ω The frequency modulation actively supports the power released by the rotor kinetic energy.

[0092] In order to enable the wind turbine to participate in the transient frequency adjustment of the power grid, an active power increment using differential control is added to the wind turbine. Its expression is as follows:

[0093] Where, K d is the virtual inertia response coefficient; d f / d t is the frequency change rate.

[0094] Wind turbine rotor kinetic energy control is applicable to the inertial response model of conventional power supply simulated by the following frequency model:

[0095] Where, T ω is the rotor inertia response time constant; Δ P W Inertial support power provided for rotor kinetic energy control.

[0096] The energy storage frequency regulation response configuration method of this embodiment is based on the energy storage system participating in system frequency regulation through virtual droop control to reduce frequency deviation, simulate traditional synchronous generators, and enhance grid stability. It is described by the following formula:

[0097] Where, K b is the virtual droop coefficient, Δ f Indicates frequency deviation.

[0098] The frequency response model can be obtained as:

[0099] 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.

[0100] 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:

[0101] 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.

[0102] This embodiment configures multi-dimensional evaluation indicators based on wind power energy storage coordinated frequency regulation.

[0103] 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.

[0104] 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: 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.

[0105] 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 regulate against frequency disturbances and is a fundamental guarantee for frequency regulation control.

[0106] 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: 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.

[0107] 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 C2 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. This dimension reveals the rationality of resource scheduling under different control strategies and guides parameter optimization.

[0108] For the frequency regulation effect dimension indicator of this embodiment, the frequency regulation effect dimension quantifies the actual dynamic response performance of the system, including: defining the utilization rate of wind turbines μ ; During the frequency regulation process, the ratio of the actual maximum power output of the wind turbine to the average adjustable output power; The formula for calculating the power utilization rate of the wind turbine is, μ= max{Δ P W} / Δ P ω ; μ= Δ E W / Δ E k .

[0109] Frequency Fluctuation Root Mean Square Error (RMSE): This evaluates the effectiveness of frequency fluctuation suppression and characterizes the degree of frequency deviation dispersion within the statistical period. Larger RMSE values indicate more severe system frequency fluctuations. RMSE amplifies the weight of larger deviations through a squaring operation, making it more sensitive to extreme frequency events (such as sudden surges and dips) and directly reflecting the system's stability margin against large disturbances. It is used to capture the intensity of transient frequency shocks caused by sudden power surges in high wind speed fluctuations. Keeping RMSE values below the threshold is essential for ensuring system safety.

[0110] The calculation formula is as follows:

[0111] 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.

[0112] Mean absolute error (MAE) of frequency fluctuation: reflects the average level of absolute frequency deviation within the statistical period. A larger MAE value indicates a more significant overall frequency deviation of the system.

[0113] MAE gives linear weight to all deviations, more intuitively depicting the cumulative impact of sustained small-amplitude frequency fluctuations. It is a core indicator for evaluating the steady-state accuracy of frequency regulation control. It is used to evaluate the steady-state regulation accuracy of frequency regulation resources in load-slowing scenarios. The smaller its value, the better the tracking ability of wind-storage coordinated control to the frequency reference point. It is calculated using the following formula: .

[0114] Comparing the ratio of a wind turbine's actual maximum power output to its adjustable capacity measures the extent to which the wind turbine exploits its dynamic regulation potential during frequency regulation. This reflects the depth of participation of the wind turbine in frequency disturbances. The higher the utilization rate, the greater the wind turbine's contribution to system frequency support through virtual inertia control and kinetic energy release. This provides a basis for optimizing wind turbine control strategies, avoiding underutilization due to excessive reserve kinetic energy, or secondary drops in system frequency and equipment safety risks caused by overregulation.

[0115] This implementation uses a squaring operation to amplify the weight of high-frequency deviations, characterizing the fluctuation amplitude of extreme events such as sudden frequency swells and dips. This quantitatively assesses the transient stability of the system during sudden load changes and wind turbine disconnections. Lower RMSE values indicate smaller frequency fluctuations during transients and higher system safety. This can serve as a rapid validation indicator for wind-storage combined frequency regulation strategies. For example, after optimizing virtual droop control parameters, a reduction in RMSE directly reflects improved transient response.

[0116] For the mean absolute error (MAE) of frequency fluctuations, the absolute value of all frequency deviations is averaged to eliminate the impact of positive and negative deviations, focusing on the overall level of long-term frequency deviation. It reflects the steady-state tracking capability of the wind-storage combined system in scenarios such as slow load changes and gradual wind speed changes. The smaller the MAE value, the closer the system frequency is to the rated value and the higher the power supply quality. It provides a basis for allocating frequency regulation tasks between traditional units and wind-storage systems. For example, when the MAE is high, the virtual droop coefficient of energy storage can be optimized or the power support ratio of wind turbines can be increased. It helps identify the attenuation of the frequency regulation capability of wind-storage systems in long-term operation (for example, frequent fluctuations in the energy storage SOC lead to a decrease in available capacity, which in turn causes the MAE to gradually increase), providing an auxiliary indicator for system economic evaluation.

[0117] To verify that the multi-dimensional wind-storage system frequency regulation capability assessment method described in this application can significantly improve the scientific nature of frequency regulation strategy evaluation and provide a quantifiable and verifiable decision-making basis for the optimized design of wind-storage system frequency regulation control schemes, the specific verification steps are given below.

[0118] A four-machine two-area frequency response model including a wind-storage combined system was developed in MATLAB / Simulink, such as Figure 4As shown. The grid's rated frequency is set at 50 Hz. The test system includes three synchronous generators (SG1, SG2, and SG4), representing traditional thermal and hydroelectric units, each with a rated power of 200 MW. The wind farm consists of 100 aggregated 2 MW wind turbines, using a single-unit equivalent model, for a total installed capacity of 200 MW. The energy storage units configured in this system utilize a modular parallel architecture of 25 groups, each rated at 1 MWh / 0.5 MW. When aggregated, they form a cluster system with a total rated capacity of 25 MWh and a total output power of 12.5 MW. This energy storage capacity is equivalent to 12.5% of the wind farm's rated installed capacity (a wind-to-storage capacity ratio of 1:0.125), serving a regional grid with a wind power penetration rate of approximately 25%. The rated wind speed is 12 m / s.

[0119] This example evaluates the frequency regulation control strategy under load disturbance. Specifically, when the wind speed is 12m / s and the simulation time is 24 seconds, a step load disturbance of 0.02 pu occurs at 1 second, followed by a step disturbance of 0.03 pu at 3 seconds, and a step disturbance of 0.05 pu at 5 seconds. Figure 5 shown.

[0120] This embodiment defines scenario 1 as only traditional generators participating in frequency regulation. Scenario 2 as only wind turbines participating in frequency regulation. Scenario 3 as wind-storage combined system participating in frequency regulation. Scenario 4 as wind-storage combined system participating in frequency regulation based on model predictive control (MPC). At the beginning of the simulation, the state of charge of the energy storage system is set to 0.8. The capacity ratio of energy storage configured in the wind farm is 0.5, and the charging and discharging efficiency of energy storage is 0.9. When the above disturbance occurs in the system, the frequency dynamic characteristics under the four frequency regulation control scenarios are as follows: Figure 6 As shown in Table 1, a multi-dimensional comprehensive evaluation of the regulation performance in these scenarios is conducted.

[0121] Table 1: Multi-dimensional comprehensive evaluation indicators

[0122] When the system experiences a step load fluctuation, the frequency dynamics of the system vary depending on the frequency regulation strategy. Before frequency regulation, the wind turbine stores kinetic energy in its rotor, while the energy storage system exhibits adjustable power and rapid charge / discharge capabilities based on its state of charge, ensuring a clear and controllable frequency regulation margin.

[0123] In the dynamic response process, Table 1 and Figure 7 (Δ P W )、 Figure 8 (Δ P B )and Figure 9 (C 1 and C 2) Revealed that despite Short-term inertial support can be provided by releasing rotor kinetic energy, but its reserve capacity is constrained by blade mass and speed limitations. This results in limited energy release in each frequency regulation event and the need to retain rotor speed recovery margin.

[0124] In scenario 2, repeated load steps may force wind turbines out of frequency regulation due to speed recovery requirements, thus creating a power gap and leading to a secondary frequency drop.

[0125] In contrast, the energy storage system (ESS), with its large energy storage capacity and flexible power regulation capability, dominates power compensation during medium- and long-term frequency disturbances and effectively suppresses steady-state frequency deviations.

[0126] In scenario 3, the coordinated wind-storage combined system frequency regulation compensates for the power gap when the wind turbines are disconnected, achieves time complementarity, and enhances system frequency stability.

[0127] Scenario 4 integrates model predictive control to optimize the power allocation between wind turbines and the ESS through multi-timescale predictions. This approach improves wind turbine power utilization and prevents secondary frequency drops in the later stages of regulation by utilizing the ESS.

[0128] Meanwhile, it reduces the frequency RMS error to 0.0681 and the frequency mean absolute error to 0.0640, as shown in FRMSE and FMAE in Table 1.

[0129] 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 pu occurs at 4 seconds, followed by a step disturbance of -0.02 pu at 6 seconds, a step disturbance of 0.05 pu at 7 seconds, and a step disturbance of 0.02 pu at 8 seconds. The initial wind speed of the wind turbine is 8.5 m / s, which drops to 7.5 m / s at 4 seconds, rises to 10 m / s at 6 seconds, drops to 9.5 m / s at 7 seconds, and drops to 8.5 m / s at 8 seconds. Figure 10 shown.

[0130] The simulation time is 24 seconds, and the system frequency response curve is as follows: Figure 11 At the beginning of the simulation, the state of charge of the energy storage system is set to 0.8. The capacity ratio of the energy storage configured in the wind farm is 0.5, and the charge and discharge efficiency of the energy storage is 0.9.

[0131] Table 2: Multi-dimensional comprehensive evaluation indicators

[0132] Figure 11 The frequency dynamic characteristics of the four scenarios are significantly different. Table 2 provides a comprehensive evaluation of the regulation performance under these scenarios. The frequency regulation spare dimension indicators in Table 2, combined with Figure 12 and Figure 13 The visualization results in show that the inertial support potential of the kinetic energy stored in the wind turbine rotor is affected by wind speed and rotational speed.

[0133] Under high wind speed conditions, the speed of the wind turbine rotor increases, thereby storing more kinetic energy. However, this energy reserve is still limited by the mechanical structure and operational safety threshold. The regulation capability of the energy storage system changes dynamically with the state of charge, and its available energy and power reserve show nonlinear changes during the frequency regulation process. Indicators of the frequency regulation strategy dimension and Figure 14 and Figure 15 It is shown that scenario 1, which relies only on traditional synchronous generators, is constrained by limited reserve capacity.

[0134] 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 frequency regulation requirements. In scenario 2, although the kinetic energy of the wind turbine can be released quickly, its limited reserve capacity leads to poor sustainability, causing secondary frequency fluctuations and low utilization efficiency. The total kinetic energy stored in the rotor is still far less than the energy storage, so the wind turbine alone cannot meet the system's frequency regulation requirements, and the frequency regulation strategy of the wind turbine needs to be optimized. The energy storage system, based on its high reserve energy / power, provides a flexible regulation basis for scenarios 3 and 4.

[0135] Figure 16 The results show that in scenarios 3 and 4, wind turbines and energy storage collaborate to provide short-term frequency support and medium- and long-term power compensation, with energy storage contributing over 80% to frequency regulation. Furthermore, the frequency regulation performance indicators in Table 2 show that scenarios 1 and 2 experience slow recovery and large steady-state deviations, while scenarios 3 and 4 effectively maintain frequency stability through continuous regulation. Scenario 4, based on model predictive control (MPC), optimizes the power allocation of the combined wind and energy storage system, achieving efficient coordination of frequency regulation resources. Throughout the process, more energy storage is consumed to compensate for the power gap during rotor speed recovery. It reduces the root mean square error of frequency fluctuations to 0.0782 and the mean absolute error of frequency to 0.0673 Hz, validating the significant advantages of this strategy in enhancing the dynamic characteristics of system frequency.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] In the embodiments of the present invention, electronic devices include, but are not limited to, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may 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 shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments of the present application described and / or claimed herein.

[0141] In the embodiment of the present application, the processor 101 can be implemented by using at least one of a special purpose integrated circuit, a programmable logic device, a field programmable gate array, a processor, a controller, a microcontroller, a microprocessor, and an electronic unit designed to perform the functions described herein. In some cases, such an embodiment can be implemented in a controller. For software implementation, an embodiment such as a process or function can be implemented with a separate software module that allows the execution of at least one function or operation. The software code can be implemented by a software application (or program) written in any appropriate programming language, and the software code can be stored in a memory and executed by a controller.

[0142] The display module 103 is used to display information input by the user or information provided to the user. The display module 103 may include a display panel, which may be configured in the form of a liquid crystal display, an organic light emitting diode, etc.

[0143] The memory 102 can be used to store software programs and various data. The memory 102 can include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0144] The present application also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for evaluating the frequency regulation capability of a multi-dimensional wind-storage combined system.

[0145] The storage medium can be any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0146] 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.

[0147] 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; 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; 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; 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: In step S101, the wind speed randomness parameter is based on the Weibull distribution function, and the probability density function of the 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.

3. The multi-dimensional wind-storage combined system frequency regulation capability evaluation method according to claim 1 is characterized in that: In step S101, the energy storage discharge adjustment 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 adjustment coefficient.

4. 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.

5. 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.

6. 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.

7. 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: 。 8. 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 7; 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.

9. 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 7 are implemented.

10. 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 7 are implemented.

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