An evaluation method for the active support control performance of an energy storage power station

Abstract

The present invention discloses a method for evaluating the active support control performance of an energy storage power station, including: S1: establishing an evaluation index system for the active support control performance of the energy storage power station to be evaluated; S2: obtaining the weight vector of the primary index; S3: obtaining the score S of the u-th primary index of the i-th energy storage power station to be evaluated ui ; S4: obtaining the active support control performance value PERF of the i-th energy storage power station to be evaluated; so as to evaluate the active support control performance of the energy storage power station to be evaluated. The present invention evaluates the active support control performance of the energy storage power station to be evaluated by calculating the active support control performance value of the energy storage power station to be evaluated. The evaluation result of the active support control performance of the energy storage power station to be evaluated is highly reliable, can play the multifunctional characteristics of electric energy storage, and provides a theoretical basis for electric energy storage to better play its due role in power grid operation. Therefore, it has important theoretical and practical significance

Description

Technical Field

[0001] The present invention relates to the technical field, and in particular to a method for evaluating the active support control performance of an energy storage power station. Background Art

[0002] In recent years, the construction of new energy has developed rapidly. However, due to the limited acceptance capacity of new energy, the phenomena of wind curtailment and light curtailment are serious. Moreover, with the global energy interconnection and mutual trust, the doping of various energy sources such as wind, light, water, heat, and hydrogen and the increasing complexity of the power grid structure have led to insufficient frequency regulation and voltage regulation capabilities in new energy-rich regions, showing characteristics of low inertia and weak damping. Energy storage can be used to make up for the lack of the active support ability of the power grid because of its fast response speed, capable of rapid charging and discharging, and capable of bidirectional regulation of active power and reactive power.

[0003] The active support function of an energy storage power station is to transform new energy from passive adaptation to actively supporting the safe and stable operation of the power grid, that is, when the grid parameters change, the energy storage power station takes active actions. The existing performance evaluation of the active support ability of energy storage power stations generally only considers the frequency regulation and voltage regulation scenarios, and does not comprehensively consider the inertia support and damping regulation scenarios. Due to the insufficient consideration of scenarios, the evaluation results of the active support of energy storage power stations are not accurate enough, and cannot fully reflect the actual active support ability of energy storage power stations. Therefore, there is an urgent need for a method for evaluating the active support control performance of energy storage power stations that can comprehensively consider the inertia support and damping regulation scenarios. Summary of the Invention

[0004] The present invention provides a method for evaluating the active support control performance of an energy storage power station to overcome the technical problems.

[0005] To achieve the above object, the technical solution of the present invention is as follows:

[0006] A method for evaluating the active support control performance of an energy storage power station includes the following steps:

[0007] S1: Establish an evaluation index system for the active support control performance of the energy storage power station to be evaluated; the evaluation index system for the active support control performance includes primary indicators and secondary indicators under each primary indicator;

[0008] S2: Obtain the weight vector of the primary indicators;

[0009] S3: According to the secondary indicators under the u-th primary indicator, obtain the score S of the u-th primary indicator of the i-th energy storage power station to be evaluated ui ; i is the number of the energy storage power station to be evaluated;

[0010] S4: According to the weight vector of the primary indicators and the score S of the u-th primary indicator of the i-th energy storage power station to be evaluated ui, obtain the active support control performance value PERF of the i-th energy storage power station to be evaluated, and evaluate the active support control performance of the energy storage power station to be evaluated.

[0011] Furthermore, the first-level indicators include dynamic voltage regulation, primary frequency regulation, inertia support, and damping regulation;

[0012] The second-level indicators under the dynamic voltage regulation index include voltage deviation, voltage fluctuation, voltage over-limit risk benefit, and maximum reactive power support capacity;

[0013] The second-level indicators under the primary frequency regulation index include: regulation rate, regulation accuracy, response time, frequency regulation mileage, and maximum output in response to primary frequency regulation;

[0014] The second-level indicators under the inertia support index include: rate of change of frequency RoCoF, minimum frequency f nadir , and maximum output in response to inertia support;

[0015] The second-level indicators under the damping regulation index include regulation time and rise time.

[0016] Furthermore, in S2, the steps to determine the weight vector of the first-level indicators are as follows:

[0017] S21: Assume that there is a criterion element C e in the network layer of ANP, e ∈ (1, 2,..., g), and for the f-th (f ≠ e) criterion element C f For the e-th criterion element C e the direct influence degree on the f-th criterion element C is y fe , where e and f are both the numbers of criterion elements; then obtain the initial judgment matrix Y as follows:

[0018]

[0019] In the formula: y ef represents the direct influence degree of the e-th (f ≠ e) criterion element C e on the f-th criterion element C f ;

[0020] S22: Compare the direct influence degrees of the g-th criterion element C g on the e-th criterion element C e pairwise, obtain the judgment matrix of the e-th criterion element C e , and obtain the judgment matrix of the e-th criterion element C e as follows:

[0021]

[0022] In the formula: Y e is the e-th criterion element Ce Judgment matrix;

[0023] S23: According to the judgment matrix Y e Solve the eigenvector to obtain the weight vector of the e-th criterion element C e as follows:

[0024]

[0025] In the formula: W e is the weight vector of the e-th criterion element C e ; represents the weight of the e-th criterion element C in the g-th column e ;

[0026] S24: According to the weight vector of the e-th criterion element C e , e ∈ (1, 2,..., g), obtain the direct influence matrix:

[0027]

[0028] In the formula: W d is the direct influence matrix;

[0029] S25: Obtain the limit value of the average comprehensive influence matrix as follows:

[0030]

[0031] In the formula, W lim represents the limit value of the average comprehensive influence matrix; T represents the cycle period; N represents the starting time of each cycle period; represents the limit value of the average comprehensive influence matrix at the starting point of the cycle; represents the limit value at the (T - 1)th moment within the cycle period;

[0032] S26: According to the limit value W of the average comprehensive influence matrix lim obtain the weighted supermatrix as follows:

[0033]

[0034] In the formula: represents the weighted supermatrix; A represents the weighted matrix; represents the element in the e-th row and f-th column of the weighted supermatrix;

[0035] S27: According to the weighted supermatrix, obtain the weight vector of the first-level index:

[0036]

[0037] In the formula: ω sIt represents the weight vector of the first-level indicators; k represents the number of times the weighted supermatrix is exponentiated.

[0038] Further, in S3, to obtain the score S of the u-th first-level indicator of the i-th energy storage power station to be evaluated ui The steps are as follows:

[0039] S31: Suppose there are q energy storage power stations to be evaluated in total, and there are p secondary indicators under the first-level indicator. i ∈ (1, 2,..., q), j ∈ (1, 2,..., p), then the original data matrix is:

[0040]

[0041] In the formula: X is the original data matrix; x ij is the data in the i-th row and j-th column of the original data matrix; j is the number of the secondary indicator in each first-level indicator; i is the number of the energy storage power station to be evaluated;

[0042] S32: Convert all secondary indicators into extremely large indicators:

[0043] Convert the extremely small indicators into extremely large indicators as follows. Among them, the extremely small indicators include voltage deviation, voltage fluctuation, voltage over-limit risk benefit, regulation rate, regulation accuracy, response time, frequency change rate, regulation time, and rise time;

[0044]

[0045] In the formula: is the extremely large indicator of the j-th secondary indicator; x j represents the j-th secondary indicator;

[0046] Convert the intermediate indicators into extremely large indicators as follows. Among them, the intermediate indicator is the minimum frequency f naidr ;

[0047]

[0048] In the formula: x best is the optimal value of the intermediate indicator; Score all the secondary indicators for positive normalization as follows:

[0049]

[0050] Obtain the positive normalization matrix:

[0051]

[0052] In the formula: x′ ij is the score of the positive normalization of the data in the i-th row and j-th column of the original data matrix; X’ is the positive normalization matrix;

[0053] S33: Standardize the matrix after forward transformation as follows:

[0054]

[0055] Obtain the standardized matrix

[0056]

[0057] where: z ij is the score after data standardization for the data in the i-th row and j-th column of the original data matrix; Z is the standardized matrix;

[0058] S34: Calculate the distance between the j-th secondary index in the i-th row and the optimal solution of the j-th secondary index and the distance between each secondary index in the i-th row and the worst solution of the j-th secondary index respectively, so as to obtain the distance between the i-th energy storage power station to be evaluated and the optimal solution and the distance between the i-th energy storage power station to be evaluated and the worst solution:

[0059]

[0060] where: is the distance between the i-th energy storage power station to be evaluated and the optimal solution; is the distance between the i-th energy storage power station to be evaluated and the worst solution; is the largest number in the j-th column, that is, the optimal solution of the j-th secondary index; is the smallest number in the j-th column, that is, the worst solution of the j-th secondary index;

[0061] S35: Obtain the score of the first-level index of the i-th energy storage power station to be evaluated as follows:

[0062]

[0063] where: S i represents the score of the first-level index of the i-th energy storage power station to be evaluated;

[0064] S36: According to S31 to S35, obtain the score S ui of the u-th first-level index of the i-th energy storage power station to be evaluated, where u is the serial number of the first-level index, u = 1 to U; U is the number of first-level indexes.

[0065] Furthermore, in S4, the method for evaluating the active support control performance of the energy storage power station to be evaluated is as follows:

[0066] Obtain the active support control performance value PERF of the i-th energy storage power station to be evaluated as follows:

[0067] PERF = [S 1i …S ui …SUi ·ω s (20)

[0068] When PERF ≥ P1, the active support control performance of the energy storage power station is excellent;

[0069] When P2 ≤ PERF < P1, the active support control performance of the energy storage power station is good;

[0070] When P3 ≤ PERF < P2, the active support control performance of the energy storage power station is medium;

[0071] When PERF < P3, the active support control performance of the energy storage power station is poor;

[0072] P1 is the excellent performance threshold, P2 is the good performance threshold, and P3 is the medium performance threshold; and P1 > P2 > P3.

[0073] Beneficial effects: An evaluation method for the active support control performance of an energy storage power station according to the present invention; an evaluation index system for the active support control performance is established, including primary indicators and secondary indicators that can reflect the support ability of the energy storage power station. By calculating the active support control performance value of the energy storage power station to be evaluated, the active support control performance of the energy storage power station to be evaluated is evaluated. The evaluation result of the active support control performance of the energy storage power station to be evaluated has high reliability, can play the multi-functional characteristics of electric energy storage, and provides a theoretical basis for the better play of the due role of electric energy storage in power grid operation. Therefore, it has important theoretical and practical significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0075] Figure 1 It is a flowchart of the active support control performance evaluation method of the present invention.

[0076] Figure 2 It is a flowchart for determining the primary index vector of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0077] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0078] This embodiment provides a method for evaluating the active support control performance of an energy storage power station, including the following steps: as Figure 1 shown:

[0079] Specifically, in view of the deficiencies in the evaluation ability of the active support control performance of existing energy storage power stations, this embodiment proposes an evaluation method that can comprehensively consider from four aspects: primary frequency regulation performance, dynamic voltage regulation performance, inertia support performance, and damping regulation performance, and evaluate the active support control ability of the energy storage power station from all-round and multi-angle perspectives.

[0080] S1: Establish an evaluation index system for the active support control performance of the energy storage power station to be evaluated; the evaluation index system for the active support control performance includes primary indicators and secondary indicators under each primary indicator;

[0081] Preferably, the secondary indicators under the primary indicators include dynamic voltage regulation, primary frequency regulation, inertia support, and damping regulation; the secondary indicators under the dynamic voltage regulation index include voltage deviation, voltage fluctuation, voltage over-limit risk benefit, and maximum reactive power support ability; the secondary indicators under the primary frequency regulation index include: regulation rate, regulation accuracy, response time, frequency regulation mileage, and maximum output power in response to primary frequency regulation; the secondary indicators under the inertia support index include: rate of change of frequency RoCoF, minimum frequency f nadir , maximum response inertia support; the secondary indicators under the damping regulation index include regulation time and rise time.

[0082] Specifically, in terms of the dynamic voltage regulation index, it is proposed to use voltage deviation, voltage fluctuation, voltage over-limit risk benefit, and maximum reactive power support ability as secondary indicators: the difference between the actual voltage and the system nominal voltage is called voltage deviation, and the smaller the voltage deviation, the better the voltage regulation effect of the energy storage; voltage fluctuation refers to the rapid change of the effective value of the grid voltage, and the faster the energy storage voltage regulation response, the smaller the voltage fluctuation; when the operating voltage of the bus in the power grid deviates from the allowable range of the voltage of each voltage level, it is easy to cause damage to the user's electrical equipment and affect the sensitivity of the relay protection devices of each voltage level. Therefore, the voltage over-limit risk benefit is used to represent the voltage regulation effect of the energy storage. The energy storage reduces the operating voltage by emitting reactive power, thereby reducing the voltage over-limit risk; the greater the reactive power support ability of the energy storage, the faster the voltage recovery. Therefore, the maximum reactive power support ability is used to represent the voltage regulation effect of the energy storage.

[0083] In terms of the primary frequency regulation index, it is proposed to use the regulation rate, regulation accuracy, response time, frequency regulation mileage, and maximum output of the first response to primary frequency regulation as secondary indicators; the regulation rate refers to the speed at which the energy storage power station responds to the frequency regulation command. The faster the frequency regression speed, the better the regulation performance of the energy storage power station; the regulation accuracy refers to the degree of difference between the final actual output of the energy storage power station and the regulation command value. The smaller the difference, the better the performance; the response time refers to the time required for the energy storage power station to start regulating its output from receiving the regulation command. The smaller the response time, the better the response performance; the frequency regulation mileage reflects the actual contribution of the energy storage power station to frequency regulation within the dispatching cycle; the greater the output of the energy storage for primary frequency regulation, the better the frequency recovery effect. Therefore, the maximum output of the first response to primary frequency regulation is used to evaluate the effect of the energy storage participating in primary frequency regulation.

[0084] For inertia support, the rate of change of frequency RoCoF and the minimum frequency f nadir are proposed as evaluation indicators, as well as the maximum output of the response to inertia support. Low inertia increases the rate of change of frequency RoCoF, and a large RoCoF can lower the lowest point of the frequency. Therefore, RoCoF and f nadir are used to evaluate the effect of inertia support; to give full play to the inhibitory effect of the energy storage power station on the rate of change of frequency in inertial control, the greater the inertia support output of the energy storage, the stronger the inhibitory effect. Therefore, the maximum output of the response to inertia support is used to evaluate the effect of inertia support.

[0085] For damping regulation, the regulation time and rise time are used to characterize the impact of the energy storage power station on the grid damping characteristics after being connected. Since the damping coefficient determines the rate of oscillation decay during the dynamic response process, the regulation time and rise time of the active power and reactive power output of the virtual synchronous generator formed by introducing the energy storage during the dynamic process are used to evaluate the damping regulation ability of the energy storage power station.

[0086] In this embodiment, the primary index divides the active support function into four major working conditions, making up for the defect of only considering frequency modulation and voltage regulation before. The secondary indicators are constructed based on the first-level indicators and the calculation formulas are set, enabling the primary indicators to be quantified. By setting two-level indicators for active support ability assessment, the ability of the energy storage power station under active support conditions can be fully reflected. The specific evaluation system for the active support control performance is shown in Table 1:

[0087] Table 1 Comprehensive evaluation index system

[0088]

[0089]

[0090] Specifically, the voltage deviation is as follows:

[0091]

[0092] Where: ΔU is the percentage of voltage deviation, U is the actual voltage, and U N is the nominal grid voltage;

[0093] The voltage fluctuation is:

[0094]

[0095] Where: n is the number of fluctuations within the fluctuation time T, and n bad is the number of times the voltage fluctuation exceeds 1% per unit time.

[0096] The voltage over - limit risk benefit is:

[0097] ΔR = Risk(n) - Risk(n′)

[0098]

[0099] Where: ΔR represents the voltage over - limit risk benefit; P(v l ) represents the probability of the l - th bus experiencing a fluctuation; S(v l ) represents the power supply loss of the l - th bus; l is the bus number; Risk(n′) is the voltage over - limit operation risk after reactive power compensation by energy storage, and Risk(n) is the original voltage over - limit operation risk;

[0100] The maximum reactive power support capacity is:

[0101]

[0102] Where, η s is the maximum reactive power support capacity; Q sfact is the actual reactive power output when the voltage is at the stable margin, and Q lim is the theoretical reactive power reserve;

[0103] The regulation rate is:

[0104]

[0105] Where, is the regulation rate; is the regulation rate of the i - th energy storage power station, is the regulation command value of the i - th energy storage power station; is the initial power value of the i - th energy storage power station when participating in regulation; v N is the standard regulation speed; i is the number of the energy storage power station;

[0106] The regulation accuracy is:

[0107]

[0108] In the formula, is the adjustment accuracy; is the adjustment error; ΔP N is the standard adjustment error;

[0109] The response time is the time when the energy storage power station reaches 90% of the expected power change after the power grid frequency stabilizes during the primary frequency regulation process of the energy storage power station;

[0110] The frequency regulation mileage is:

[0111]

[0112] In the formula, R M is the frequency regulation mileage; R t is the actual output under the dispatching instruction t; m is the total number of dispatching instructions within the evaluation period; t is the number of the dispatching instruction;

[0113] The maximum output for responding to primary frequency regulation is:

[0114]

[0115] In the formula, P ess1 is the maximum output for responding to primary frequency regulation; b1 is the virtual droop control task coefficient in the primary frequency regulation stage; b2 is the virtual negative inertia control task coefficient in the primary frequency regulation stage;

[0116] Where: when Δf≥0

[0117]

[0118] When Δf<0,

[0119]

[0120] In the formula: Δf is the frequency deviation; Δf max is the maximum frequency deviation; f b is the abscissa of the initial intersection point of b1 and b2, f b =ln 3 / (20n2); n2 is the shape parameter of the task coefficient change curve in the primary frequency regulation stage;

[0121] The rate of change of frequency RoCoF is:

[0122]

[0123] In the formula, ω(t) is the angular frequency at the current moment;

[0124] The lowest frequency f nadir is solved using the response time model. The energy storage system can quickly make charge and discharge reactions. Therefore, the lowest frequency f nadiris:

[0125]

[0126] In the formula: S B,sys is the system base capacity; r p is the power growth rate; Δf DB is the dead - band frequency; M sys is the total system inertia level; f0 is the system nominal frequency; ΔP L = P m0 - P e0 is the unbalanced power value, affected by the mechanical power P m0 and the electromagnetic power P e0 at this moment.

[0127] The calculation formula for the maximum output of the responsive inertia support is:

[0128]

[0129] Among them:

[0130] In the formula: a1 is the virtual droop control task coefficient in the inertia response stage; a2 is the virtual inertia control task coefficient in the inertia response stage; Δf is the frequency deviation; n1 is the shape parameter of the task coefficient change curve in the virtual inertia stage, K ess is the unit regulation power of the virtual droop control; is the unit regulation power of the virtual inertia control; dΔf / dt is the system frequency deviation change rate.

[0131] The regulation time is the shortest time experienced until the active and reactive powers output by the virtual synchronous generator return to within ±5% (±2%) of the original steady - state value and no longer exceed it during the dynamic process after the energy storage system is introduced to form the virtual synchronous generator.

[0132] The rise time is the time required for the active and reactive powers output by the virtual synchronous generator to rise from 10% of the steady - state value to 90% of the steady - state value during the dynamic process.

[0133] S2: Obtain the weight vector of the first - level indicators:

[0134] Specifically, when comprehensively evaluating the active support control performance of an energy storage power station, since the energy storage power station needs to fully consider the demands of new energy-rich areas when providing active support functions, the subjective weighting method is used to determine the weights of the first-level indicators. Combining the advantages of DEMATEL (Decision Making Trial and Evaluation Laboratory), DEMATEL-ANP (Analytic Network Process based on Decision Making Trial and Evaluation Laboratory) is used to determine the weights of the first-level indicators. Since the second-level indicators are independent of each other and each second-level indicator can be quantified, the TOPSIS method is used when assigning weights to the second-level indicators.

[0135] The steps for determining the weight vector of the first-level indicators are as follows, as Figure 2 shown:

[0136] S21: Suppose there are criterion elements C e , e ∈ (1, 2,..., g) in the network layer of ANP (the network layer in the Analytic Network Process based on Decision Making Trial and Evaluation Laboratory). For the fth (f ≠ e) criterion element C f The direct influence degree on the eth criterion element C e is y fe , where both e and f are the numbers of the criterion elements. Then the initial judgment matrix Y is obtained as follows: where y fe is obtained according to the experts' scoring based on their own experience;

[0137]

[0138] In the formula: y gg represents the direct influence degree of C g on C g ;

[0139] S22: Compare the direct influence degrees of the gth criterion element C g on the eth criterion element C e pairwise to obtain the judgment matrix of the eth criterion element C e , that is, obtain the judgment matrix of the eth criterion element C e according to the sub-criteria as follows:

[0140]

[0141] In the formula: Y e is the judgment matrix of the eth criterion element C e ;

[0142] S23: Solve the eigenvector according to the eigenvalue method for the judgment matrix Y e to obtain the weight vector of the eth criterion element C e as follows: Among them, according to the eigenvalue method for the judgment matrix Y eSolving eigenvectors is a common technique in the field, so it will not be described in detail here.

[0143]

[0144] In the formula: W e is the weight vector of the e-th criterion element C e ; represents the weight of the e-th criterion element C e in the g-th column;

[0145] S24: According to the weight vector of the e-th criterion element C e , e ∈ (1, 2,..., g), combine all weight vectors into a weight matrix to obtain the direct influence matrix in the DEMATEL method:

[0146]

[0147] In the formula: W d is the direct influence matrix of the DEMATEL method;

[0148] S25: Obtain the limit value of the average comprehensive influence matrix as follows:

[0149]

[0150] Specifically, when there are multiple limit values for the average comprehensive influence matrix, the average comprehensive influence matrix shows periodic changes. Take the average value of the starting time of the cycle period to obtain the limit value of the average comprehensive influence matrix:

[0151]

[0152] In the formula, W lim represents the limit value of the average comprehensive influence matrix; T represents the cycle period; N represents the starting time of each cycle period; represents the limit value of the average comprehensive influence matrix at the starting point of the cycle; represents the limit value at the (T - 1)th moment within the cycle period;

[0153] S26: According to the limit value W lim of the average comprehensive influence matrix, obtain the weighted supermatrix as follows:

[0154]

[0155] In the formula: represents the weighted supermatrix; A represents the weighted matrix; represents the element in the e-th row and f-th column of the weighted supermatrix;

[0156] S27: Obtain the weight vector of the first-level indicators according to the weighted supermatrix:

[0157]

[0158] where: ω s represents the weight vector of the first-level indicators; k represents the number of powers of the weighted supermatrix;

[0159] S3: Obtain the score S of the u-th first-level indicator of the i-th energy storage power station to be evaluated ui , where u is the serial number of the first-level indicator, u = 1~U; U is the number of first-level indicators; i is the number of the energy storage power station to be evaluated;

[0160] Specifically, in this embodiment, according to the TOPSIS method (Technique for Order Preference by Similarity to an Ideal Solution), that is, the objective assignment method, determine the score of each first-level indicator;

[0161] S31: Suppose there are q energy storage power stations to be evaluated, and there are p secondary indicators under the first-level indicator of dynamic voltage regulation, i ∈ (1, 2... q), j ∈ (1, 2... p), then the original data matrix is:

[0162]

[0163] where: X is the original data matrix; x ij is the data in the i-th row and j-th column of the original data matrix (i.e., the j-th secondary indicator of the i-th energy storage power station to be evaluated); j is the serial number of the secondary indicator in each first-level indicator; i is the number of the energy storage power station to be evaluated;

[0164] S32: Since the orders of magnitude of the secondary indicators are different, they need to be converted into the same range. Therefore, it is necessary to perform positive normalization on the indicators, that is, convert the extremely small and intermediate indicators into extremely large indicators. Whether each indicator is an extremely large indicator is determined by the nature of the indicator itself. An indicator with a larger value being better is called an extremely large indicator, an indicator with a smaller value being better is called an extremely small indicator, and an indicator with a value closer to a certain value being better is called an intermediate indicator. In this embodiment, the extremely large indicators include the maximum reactive power support capacity, frequency modulation mileage, maximum output power in response to primary frequency modulation, and maximum output power in response to inertia support. Convert the extremely small and intermediate indicator secondary indicators into extremely large indicators:

[0165] The extremely small indicators include voltage deviation, voltage fluctuation, voltage over-limit risk and return, regulation rate, regulation accuracy, response time, frequency change rate, regulation time, and rise time;

[0166] Convert the extremely small indicators, namely voltage deviation, voltage fluctuation, voltage over-limit risk and return, regulation rate, regulation accuracy, response time, frequency change rate, regulation time, and rise time, into extremely large indicators as follows:

[0167]

[0168] Wherein: is the extremely large index of the j-th secondary index; x j represents the j-th secondary index;

[0169] The intermediate index, i.e., the lowest frequency f naidr is transformed into an extremely large index as follows: Specifically, the optimal value of the lowest frequency f naidr is the power grid frequency of 50 Hz;

[0170]

[0171] Wherein: x best is the optimal value of the intermediate index; The positive scoring of all secondary indices is as follows:

[0172]

[0173] The positive matrix is obtained:

[0174]

[0175] Wherein: x′ ij is the score of the positive scoring of the data in the i-th row and j-th column of the original data matrix (i.e., the score of the positive scoring of the j-th secondary index of the i-th energy storage power station to be evaluated); X’ is the positive matrix;

[0176] S33: The standardized processing of the positive matrix is as follows:

[0177]

[0178] The standardized matrix is obtained

[0179]

[0180] Wherein: z ij is the score after the standardized processing of the data in the i-th row and j-th column of the original data matrix (i.e., the score after the standardized processing of the j-th secondary index of the i-th energy storage power station to be evaluated); Z is the standardized matrix;

[0181] S34: Take the largest number in the j-th column as the optimal solution of the j-th secondary index, denoted as That is, it is used as the optimal solution of the j-th secondary index, and the smallest number in the j-th column is used as the worst solution of the j-th secondary index, denoted as That is, as the worst solution of the j-th secondary index, calculate the distance between the j-th secondary index in the i-th row and the optimal solution of the j-th secondary index, and the distance between each secondary index in the i-th row and the worst solution of the j-th secondary index, so as to obtain the distance between the i-th energy storage power station to be evaluated and the optimal solution and the distance between the i-th energy storage power station to be evaluated and the worst solution:

[0182]

[0183] In the formula: is the distance between the i-th energy storage power station to be evaluated and the optimal solution; is the distance between the i-th energy storage power station to be evaluated and the worst solution; is the largest number in the j-th column, that is, the optimal solution of the j-th secondary index; is the smallest number in the j-th column, that is, the worst solution of the j-th secondary index;

[0184] S35: Obtain the score of the first-level index of the i-th energy storage power station to be evaluated as follows:

[0185]

[0186] In the formula: S i represents the score of the first-level index of the i-th energy storage power station to be evaluated;

[0187] S36: According to S31-S35, obtain the score S ui of the u-th first-level index of the i-th energy storage power station to be evaluated, where u is the serial number of the first-level index, u = 1-U; U is the number of first-level indexes;

[0188] S4: According to the weight vector of the first-level index and the score S ui of the u-th first-level index of the i-th energy storage power station to be evaluated, obtain the active support control performance value PERF of the i-th energy storage power station to be evaluated; to evaluate the active support control performance of the energy storage power station to be evaluated;

[0189] In S4, the method for evaluating the active support control performance of the energy storage power station to be evaluated is as follows:

[0190] Obtain the active support control performance value PERF of the i-th energy storage power station to be evaluated as follows:

[0191] PERF = [S 1i …S ui …S Ui ·ω s (20)

[0192] When PERF≥P1, the active support control performance of the energy storage power station is excellent;

[0193] When P2 ≤ PERF < P1, the active support control performance of the energy storage power station is good;

[0194] When P3 ≤ PERF < P2, the active support control performance of the energy storage power station is medium;

[0195] When PERF < P3, the active support control performance of the energy storage power station is poor;

[0196] Among them, P1 is the excellent performance threshold, P2 is the good performance threshold, and P3 is the medium performance threshold; and P1 > P2 > P3.

[0197] Specifically, in this embodiment, there are 4 primary indicators, so u = 1 to 4; the dynamic voltage regulation indicators S 1i 、S 2i 、S 3i 、S 4i of the i-th energy storage power station to be evaluated are calculated;

[0198] Therefore, PERF = [S 1i S 2i S 3i S 4i ·ω s ;

[0199] P1, P2, and P3 are determined according to expert evaluation. In this embodiment, P1 = 90; P2 = 70; P3 = 60.

[0200] This embodiment fully considers the active support functions of inertia support and damping regulation, conducts research on the comprehensive evaluation method of the active support ability of the energy storage power station, and through the primary indicators including primary frequency modulation, inertia support, damping regulation, and dynamic voltage regulation, it can play the multifunctional characteristics of electric energy storage and provide a theoretical basis for electric energy storage to better play its due role in power grid operation. Therefore, it has important theoretical and practical significance.

[0201] Beneficial effects:

[0202] 1. An evaluation index system for the active support control performance of the energy storage power station is established; and it is divided into primary indicators and secondary indicators. The secondary indicators can reflect the active support control performance of the energy storage power station. Therefore, the evaluation index system of the present invention has excellent effects in reflecting the active support control performance of the energy storage power station to be evaluated.

[0203] 2. At the same time, a calculation method for the weight of the active support control performance index of the energy storage power station is proposed: adopting a combination of subjective and objective methods, the weight vectors of the active support control performance index system of the new energy power station equipped with the energy storage power station are calculated respectively, thus combining the advantages of subjective and objective weight calculations.

[0204] 3. The secondary indicators under damping regulation are proposed, which can reflect the damping regulation ability of the energy storage power station by using the regulation time and rise time of the active and reactive power output by the virtual synchronous generator during the dynamic process.

[0205] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the active support control performance of an energy storage power station, characterized in that, It includes the following steps: S1: Establish an evaluation index system for the active support control performance of the energy storage power station to be evaluated; the evaluation index system for the active support control performance includes primary indicators and secondary indicators under each of the primary indicators; The primary indicators include dynamic voltage regulation, primary frequency regulation, inertia support, and damping regulation; The secondary indicators under the dynamic voltage regulation index include voltage deviation, voltage fluctuation, voltage over-limit risk-benefit, and maximum reactive power support capacity; The secondary indicators under the primary frequency regulation index include: regulation rate, regulation accuracy, response time, frequency regulation mileage, and maximum output of the first response to primary frequency regulation; The secondary indicators under the inertia support index include: Rate of Change of Frequency (RoCoF), minimum frequency f nadir , and maximum output of response inertia support; The secondary indicators under the damping regulation index include regulation time and rise time; S2: Obtain the weight vector of the primary indicators; The calculation formula for the weight vector of the primary indicators is as follows: where: ω s represents the weight vector of the first-level index; k represents the number of powers of the weighted supermatrix; represents the weighted supermatrix; S3: Obtain the score S of the u-th first-level index of the i-th energy storage power station to be evaluated according to the second-level index under the u-th first-level index ui ; i is the number of the energy storage power station to be evaluated S4: Obtain the active support control performance value PERF of the i-th energy storage power station to be evaluated according to the weight vector of the first-level indicators and the score S of the u-th first-level indicator of the i-th energy storage power station to be evaluated, so as to evaluate the active support control performance of the energy storage power station to be evaluated. ui Here, the active support control performance of the energy storage power station to be evaluated is evaluated.

2. According to the method for evaluating the active support control performance of an energy storage power station described in claim 1, wherein, In S2, the steps for determining the weight vector of the primary indicators are as follows: S21: Assume that there is a criterion element C in the network layer of ANP e , e ∈ (1, 2,..., g), the f-th criterion element C f For the e-th criterion element C e The direct influence degree is y fe , where both e and f are the numbers of criterion elements; then obtain the initial judgment matrix Y as follows: where: y ef represents the direct influence degree on the e-th criterion element C e for the f-th criterion element C f , where f ≠ e; S22: Compare the direct influence degrees of the g-th criterion element C pairwise, obtain the judgment matrix of the e-th criterion element C g For the e-th criterion element C e to obtain the judgment matrix of the e-th criterion element C e The judgment matrix of the e-th criterion element C e is as follows: where: Y e is the judgment matrix of the e-th criterion element C e ; S23: According to the judgment matrix Y e Solve the eigenvector to obtain the weight vector of the e-th criterion element C e as follows: Where: W e is the weight vector of the e-th criterion element C e ; represents the weight of the e-th criterion element C e in the g-th column; S24: Obtain the direct influence matrix according to the weight vector of the e-th criterion element C e , where e ∈ (1, 2,..., g): Where: W d is the direct influence matrix; S25: Obtain the limit value of the average comprehensive influence matrix as follows: where, W lim represents the limit value of the average comprehensive influence matrix; T represents the cycle period; N represents the starting time of each cycle period; represents the limit value of the average comprehensive influence matrix at the starting point of the cycle; represents the limit value at the (T-1)th moment within the cycle period; S26: Obtain the weighted supermatrix according to the limit value W of the average comprehensive impact matrix lim The weighted supermatrix is obtained as follows: In the formula: represents the weighted supermatrix; A represents the weighted matrix; represents the element in the e-th row and f-th column of the weighted supermatrix; S27: According to the weighted supermatrix, obtain the weight vector of the primary indicators.

3. The active support control performance evaluation method for an energy storage power station according to claim 2, characterized in that, In S3, obtain the score S of the u-th first-level index of the i-th energy storage power station to be evaluated ui The steps are as follows: S31: Assume that there are q energy storage power stations to be evaluated, and there are p secondary indicators under the primary indicators. i ∈ (1, 2,..., q), j ∈ (1, 2,..., p), then the original data matrix is: Where: X is the original data matrix; x ij is the data at the i-th row and j-th column in the original data matrix; j is the number of the secondary index in each primary index; i is the number of the energy storage power station to be evaluated; S32: Convert all secondary indicators into extremely large type indicators: Convert the extremely small type indicators into extremely large type indicators as follows: Among them, the extremely small type indicators include voltage deviation, voltage fluctuation, voltage over-limit risk-benefit, regulation rate, regulation accuracy, response time, frequency change rate, regulation time, and rise time; In the formula: is the positive indicator of the j-th secondary indicator; x j represents the j-th secondary indicator; Convert the intermediate-type index into a positive-type index as follows: where the intermediate-type index is the minimum frequency f naidr ; where: x best is the optimal value of the intermediate index; The positive scoring of all secondary indexes is as follows: Obtain the positive matrix: where: x′ ij is the score of the positive scoring of the data in the i-th row and j-th column of the original data matrix; X’ is the positive matrix; S33: Standardize the positive matrix as follows: Obtain the standardized matrix where: z ij is the score after data standardization processing for the data in the i-th row and j-th column of the original data matrix; Z is the standardized matrix; S34: Calculate the distance between the j-th secondary indicator in the i-th row and the optimal solution of the j-th secondary indicator and the distance between each secondary indicator in the i-th row and the worst solution of the j-th secondary indicator respectively, so as to obtain the distance between the i-th energy storage power station to be evaluated and the optimal solution and the distance between the i-th energy storage power station to be evaluated and the worst solution; Wherein: is the distance between the i-th energy storage power station to be evaluated and the optimal solution; is the distance between the i-th energy storage power station to be evaluated and the worst solution; is the largest number in the j-th column, i.e., the optimal solution of the j-th secondary index; is the smallest number in the j-th column, i.e., the worst solution of the j-th secondary index; S35: Obtain the score of the primary indicators of the i-th energy storage power station to be evaluated as follows: Where: S i represents the score of the first-level index of the i-th energy storage power station to be evaluated; S36: Obtain the score S of the u-th first-level indicator of the i-th energy storage power station to be evaluated according to S31 to S35 ui , where u is the serial number of the first-level indicator, u = 1 to U; U is the number of first-level indicators.

4. The active support control performance evaluation method for an energy storage power station according to claim 3, wherein In S4, the method for evaluating the active support control performance of the energy storage power station to be evaluated is as follows: Obtain the active support control performance value PERF of the i-th energy storage power station to be evaluated as follows: PERF = [S 1i … S ui … S Ui ·ω s (20) When PERF ≥ P1, the active support control performance of the energy storage power station is excellent; When P2 ≤ PERF < P1, the active support control performance of the energy storage power station is good; When P3 ≤ PERF < P2, the active support control performance of the energy storage power station is medium; When PERF < P3, the active support control performance of the energy storage power station is poor; P1 is the excellent performance threshold, P2 is the good performance threshold, and P3 is the medium performance threshold; and P1 > P2 > P3.

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