Evaluation methods, devices, equipment, and media for power grid load frequency regulation performance

Abstract

This disclosure relates to a method, apparatus, equipment, and medium for evaluating the load frequency regulation performance of a power grid. The disclosure constructs a load frequency regulation model for a combined hydropower and wind power system based on a regulation system model of a hydropower unit and a power output model of a wind turbine unit. Based on this model, the time-domain and frequency-domain characteristics of the combined hydropower and wind power system are analyzed under a preset wind power frequency disturbance scenario. This yields time-domain and frequency-domain indices for evaluating the load frequency regulation performance of the combined hydropower and wind power system, generating a comprehensive evaluation index for the system's load frequency regulation performance. This disclosure improves the accuracy and comprehensiveness of the evaluation of the load frequency regulation performance of combined hydropower and wind power systems by comprehensively evaluating the load frequency regulation performance using both time-domain and frequency-domain indices.

Description

Technical Field

[0001] This disclosure relates to the field of power technology, and in particular to a method, apparatus, equipment and medium for evaluating the frequency regulation performance of power grid loads. Background Technology

[0002] Currently, the power industry is transitioning towards renewable energy sources such as hydropower, wind power, and solar power. However, due to the randomness, volatility, and unpredictability of wind energy, and the rapid start-up and shutdown and high flexibility of hydropower units, which can be used for peak shaving and frequency regulation of the power grid, combined hydropower and wind power systems are gradually gaining popularity in various countries. Evaluating the load frequency regulation performance of combined hydropower and wind power systems is of great significance for their safe and stable operation.

[0003] However, the current evaluation criteria for the load frequency regulation performance of combined hydropower and wind power systems are limited and cannot accurately assess the load frequency regulation performance of combined hydropower and wind power systems. Summary of the Invention

[0004] To address the aforementioned technical problems, this disclosure provides a method, apparatus, equipment, and medium for evaluating the frequency regulation performance of power grid loads.

[0005] The first aspect of this disclosure provides a method for evaluating the frequency regulation performance of a power grid load, comprising:

[0006] Based on the regulation system model of hydropower units and the power output model of wind turbine units, a load frequency regulation model of a combined hydropower and wind power system is constructed.

[0007] Based on the load frequency regulation model, the time-domain characteristics of the regulation performance of the hydropower-wind power combined system under the preset wind power frequency disturbance scenario are analyzed, and time-domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system are obtained.

[0008] Based on the load frequency regulation model, the frequency domain characteristics of the regulation performance of the hydropower-wind power combined system under the preset wind power frequency disturbance scenario are analyzed, and frequency domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system are obtained.

[0009] Based on time-domain and frequency-domain indicators, a comprehensive evaluation index for the load frequency regulation performance of a hydropower-wind power combined system is generated.

[0010] A second aspect of this disclosure provides an evaluation device for the frequency regulation performance of a power grid load, comprising:

[0011] The first construction module is used to construct a load frequency regulation model for a combined hydropower and wind power system based on the regulation system model of hydropower units and the power output model of wind power units.

[0012] The time-domain analysis module is used to perform time-domain characteristic analysis on the regulation performance of the hydropower-wind power combined system under a preset wind power frequency disturbance scenario based on the load frequency regulation model, and obtain time-domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system.

[0013] The frequency domain analysis module is used to perform frequency domain characteristic analysis on the regulation performance of the hydropower-wind power combined system under a preset wind power frequency disturbance scenario based on the load frequency regulation model, and obtain frequency domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system.

[0014] The generation module is used to generate comprehensive evaluation indicators for the load frequency regulation performance of hydropower and wind power combined systems based on time-domain and frequency-domain indicators.

[0015] A third aspect of this disclosure provides a computer device including a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, can implement the power grid load frequency regulation performance evaluation method of the first aspect described above.

[0016] The fourth aspect of this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the power grid load frequency regulation performance evaluation method of the first aspect described above.

[0017] The technical solution provided in this disclosure has the following advantages compared with the prior art:

[0018] This disclosure constructs a load frequency regulation model for a hydropower-wind power combined system based on a regulation system model of a hydropower unit and a power output model of a wind turbine unit. Based on this model, it performs time-domain characteristic analysis on the regulation performance of the combined system under a preset wind power frequency disturbance scenario, obtaining time-domain indices for evaluating the load frequency regulation performance. Similarly, based on the same model, it performs frequency-domain characteristic analysis on the same system under the same scenario, obtaining frequency-domain indices for evaluating the load frequency regulation performance. Finally, based on both time-domain and frequency-domain indices, a comprehensive evaluation index for the load frequency regulation performance of the combined hydropower-wind power system is generated. This disclosure improves the accuracy and comprehensiveness of the evaluation of the load frequency regulation performance of the combined hydropower-wind power system by comprehensively evaluating its performance using both time-domain and frequency-domain indices. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0020] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, those skilled in the art can obtain other drawings based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of a method for evaluating the frequency regulation performance of a power grid load according to an embodiment of this disclosure;

[0022] Figure 2 This is a schematic diagram of parameters for a wind power frequency disturbance scenario provided in an embodiment of this disclosure;

[0023] Figure 3 This is a flowchart of a method for evaluating the frequency regulation performance of a power grid load according to an embodiment of this disclosure;

[0024] Figure 4 This is a flowchart of a method for evaluating the frequency regulation performance of a power grid load according to an embodiment of this disclosure;

[0025] Figure 5 This is a schematic diagram of the structure of an evaluation device for power grid load frequency regulation performance provided in an embodiment of this disclosure;

[0026] Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this disclosure. Detailed Implementation

[0027] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0028] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0029] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0030] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0031] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0032] The method for evaluating the frequency regulation performance of power grid load provided in this disclosure can be executed by a computer device. This device can be understood as any device with processing and computing capabilities, including but not limited to mobile terminals such as smartphones, laptops, and tablets (PADs), as well as fixed electronic devices such as digital TVs and desktop computers.

[0033] To better understand the inventive concept of the embodiments of this disclosure, the technical solutions of the embodiments of this disclosure will be described below in conjunction with exemplary embodiments.

[0034] Figure 1 This is a flowchart illustrating a method for evaluating the frequency regulation performance of a power grid load, as provided in this embodiment. This method can be executed by a computer device, such as... Figure 1 As shown, the method for evaluating the frequency regulation performance of power grid load provided in this embodiment includes the following steps:

[0035] Step 110: Based on the regulation system model of hydropower units and the power output model of wind turbine units, construct a load frequency regulation model for the combined hydropower and wind power system.

[0036] In this embodiment of the disclosure, the computer device can construct a regulation system model of the hydropower unit and a power output model of the wind turbine unit, and then construct a load frequency regulation model of the hydropower-wind power combined system based on the regulation system model of the hydropower unit and the power output model of the wind turbine unit.

[0037] Hydropower units are hydroelectric generator sets; wind power units are wind turbine generator sets.

[0038] In some embodiments, before constructing the load frequency regulation model of the hydropower-wind power combined system, the computer equipment may execute S11-S13:

[0039] S11. Construct the speed regulation system model of the hydropower unit, the rigid water hammer model of the pipeline of the hydropower unit, the flow and torque characteristic output model of the turbine of the hydropower unit, and the generator model of the hydropower unit.

[0040] In this embodiment, the speed control system model of the hydropower unit can be understood as the governor model of the hydropower unit. For example, a proportional integral (PI) controller can be used as the governor of the hydropower unit. Ignoring its nonlinear characteristics, according to the hydraulic-mechanical subsystem governor system structure diagram, the transfer function of the speed control system model of the hydropower unit can be Equation (1):

[0041]

[0042] Among them, G g (s) is the transfer function of the speed governor; G s (s) is the transfer function of the hydraulic system of the hydroelectric generator; K p K is the proportional integral constant; i T is the integration time constant; y is the time constant of the relay.

[0043] Based on the principles of applied hydraulics, the basic motion and continuity characteristics of unsteady flow in the pressure pipeline of a hydroelectric generator can be described by the famous Saint-Venant equation, as shown in equation (2):

[0044]

[0045] Where A is the cross-sectional area of ​​the pipe; Q0 is the turbine flow rate of the hydropower unit; l is the distance between the pipe flow section and the set origin; a is the speed of the turbine; H0 is the turbine head; and α is the horizontal inclination angle of the pipe.

[0046] By ignoring minor terms and friction effects, a concise representation of the pipe model can be obtained using the Laplace transform, as shown in equation (3):

[0047]

[0048] Wherein, △H U For upstream head changes; △H D This represents the change in downstream water head; △Q U For upstream head changes; △Q D This refers to changes in downstream water head.

[0049] Using Taylor series expansion and ignoring terms of second order and above, the transfer function of the rigid water hammer model of the pipe can be obtained as shown in equation (4):

[0050]

[0051] Among them, G h (s) is the transfer function of the rigid water hammer model of the pipeline; T w Δh(s) represents the inertial time constant of the water flow in the pipeline; Δh(s) represents the head change in the pipeline; and Δq(s) represents the flow rate change in the pipeline.

[0052] The linearized equation of the output model of the flow-torque characteristics of the hydropower unit's turbine can be written as equation (5):

[0053] Δq=e qh Δh+e qω Δω r +e qy Δy (5);

[0054] Among them, e qh e qω e qy Δh is the flow transfer coefficient; Δh is the turbine head change; Δq is the turbine flow rate change; Δy is the turbine guide vane opening change; Δω r This represents the relative deviation of the turbine's rotational speed.

[0055] The transfer function of the generator model of the hydroelectric power unit can be expressed as equation (6):

[0056]

[0057] Where Gs is the transfer function of the generator model; T a e is the inertial time constant of the generator; n is the generator's self-regulation coefficient; s is the Laplace operator.

[0058] S12. Based on the speed regulation system model, rigid water hammer model, flow-torque characteristic output model, and generator model of the hydropower unit, construct the regulation system model of the hydropower unit.

[0059] S13. Based on the duct contact area and wind speed of the wind turbine, construct the power output model of the wind turbine.

[0060] Specifically, the output power of a wind turbine generator set is determined by the contact area of ​​the duct and the wind speed. The expression for the power output model of a wind turbine generator set can be given by equation (7):

[0061]

[0062] Among them, P ωC represents the power generation capacity of the wind turbine generator. P λ is the wind power coefficient; β is the blade tip velocity of the wind turbine; V is the blade pitch angle; ω R represents wind speed. b d is the blade radius; d is the air density.

[0063] Step 120: Based on the load frequency regulation model, perform time-domain characteristic analysis on the regulation performance of the hydropower-wind power combined system under the preset wind power frequency disturbance scenario, and obtain time-domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system.

[0064] In this embodiment of the disclosure, the computer device can perform time-domain characteristic analysis on the regulation performance of the hydropower-wind power combined system in a preset wind power frequency disturbance scenario based on the load frequency regulation model of the hydropower-wind power combined system, and obtain time-domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system.

[0065] The preset wind power frequency disturbance scenario can be understood as a pre-set wind power frequency disturbance scenario, which can be set as needed, and there is no limitation here.

[0066] For example, the preset wind power frequency disturbance scenario may include at least one of the following disturbance scenarios under at least one turbulence intensity: single-peak frequency disturbance scenario, positive skewed frequency disturbance scenario, negative skewed frequency disturbance scenario, and double-peak frequency disturbance scenario.

[0067] like Figure 2 As shown, Figure 2 A parameter diagram of wind power frequency disturbance scenarios is provided, including single-peak frequency disturbance scenario, positive skewed frequency disturbance scenario, negative skewed frequency disturbance scenario, and double-peak frequency disturbance scenario.

[0068] Among them, the time-domain indicators may include at least one of the deviation index, stability index, and complementarity index.

[0069] The deviation index can be understood as the degree of dispersion between the actual frequency and the standard frequency when the combined hydropower and wind power system performs load frequency regulation.

[0070] The stability index can be understood as the degree to which hydropower units compensate for power fluctuations in a hydropower-wind power combined system during load frequency regulation.

[0071] The complementarity index can be understood as a measure of the degree of power complementarity between hydropower units and wind power units when the combined hydropower and wind power system performs load frequency regulation.

[0072] Step 130: Based on the load frequency regulation model, perform frequency domain characteristic analysis on the regulation performance of the hydropower-wind power combined system under the preset wind power frequency disturbance scenario, and obtain frequency domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system.

[0073] In this embodiment of the disclosure, the computer device can perform frequency domain characteristic analysis on the regulation performance of the hydropower-wind power combined system in a preset wind power frequency disturbance scenario based on the load frequency regulation model of the hydropower-wind power combined system, and obtain frequency domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system.

[0074] The frequency domain index may include at least one of frequency deviation suppression and harmonic distortion rate.

[0075] Frequency deviation suppression can be understood as the degree to which hydropower units suppress frequency fluctuations caused by wind turbine units when a hydropower-wind power combined system performs load frequency regulation.

[0076] Harmonic distortion rate can be understood as the contribution of hydropower units to the load frequency regulation process of a combined hydropower and wind power system.

[0077] Step 140: Based on time-domain and frequency-domain indicators, generate a comprehensive evaluation index for the load frequency regulation performance of the hydropower-wind power combined system.

[0078] In this embodiment of the disclosure, after obtaining the time-domain and frequency-domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system, the computer device can generate a comprehensive evaluation index of the load frequency regulation performance of the hydropower-wind power combined system based on the time-domain and frequency-domain indicators.

[0079] This embodiment of the disclosure comprehensively evaluates the load frequency regulation performance of a hydropower-wind power combined system by using time-domain and frequency-domain indicators, thereby improving the accuracy and comprehensiveness of the evaluation of the load frequency regulation performance of the hydropower-wind power combined system.

[0080] Figure 3 This is a flowchart illustrating a method for evaluating the frequency regulation performance of a power grid load, as provided in this embodiment. This method can be executed by a computer device, such as... Figure 3 As shown, the method for evaluating the frequency regulation performance of power grid load provided in this embodiment includes the following steps:

[0081] Step 310: Based on the regulation system model of hydropower units and the power output model of wind turbine units, construct a load frequency regulation model for the combined hydropower and wind power system.

[0082] Step 320: Based on the load frequency regulation model, perform dynamic simulation of the hydropower-wind power combined system under the preset wind power frequency disturbance scenario.

[0083] Step 330: Based on the load frequency regulation model, perform time-domain characteristic analysis on the regulation performance of the hydropower-wind power combined system in the wind power frequency disturbance scenario at a preset time-domain angle, and obtain the deviation index, stability index and complementarity index of the load frequency regulation of the hydropower-wind power combined system.

[0084] Specifically, this may include steps 3301-3305:

[0085] Step 3301: Obtain a preset number of actual frequencies and a preset number of output powers of the hydropower-wind power combined system in the preset wind power frequency disturbance scenario.

[0086] The preset quantity can be set as needed; there is no limit here.

[0087] The preset duration can be set as needed; there is no limit here.

[0088] Step 3302: Calculate the root mean square of a preset number of actual frequencies and the standard frequency of the hydropower-wind power combined system, and determine the root mean square as the deviation index for load frequency regulation of the hydropower-wind power combined system.

[0089] For example, the deviation index for load frequency regulation of a combined hydropower and wind power system can be calculated according to equation (8):

[0090]

[0091] Among them, f rms The deviation index (root mean square); N is the preset quantity; f i f0 represents the actual frequency of the hydropower-wind power combined system corresponding to the i-th point on the frequency response curve; f0 is the standard frequency.

[0092] For example, Table 1 is a schematic table of the deviation index for load frequency regulation in a combined hydropower and wind power system:

[0093] Table 1

[0094]

[0095] Step 3303: Based on a preset number of output powers, calculate the power smoothness of the hydropower-wind power combined system during load frequency regulation, and determine the power smoothness as the stability index of the hydropower-wind power combined system for load frequency regulation.

[0096] For example, the stability index of load frequency regulation in a combined hydropower and wind power system can be calculated according to equation (9):

[0097]

[0098] Among them, I s Deviation index for load frequency regulation of hydropower-wind power combined systems (power smoothness of hydropower-wind power combined systems); A s It is an amplification factor for the complementarity index; T s Sampling interval; point P h,i Let be the output power of the hydropower-wind power combined system corresponding to the i-th point on the frequency response curve.

[0099] For example, Table 2 is a schematic table of the stability index of load frequency regulation in a combined hydropower and wind power system:

[0100] Table 2

[0101]

[0102] Step 3303: Based on a preset number of output power and the average wind power setpoint for load frequency regulation of the hydropower-wind power combined system, calculate the complementarity index of load frequency regulation of the hydropower-wind power combined system.

[0103] For example, the complementarity index for load frequency regulation of a combined hydropower and wind power system can be calculated according to equation (10):

[0104]

[0105] Among them, I C The complementarity index for load frequency regulation in hydropower-wind power combined systems; ΔP * w,avg The average wind power setpoint for load frequency regulation in a combined hydropower and wind power system.

[0106] Step 340: Based on the deviation index, stability index, and complementarity index, construct a time-domain index for evaluating the load frequency regulation performance of a hydropower-wind power combined system.

[0107] Step 350: Based on the load frequency regulation model, perform frequency domain characteristic analysis on the regulation performance of the hydropower-wind power combined system in the preset wind power frequency disturbance scenario, and obtain the frequency deviation suppression degree and harmonic distortion rate of the load frequency regulation of the hydropower-wind power combined system.

[0108] Specifically, this may include steps 3501-3505:

[0109] Step 3501: Calculate the power fluctuation value of the wind turbine based on the output power of the wind turbine in the preset wind power frequency disturbance scenario.

[0110] For example, according to Passevar's law and Rayleigh's energy theorem, the sum of squares of a random time series signal is equivalent to the square of its Fourier transform amplitude, i.e., equation (11):

[0111]

[0112] Where x(t) represents the time series signal of the wind turbine's output power; T is the observation period; f is the frequency of the wind turbine's output power; F x This represents the Fourier transform of the wind turbine's output power in the frequency domain.

[0113] By statistically averaging each possible power spectrum, the power spectral density of the wind turbine's output power is obtained, as shown in Equation (12):

[0114]

[0115] Where E represents the expected value; S x (f) is the statistical average of the different output powers of the wind turbine in Fourier transform.

[0116] By applying the windowed Fourier transform to the equation, analysis can be performed within a finite time period. Combined with the Wiener-Khinchin theorem, consistency of random fluctuations in the time and frequency domain studies is achieved, as shown in equation (13):

[0117]

[0118] Where, x T (t) represents the truncated version of x(t) within a finite time window [-T, T]; X T (f) represents the signal x T (t) Frequency domain representation after Fourier transform; e -j2Πft The kernel represents the Fourier transform; j is the imaginary unit.

[0119] Then, the power spectral density distribution of the wind turbine's output power is discretized, and the k-th power fluctuation value of the wind turbine can be expressed as Equation (14):

[0120]

[0121] Among them, T s The sampling interval is defined as x, representing the power fluctuation value of the wind turbine at a given moment. T [i] = ΔP(t) i ), where △P represents the power change of the wind turbine; the i-th sampling point is t. i = (i-1)T s N = T / T s DFT (Discrete Fourier Transform) represents the Discrete Fourier Transform.

[0122] Step 3502: Calculate the power spectral density of the wind turbine output power based on the power fluctuation value.

[0123] For example, equation (14) above can be rewritten as equation (15):

[0124]

[0125] Among them, S x (k) represents the power spectral density of the kth output power of the wind turbine.

[0126] For comparison, the spectral density analysis of the power fluctuation of the wind turbine was performed using the MATLAB function "pwelch". Specifically, the normalized average power of the wind turbine was integrated with the power of the wind turbine over different time periods to obtain the power spectral density distribution characteristics of the wind turbine output power.

[0127] Step 3503: Calculate the power spectral density of the total power output of the hydropower-wind power combined system based on the total power output in the preset wind power frequency disturbance scenario.

[0128] The calculation process of step 3503 in this embodiment can refer to the calculation process of the power spectral density of the wind turbine output power described above, and will not be repeated here.

[0129] Step 3504: Based on the power spectral density of the wind turbine and the power spectral density of the total power, calculate the frequency deviation suppression degree of the combined hydropower and wind power system for load frequency regulation.

[0130] In this embodiment of the disclosure, based on the power spectral density distribution characteristics of wind turbine generators, the suppression effect of hydroelectric generators on wind power fluctuations was further studied.

[0131] For example, the frequency deviation suppression degree of load frequency regulation in a combined hydropower and wind power system can be calculated using equation (16):

[0132]

[0133] Where W represents the frequency deviation suppression degree of the combined hydropower and wind power system for load frequency regulation; N is the preset quantity.

[0134] Step 3605: Based on the frequency of the total output power of the hydropower-wind power combined system, calculate the harmonic distortion rate of the load frequency regulation of the hydropower-wind power combined system.

[0135] For example, the harmonic distortion rate of a combined hydropower and wind power system for load frequency regulation can be calculated using equation (17):

[0136]

[0137] Where HD represents the harmonic distortion rate of the combined hydropower and wind power system for load frequency regulation; Ck This represents the Fourier coefficient of the frequency component of the k-th total power output of the combined hydropower and wind power system in Fourier fast analysis; the frequency corresponding to the k-th total power frequency component is f. k =kf s / N,f s is the sampling frequency; A is the frequency band range related to the fluctuation of the input signal; C0 represents the Fourier coefficient of the frequency component of the 0th total power.

[0138] For example, Table 3 is a schematic table of the complementarity index for load frequency regulation in a combined hydropower and wind power system:

[0139] Table 3

[0140]

[0141] For example, Table 4 is a schematic diagram of the frequency deviation suppression degree of load frequency regulation in a combined hydropower and wind power system:

[0142] Table 4

[0143]

[0144] For example, Table 5 is a schematic table of harmonic distortion rates for load frequency regulation in a combined hydropower and wind power system:

[0145] In Table 5, the harmonic distortion rate reaches its maximum value in the low-frequency band (LF band), close to 1, indicating that the hydropower unit has little effect on improving the harmonic enhancement in the low-frequency band. However, the harmonic distortion rates of the hydropower unit in the mid-frequency band (MF band) and high-frequency band (HF band) are reduced to 0.78 and 0.73, respectively, with a significant improvement in the enhancement effect. Furthermore, there is a significant reduction in the mid-frequency band, which leads to a change in the suppression trend. This further proves that hydropower can alleviate the frequency shift caused by wind power fluctuations.

[0146] Table 5

[0147]

[0148] Step 370: Based on the frequency deviation suppression degree and harmonic distortion rate, construct a frequency domain index for evaluating the load frequency regulation performance of the hydropower-wind power combined system.

[0149] Step 380: Based on time-domain and frequency-domain indicators, generate a comprehensive evaluation index for the load frequency regulation performance of the hydropower-wind power combined system.

[0150] Therefore, the load frequency regulation performance of hydropower-wind power combined systems can be comprehensively evaluated through time-domain and frequency-domain indicators, improving the accuracy and comprehensiveness of the evaluation of load frequency regulation performance of hydropower-wind power combined systems.

[0151] In some embodiments of this disclosure, the comprehensive evaluation index for the load frequency regulation performance of the hydropower-wind power combined system is generated based on time-domain and frequency-domain indicators. The computer equipment can execute this evaluation. Figure 4 A flowchart of a method for evaluating the frequency regulation performance of power grid loads is provided, such as... Figure 4 As shown, the method for evaluating the frequency regulation performance of power grid load provided in this embodiment includes the following steps:

[0152] Step 410: Obtain the correlation between each indicator in the time domain and frequency domain and the comprehensive evaluation indicator, as well as the comparative importance of each indicator.

[0153] In this embodiment of the disclosure, after obtaining the time-domain and frequency-domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system, the computer device can obtain the correlation between each indicator in the time-domain and frequency-domain indicators and the comprehensive evaluation indicator, as well as the comparative importance of each indicator.

[0154] Correlation can include positive correlation and negative correlation.

[0155] Among them, the deviation index, stability index, and complementarity index in the time domain are negatively correlated with the comprehensive evaluation index; the frequency deviation suppression degree in the frequency domain is positively correlated with the comprehensive evaluation index, while the harmonic distortion rate is negatively correlated with the comprehensive evaluation index.

[0156] Step 420: Based on the comparative importance of each indicator in the time domain and frequency domain, calculate the initial weight value of each indicator relative to the comprehensive evaluation indicator.

[0157] In this embodiment of the disclosure, the computer device can calculate the initial weight value of each indicator relative to the comprehensive evaluation indicator based on the comparative importance of each indicator and the Analytic Hierarchy Process (AHP).

[0158] Specifically, the comparative importance of time-domain indicators such as deviation index, stability index, and complementarity index, as well as frequency deviation suppression and harmonic distortion rate in frequency-domain indicators, can be obtained. For example, as shown in Table 6, Table 6 provides the comparative importance of each indicator:

[0159] Table 6

[0160]

[0161] In some embodiments, calculating the initial weight value of each indicator relative to the comprehensive evaluation indicator based on the comparative importance of each indicator in the time domain and frequency domain indicators may include steps 4201-4203:

[0162] Step 4201: Construct a comparison matrix based on the comparative importance of each indicator.

[0163] Specifically, the comparative importance of each indicator can be used as elements of a matrix to construct a comparison matrix.

[0164] Step 4202: Solve for the total eigenvector of the comparison matrix and the eigenvector corresponding to the comparison importance of each indicator.

[0165] Step 4203: For each indicator, calculate the proportion of the feature vector corresponding to the comparative importance of each indicator to the total feature vector, and obtain the initial weight value of the indicator relative to the comprehensive evaluation indicator.

[0166] For example, as shown in Table 7, Table 7 provides the analysis results of the analytic hierarchy process:

[0167] Table 7

[0168]

[0169] Table 2 shows the weight calculation results of the analytic hierarchy process (AHP). The weight of the deviation index is 5.882%, the weight of the complementarity index is 17.647%, the weight of the stability index is 29.412%, the weight of the frequency deviation suppression degree is 29.412%, and the weight of the harmonic distortion rate is 17.647%.

[0170] Step 430: Based on the correlation between each indicator and the comprehensive evaluation indicator, determine the sign of the initial weight value of the indicator relative to the comprehensive evaluation indicator. The sign of the weight value corresponding to a positive correlation is positive, and the sign of the weight value corresponding to a negative correlation is negative.

[0171] Specifically, in the time domain, the deviation index, stability index, and complementarity index are negatively correlated with the comprehensive evaluation index, so the initial weight values ​​of the deviation index, stability index, and complementarity index all have negative signs. In the frequency domain, the frequency deviation suppression degree is positively correlated with the comprehensive evaluation index, while the harmonic distortion rate is negatively correlated with the comprehensive evaluation index, so the initial weight values ​​of the frequency deviation suppression degree all have positive signs, while the initial weight values ​​of the harmonic distortion rate all have negative signs.

[0172] Step 440: For each indicator, multiply the initial weight value by the sign of the weight value corresponding to the initial weight value to obtain the target weight value corresponding to that indicator.

[0173] Step 450: Weight the sum of each index in the time domain and frequency domain with the target weight value corresponding to the index to obtain the comprehensive evaluation index of the load frequency regulation performance of the hydropower and wind power combined system.

[0174] In some embodiments, the computer device may also perform a consistency check on the comparison matrix described above.

[0175] CI is a consistency index that measures the deviation of the comparison matrix. CI = (λ-n) / (n-1). The larger the CI, the worse the consistency of the comparison matrix. When CI is 0, the comparison matrix has perfect consistency.

[0176] CR is the consistency ratio, and the formula is: CR = CI / RI, where RI is the average random consistency index. When CR < 0.1, the consistency of the comparison matrix can be considered acceptable.

[0177] For example, the consistency test results can be shown in Table 8:

[0178] Table 8

[0179]

[0180] The largest eigenvalue is the largest eigenvalue of a matrix.

[0181] Figure 5 This is a schematic diagram of the structure of an evaluation device for power grid load frequency regulation performance provided in an embodiment of this disclosure. This device can be understood as the aforementioned computer equipment or a functional module within the aforementioned computer equipment. For example... Figure 5 As shown, the power grid load frequency regulation performance evaluation device 500 includes:

[0182] The first construction module 510 is used to construct a load frequency regulation model of a hydropower-wind power combined system based on the regulation system model of hydropower units and the power output model of wind power units.

[0183] The time-domain analysis module 520 is used to perform time-domain characteristic analysis on the regulation performance of the hydropower-wind power combined system in a preset wind power frequency disturbance scenario based on the load frequency regulation model, and obtain time-domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system.

[0184] The frequency domain analysis module 530 is used to perform frequency domain characteristic analysis on the regulation performance of the hydropower-wind power combined system in a preset wind power frequency disturbance scenario based on the load frequency regulation model, and obtain frequency domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system.

[0185] The generation module 540 is used to generate a comprehensive evaluation index of the load frequency regulation performance of the hydropower-wind power combined system based on the time domain index and the frequency domain index.

[0186] Optionally, the above-mentioned evaluation device for power grid load frequency regulation performance includes:

[0187] The second construction module is used to construct the speed regulation system model of the hydropower unit, the rigid water hammer model of the pipeline of the hydropower unit, the flow and torque characteristic output model of the turbine of the hydropower unit, and the generator model of the hydropower unit.

[0188] The third construction module is used to construct the regulating system model of the hydropower unit based on the speed regulation system model, the rigid water hammer model, the flow torque characteristic output model, and the generator model.

[0189] The fourth module is used to construct the power output model of the wind turbine based on the duct contact area of ​​the wind turbine and the wind speed received by the wind turbine.

[0190] Optionally, the aforementioned time-domain indicators include at least one of the deviation index, stability index, and complementarity index;

[0191] The deviation index is used to evaluate the degree of dispersion between the actual frequency and the standard frequency when the hydropower and wind power combined system performs load frequency regulation;

[0192] The stability index is used to evaluate the degree of compensation of the hydropower generator to the power fluctuation of the hydropower-wind power combined system during the load frequency regulation process.

[0193] The complementarity index is used to evaluate the degree of power complementarity between the hydropower units and the wind power units when the hydropower-wind power combined system performs load frequency regulation.

[0194] The aforementioned time-domain analysis module includes:

[0195] The time-domain simulation submodule is used to perform dynamic simulation of the hydropower-wind power combined system under a preset wind power frequency disturbance scenario.

[0196] The time-domain analysis submodule is used to perform time-domain characteristic analysis on the regulation performance of the hydropower-wind power combined system in a wind power frequency disturbance scenario at a preset time-domain angle, based on the load frequency regulation model, and to obtain the deviation index, stability index and complementarity index of the load frequency regulation of the hydropower-wind power combined system.

[0197] The time-domain index submodule is used to construct time-domain indices for evaluating the load frequency regulation performance of the hydropower-wind power combined system based on the deviation index, stability index, and complementarity index.

[0198] Optionally, the above time-domain analysis submodule includes:

[0199] The acquisition unit is used to acquire a preset number of actual frequencies of the hydropower-wind power combined system and a preset number of output powers of the hydropower-wind power combined system in the preset wind power frequency disturbance scenario.

[0200] The first calculation unit is used to calculate the root mean square of a preset number of actual frequencies and the standard frequency of the hydropower-wind power combined system, and to determine the root mean square as the deviation index for load frequency regulation of the hydropower-wind power combined system.

[0201] The second calculation unit is used to calculate the power smoothness of the hydropower-wind power combined system within a preset time period based on a preset number of output powers, and to determine the power smoothness as the stability index of the hydropower-wind power combined system for load frequency regulation.

[0202] The third calculation unit is used to calculate the complementarity index of the load frequency regulation of the hydropower-wind power combined system based on the preset number of output powers and the average wind power setpoint for load frequency regulation of the hydropower-wind power combined system.

[0203] Optionally, the frequency domain metrics mentioned above include at least one of frequency deviation suppression and harmonic distortion.

[0204] The frequency deviation suppression degree is used to evaluate the degree to which the hydropower unit suppresses the frequency fluctuations generated by the wind power unit when the hydropower-wind power combined system performs load frequency regulation;

[0205] The harmonic distortion rate is used to evaluate the contribution of the hydropower unit to the load frequency regulation process of the hydropower-wind power combined system.

[0206] The frequency domain analysis module mentioned above includes:

[0207] The frequency domain simulation submodule is used to perform dynamic simulation of the load frequency regulation model under a preset wind power frequency disturbance scenario.

[0208] The frequency domain analysis submodule is used to perform frequency domain characteristic analysis on the regulation performance of the hydropower-wind power combined system in a preset wind power frequency disturbance scenario based on the load frequency regulation model, and to obtain the frequency deviation suppression degree and harmonic distortion rate of the load frequency regulation of the hydropower-wind power combined system.

[0209] The frequency domain index construction submodule is used to construct frequency domain indices for evaluating the load frequency regulation performance of the hydropower-wind power combined system based on the frequency deviation suppression degree and the harmonic distortion rate.

[0210] Optionally, the frequency domain analysis submodule mentioned above includes:

[0211] The fourth calculation unit is used to calculate the power fluctuation value of the wind turbine based on the output power of the wind turbine in the preset wind power frequency disturbance scenario.

[0212] The fifth calculation unit is used to calculate the power spectral density of the wind turbine output power based on the power fluctuation value;

[0213] The sixth calculation unit is used to calculate the power spectral density of the total power output by the hydropower-wind power combined system in the preset wind power frequency disturbance scenario.

[0214] The seventh calculation unit is used to calculate the frequency deviation suppression degree of the hydropower-wind power combined system for load frequency regulation based on the power spectral density of the wind turbine and the power spectral density of the total power.

[0215] The eighth calculation unit is used to calculate the harmonic distortion rate of the combined hydropower and wind power system for load frequency regulation based on the frequency of the total power output of the combined hydropower and wind power system.

[0216] Optionally, the above-mentioned generation module includes:

[0217] The acquisition submodule is used to acquire the correlation between each of the time-domain indicators and the frequency-domain indicators and the comprehensive evaluation indicator, as well as the comparative importance of each indicator.

[0218] The weight calculation submodule is used to calculate the initial weight value of each indicator relative to the comprehensive evaluation indicator based on the comparative importance of each indicator in the time domain indicator and the frequency domain indicator.

[0219] The sign determination submodule is used to determine the sign of the weight value corresponding to the initial weight value of each indicator relative to the comprehensive evaluation indicator based on the correlation between each indicator and the comprehensive evaluation indicator, wherein the weight value sign corresponding to a positive correlation is positive and the weight value sign corresponding to a negative correlation is negative.

[0220] The multiplication submodule is used to multiply the initial weight value with the sign of the weight value corresponding to the initial weight value for each of the indicators to obtain the target weight value corresponding to the indicator.

[0221] The summation submodule is used to perform a weighted summation of each index in the time domain and the frequency domain with the target weight value corresponding to the index, so as to obtain a comprehensive evaluation index of the load frequency regulation performance of the hydropower and wind power combined system.

[0222] Optionally, the above weight calculation submodule includes:

[0223] A construction unit is used to construct a comparison matrix based on the comparative importance of each indicator.

[0224] The solving unit is used to solve for the total eigenvector of the comparison matrix and the eigenvector corresponding to the comparison importance of each indicator;

[0225] The proportion calculation unit is used to calculate the proportion of the feature vector corresponding to the comparative importance of each indicator to the total feature vector for each indicator, so as to obtain the initial weight value of the indicator relative to the comprehensive evaluation indicator.

[0226] The power grid load frequency regulation performance evaluation device provided in this embodiment can implement the method of any of the above embodiments, and its execution mode and beneficial effects are similar, so they will not be described again here.

[0227] This disclosure also provides a computer device, which includes a processor and a memory, wherein the memory stores a computer program. When the computer program is executed by the processor, it can implement the methods of any of the above embodiments. The execution method and beneficial effects are similar, and will not be described again here.

[0228] Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this disclosure, such as... Figure 6 As shown, the computer device 600 may include a processor 610 and a memory 620. The memory 620 stores a computer program 621. When the computer program 621 is executed by the processor 610, it can implement the method provided in any of the above embodiments. The execution mode and beneficial effects are similar and will not be described again here.

[0229] Of course, for the sake of simplicity, Figure 6 Only some of the components of the computer device 600 relevant to the present invention are shown in this illustration; components such as buses, input / output interfaces, input devices, and output devices are omitted. In addition, the computer device 600 may include any other suitable components depending on the specific application.

[0230] This disclosure provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it can implement the methods of any of the above embodiments. The execution method and beneficial effects are similar, and will not be described again here.

[0231] The aforementioned computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0232] The computer program described above can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this disclosure. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer device, partially on the user's device, as a standalone software package, partially on the user's computer device and partially on a remote computer device, or entirely on a remote computer device or server.

[0233] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0234] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0235] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating the frequency regulation performance of power grid loads, characterized in that, include: Based on the regulation system model of hydropower units and the power output model of wind turbine units, a load frequency regulation model of a combined hydropower and wind power system is constructed. Based on the load frequency regulation model, the time-domain characteristics of the regulation performance of the hydropower-wind power combined system in a preset wind power frequency disturbance scenario are analyzed to obtain time-domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system. Based on the load frequency regulation model, the frequency domain characteristics of the regulation performance of the hydropower-wind power combined system in a preset wind power frequency disturbance scenario are analyzed to obtain frequency domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system. Based on the time-domain index and the frequency-domain index, a comprehensive evaluation index for the load frequency regulation performance of the hydropower-wind power combined system is generated. The comprehensive evaluation index for generating the load frequency regulation performance of the hydropower-wind power combined system based on the time-domain index and the frequency-domain index includes: Obtain the correlation between each of the time-domain and frequency-domain indicators and the comprehensive evaluation indicator, as well as the comparative importance of each indicator; Based on the comparative importance of each indicator in the time domain and frequency domain, the initial weight value of each indicator relative to the comprehensive evaluation indicator is calculated. Based on the correlation between each indicator and the comprehensive evaluation indicator, the sign of the weight value corresponding to the initial weight value of the indicator relative to the comprehensive evaluation indicator is determined, wherein the sign of the weight value corresponding to a positive correlation is positive, and the sign of the weight value corresponding to a negative correlation is negative. For each of the aforementioned indicators, the initial weight value is multiplied by the sign of the weight value corresponding to the initial weight value to obtain the target weight value corresponding to the indicator. The load frequency regulation performance of the hydropower-wind power combined system is obtained by weighting and summing each index in the time domain and the frequency domain with the target weight value corresponding to the index. The calculation of the initial weight value of each indicator relative to the comprehensive evaluation indicator based on the comparative importance of each indicator in the time domain and frequency domain indicators includes: Based on the comparative importance of each indicator, a comparison matrix is ​​constructed; Solve for the total eigenvector of the comparison matrix and the eigenvector corresponding to the comparison importance of each indicator; For each of the indicators, the proportion of the feature vector corresponding to the comparative importance of each indicator to the total feature vector is calculated to obtain the initial weight value of the indicator relative to the comprehensive evaluation indicator.

2. The method according to claim 1, characterized in that, Before constructing the load frequency regulation model of the hydropower-wind power combined system based on the regulation system model of the hydropower unit and the power output model of the wind power unit, the method further includes: Construct a speed control system model for the hydropower unit, a rigid water hammer model for the pipeline of the hydropower unit, a flow-torque characteristic output model for the turbine of the hydropower unit, and a generator model for the hydropower unit; Based on the speed regulation system model, the rigid water hammer model, the flow-torque characteristic output model, and the generator model, a regulation system model for the hydropower unit is constructed. Based on the duct contact area of ​​the wind turbine and the wind speed received by the wind turbine, a power output model of the wind turbine is constructed.

3. The method according to claim 1, characterized in that, The time-domain index includes at least one of the deviation index, stability index, and complementarity index; The deviation index is used to evaluate the degree of dispersion between the actual frequency and the standard frequency when the hydropower and wind power combined system performs load frequency regulation; The stability index is used to evaluate the degree of compensation of the hydropower generator to the power fluctuation of the hydropower-wind power combined system during the load frequency regulation process. The complementarity index is used to evaluate the degree of power complementarity between the hydropower units and the wind power units when the hydropower-wind power combined system performs load frequency regulation. Based on the load frequency regulation model, the time-domain characteristics analysis of the regulation performance of the hydropower-wind power combined system under a preset wind power frequency disturbance scenario is performed to obtain time-domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system, including: Dynamic simulation of the hydropower-wind power combined system under a preset wind power frequency disturbance scenario was performed. Based on the load frequency regulation model, the regulation performance of the hydropower-wind power combined system in a wind power frequency disturbance scenario at a preset time domain angle is analyzed in the time domain, and the deviation index, stability index and complementarity index of the load frequency regulation of the hydropower-wind power combined system are obtained. Based on the aforementioned deviation index, stability index, and complementarity index, a time-domain index is constructed to evaluate the load frequency regulation performance of the hydropower-wind power combined system.

4. The method according to claim 3, characterized in that, Based on the load frequency regulation model, the time-domain characteristics analysis of the regulation performance of the hydropower-wind power combined system in a wind power frequency disturbance scenario at a preset time-domain angle is performed to obtain the deviation index, stability index, and complementarity index of the load frequency regulation of the hydropower-wind power combined system, including: Obtain a preset number of actual frequencies of the hydropower-wind power combined system and a preset number of output powers of the hydropower-wind power combined system in the preset wind power frequency disturbance scenario. Calculate the root mean square of a preset number of actual frequencies and the standard frequency of the hydropower-wind power combined system, and determine the root mean square as the deviation index for load frequency regulation of the hydropower-wind power combined system; Based on a preset number of output powers, the power smoothness of the hydropower-wind power combined system within a preset time period is calculated, and the power smoothness is determined as the stability index of the hydropower-wind power combined system for load frequency regulation. Based on the preset number of output powers and the average wind power setpoint for load frequency regulation of the hydropower-wind power combined system, the complementarity index for load frequency regulation of the hydropower-wind power combined system is calculated.

5. The method according to claim 1, characterized in that, The frequency domain index includes at least one of frequency deviation suppression degree and harmonic distortion rate; The frequency deviation suppression degree is used to evaluate the degree to which the hydropower unit suppresses the frequency fluctuations generated by the wind power unit when the hydropower-wind power combined system performs load frequency regulation; The harmonic distortion rate is used to evaluate the contribution of the hydropower unit to the load frequency regulation process of the hydropower-wind power combined system. Based on the load frequency regulation model, the frequency domain characteristics analysis of the regulation performance of the hydropower-wind power combined system under a preset wind power frequency disturbance scenario is performed to obtain frequency domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system, including: Dynamic simulation of the load frequency regulation model under a preset wind power frequency disturbance scenario is performed. Based on the load frequency regulation model, the frequency domain characteristics of the regulation performance of the hydropower-wind power combined system in a preset wind power frequency disturbance scenario are analyzed to obtain the frequency deviation suppression degree and harmonic distortion rate of the load frequency regulation of the hydropower-wind power combined system. Based on the frequency deviation suppression degree and the harmonic distortion rate, a frequency domain index is constructed to evaluate the load frequency regulation performance of the hydropower-wind power combined system.

6. The method according to claim 5, characterized in that, Based on the load frequency regulation model, the frequency domain characteristics analysis of the regulation performance of the hydropower-wind power combined system under a preset wind power frequency disturbance scenario is performed to obtain the frequency deviation suppression degree and harmonic distortion rate of the load frequency regulation of the hydropower-wind power combined system, including: Based on the output power of the wind turbine in the preset wind power frequency disturbance scenario, calculate the power fluctuation value of the wind turbine. Based on the power fluctuation value, calculate the power spectral density of the wind turbine output power; Based on the total power output of the hydropower-wind power combined system in the preset wind power frequency disturbance scenario, calculate the power spectral density of the total power; Based on the power spectral density of the wind turbine and the power spectral density of the total power, the frequency deviation suppression degree of the combined hydropower and wind power system for load frequency regulation is calculated. Based on the frequency of the total output power of the hydropower-wind power combined system, calculate the harmonic distortion rate of the load frequency regulation of the hydropower-wind power combined system.

7. The method according to claim 1, characterized in that, The preset wind power frequency disturbance scenario includes at least one of the following disturbance scenarios under turbulence intensity: single-peak frequency disturbance scenario, positive skewed frequency disturbance scenario, negative skewed frequency disturbance scenario, and double-peak frequency disturbance scenario.

8. A device for evaluating the frequency regulation performance of a power grid load, characterized in that, include: The first construction module is used to construct a load frequency regulation model for a combined hydropower and wind power system based on the regulation system model of hydropower units and the power output model of wind power units. The time-domain analysis module is used to perform time-domain characteristic analysis on the regulation performance of the hydropower-wind power combined system under a preset wind power frequency disturbance scenario based on the load frequency regulation model, and obtain time-domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system. The frequency domain analysis module is used to perform frequency domain characteristic analysis on the regulation performance of the hydropower-wind power combined system under a preset wind power frequency disturbance scenario based on the load frequency regulation model, and obtain frequency domain indicators for evaluating the load frequency regulation performance of the hydropower-wind power combined system. The generation module is used to generate a comprehensive evaluation index of the load frequency regulation performance of the hydropower-wind power combined system based on the time domain index and the frequency domain index. The generation module includes: The acquisition submodule is used to acquire the correlation between each of the time-domain indicators and the frequency-domain indicators and the comprehensive evaluation indicator, as well as the comparative importance of each indicator. The weight calculation submodule is used to calculate the initial weight value of each indicator relative to the comprehensive evaluation indicator based on the comparative importance of each indicator in the time domain indicator and the frequency domain indicator. The sign determination submodule is used to determine the sign of the weight value corresponding to the initial weight value of each indicator relative to the comprehensive evaluation indicator based on the correlation between each indicator and the comprehensive evaluation indicator, wherein the weight value sign corresponding to a positive correlation is positive and the weight value sign corresponding to a negative correlation is negative. The multiplication submodule is used to multiply the initial weight value with the sign of the weight value corresponding to the initial weight value for each of the indicators to obtain the target weight value corresponding to the indicator. The summation submodule is used to perform a weighted summation of each index in the time domain and the frequency domain with the target weight value corresponding to the index, so as to obtain a comprehensive evaluation index of the load frequency regulation performance of the hydropower and wind power combined system. The weight calculation submodule includes: A construction unit is used to construct a comparison matrix based on the comparative importance of each indicator. The solving unit is used to solve for the total eigenvector of the comparison matrix and the eigenvector corresponding to the comparison importance of each indicator; The proportion calculation unit is used to calculate the proportion of the feature vector corresponding to the comparative importance of each indicator to the total feature vector for each indicator, so as to obtain the initial weight value of the indicator relative to the comprehensive evaluation indicator.

9. A computer device, characterized in that, include: A memory and a processor, wherein the memory stores a computer program that, when executed by the processor, implements the method for evaluating the frequency regulation performance of power grid load as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the evaluation method for power grid load frequency regulation performance as described in any one of claims 1-7.

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