A new energy station active support control performance evaluation method and system

Abstract

The application relates to a new energy station active support control performance evaluation method, which comprises the following steps: determining a first index of a new energy station active support control performance index system configured with energy storage, and constructing a second index based on the first index; determining the weights of the first index and the second index, calculating a new energy station active support control performance value based on the weight values of the first index and the second index, and realizing new energy station active support control performance evaluation. The application can reflect the active support capability of the new energy station and has a high credibility.

Description

Technical Field

[0001] This application relates to the field of active support control technology for new energy power stations, and in particular to a method and system for evaluating the performance of active support control for new energy power stations. Background Technology

[0002] The new mandatory national standard "Guidelines for the Safety and Stability of Power Systems" (GB 38755-2019) came into effect on July 1, 2020. This standard requires renewable energy power plants to have flexible regulation capabilities such as primary frequency regulation, rapid voltage regulation, and peak shaving. However, relying solely on the self-regulation capabilities of renewable energy units to achieve functions such as frequency regulation and voltage regulation will lead to power-limited operation of renewable energy units, resulting in problems such as wind and solar curtailment, which will affect the efficiency of renewable energy power generation.

[0003] With the increasing proportion of renewable energy, thermal power units can no longer meet the demand for flexible regulation. Since energy storage has the capability for rapid operation in four quadrants, configuring energy storage in renewable energy power plants can achieve the flexible regulation capabilities required by national standards. However, evaluating the active support function of renewable energy power plants equipped with energy storage requires multiple levels and aspects of indicators to quantify the active support capability. Currently, there is no established evaluation mechanism or universally accepted assessment method for evaluating the active support control capability of energy storage in renewable energy power plants.

[0004] Therefore, how to provide a method for evaluating the active support control performance of new energy power plants is an urgent problem to be solved. Summary of the Invention

[0005] This application provides a method for evaluating the active support control performance of new energy power stations, addressing the problem that existing technologies lack a corresponding evaluation mechanism for assessing the ability of energy storage to participate in active support control. To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments. Its sole purpose is to present some concepts in a simple form as a prelude to the detailed description that follows.

[0006] Firstly, this application provides a method for evaluating the active support control performance of a new energy power station, comprising the following steps:

[0007] The primary indicators of the active support control performance index system for new energy power stations with energy storage configuration are determined, and secondary indicators are constructed based on the primary indicators;

[0008] The weights of the primary and secondary indicators are determined, and the active support control performance values ​​of the new energy power stations are calculated based on the weight values ​​of the primary and secondary indicators to achieve the evaluation of the active support control performance of the new energy power stations.

[0009] Optionally, the primary indicators include one or more of the following: dynamic voltage regulation indicators, primary frequency regulation indicators, inertia support indicators, and / or damping adjustment indicators.

[0010] Optionally, the dynamic voltage regulation index includes a voltage qualification rate index and a maximum voltage state perception index.

[0011] Optionally, the formula for calculating the voltage qualification rate index is:

[0012]

[0013] Among them: U qualified For voltage qualification rate, U over For voltage exceeding the power supply / consumption limit, U all Percentage of total electricity supply / consumption;

[0014] The calculation formula for the maximum voltage state sensing is as follows:

[0015]

[0016]

[0017]

[0018] Where: γ1(t) is the severity index of voltage drop duration, γ2(t) is the severity index of voltage drop amplitude, and T d (t) represents the duration of the voltage drop, T min T max These represent the minimum and maximum values ​​of the voltage sag duration, respectively; U(t) is the real-time voltage value at the grid connection point; U max U min U lim These are the upper interval value of the steady-state voltage range, the lower interval value of the steady-state voltage range, and the critical voltage value for voltage collapse, respectively.

[0019] Optionally, the primary frequency regulation indicators include the root mean square value of frequency deviation, the primary frequency regulation control performance evaluation indicators, and the input status evaluation indicators.

[0020] Optionally, the formula for calculating the root mean square value of the frequency deviation index is:

[0021]

[0022] Where: f i N represents the frequency sample value at the i-th point; c f represents the total number of sampling points; B The reference frequency for the power grid is 50Hz, which is selected here. resultThe root mean square value of the frequency deviation is an indicator that represents the effectiveness of frequency adjustment.

[0023] The calculation formula for the primary frequency modulation control performance evaluation index is as follows:

[0024]

[0025] Where T is the evaluation period, and ΔP Gt With ΔP St These are the calculated and sampled values ​​of the power change at time t, respectively, for the primary frequency modulation.

[0026] The evaluation formula for the aforementioned input evaluation indicators is as follows:

[0027]

[0028] Where, N P.Cq To evaluate the number of qualified points for the input performance indicator Cq within a given time period, N S.Cq Indicator C for evaluating input during the evaluation period q Total points.

[0029] Optionally, the inertia support indicators include the frequency drop minimum point indicator, the power grid frequency damping effect indicator, the weak grid stability evaluation indicator, the power grid frequency secondary drop evaluation indicator, and the joint inertia constant indicator.

[0030] Optionally, the formula for calculating the frequency drop minimum point index is as follows:

[0031]

[0032] Wherein: S B，sys The system baseline capacity is represented by rp, and the power growth rate is represented by Δf. DB M is the dead zone frequency; sys The system's total inertia level; f B The reference frequency for the power grid is set at 50Hz; ΔP L =P m0 -P e0 That is, unbalanced power, P m0 For mechanical power, P e0 Electromagnetic power;

[0033] The formula for calculating the power grid frequency damping effect index is as follows:

[0034]

[0035] Where, Δf max f is the maximum value of the change in grid frequency during the dynamic process; B The reference value for the power grid frequency is 50Hz, which is selected here.

[0036] The formula for calculating the power grid frequency second sag index is as follows:

[0037]

[0038] Where, Δf 2_max f is the maximum deviation value of the second frequency drop in the power grid. B The reference value for the power grid frequency is 50Hz, which is selected here.

[0039] The formula for calculating the joint inertia constant index is as follows:

[0040]

[0041] Wherein: S NEW For the rated capacity of new energy power stations, E ESS E provides energy to the energy storage system. NEW The energy provided by the renewable energy power station, J is the moment of inertia of the renewable energy power station, ω s This is the system's synchronous speed.

[0042] Optionally, the damping adjustment index includes a settling time index and a rise time index.

[0043] Optionally, the adjustment time index is the shortest time it takes for the output active and reactive power of the virtual synchronous generator to recover from the original steady state to within ±2% to ±5% of the new steady state value in the dynamic process after the energy storage system is introduced to form a virtual synchronous generator, and then no longer exceeds this range.

[0044] The rise time metric is the time required for the output active and reactive power of the virtual synchronous generator to rise from 10% of the steady-state value to 90% of the steady-state value during a dynamic process.

[0045] Optionally, the determination of the weights of the primary indicators adopts a network analysis method based on decision laboratories, which includes the following steps:

[0046] Suppose that there are criterion elements in the network layer of the network analysis method. The degree of direct influence between each pair of criterion elements is used as matrix elements to obtain the initial judgment matrix.

[0047] The degree of direct influence of the remaining elements in the network layer, excluding the criterion element, on the criterion element is compared pairwise, that is, the corresponding judgment matrix is ​​obtained according to the secondary criterion.

[0048] The weight vectors under the secondary criteria are obtained by using the eigenvalue method, and the weight vectors under all the secondary criteria are combined into a weight matrix to obtain the direct influence matrix in decision experiment and evaluation experiment methods.

[0049] Calculate the average comprehensive influence matrix of the direct influence matrix. When the limit of the comprehensive influence weight matrix is ​​unique, the limit of the comprehensive influence weight matrix is ​​determined as the limit value of the average comprehensive influence matrix. When there are multiple limit values, the matrix exhibits periodic changes, and the average value of each limit point is taken as the limit value of the average comprehensive influence matrix.

[0050] Calculate the weighted hypermatrix using the limiting value of the average comprehensive influence matrix;

[0051] Repeat the above steps 2k+1 times to evolve the weighted supermatrix 2k+1 times, forming a long-term stable matrix and obtaining the weight vectors of each first-level index, where k is a natural number.

[0052] Optionally, the method for determining the primary indicator further includes the following steps:

[0053] Establish the original data matrix of the secondary indicators, determine the maximum index of each secondary indicator, and positively process the remaining secondary indicators into maximum indexes, so that the order of magnitude of all secondary indicators is within the same range.

[0054] The standard deviation is used to represent the comparison of a certain indicator and to determine the degree of contradiction between that indicator and the other indicators.

[0055] The dynamic voltage regulation index, primary frequency regulation index, inertia support index, and damping adjustment index are calculated sequentially using the information carrying capacity.

[0056] Optionally, the formula for calculating the active support control performance value of the new energy power station is as follows:

[0057]

[0058] Among them, PERF represents the active support control performance value of the new energy power station, S si ω represents the calculated value of the primary indicator. s This represents the weight vector of each primary indicator.

[0059] Optionally, when the active support control performance value of the new energy power station is greater than or equal to P1, the active support control performance of the new energy power station is excellent.

[0060] When the active support control performance value of the new energy power station is greater than or equal to P2 and less than P1, the active support control performance of the new energy power station is good.

[0061] When the active support control performance value of the new energy power station is greater than or equal to P3 and less than P2, the active support control performance of the new energy power station is medium.

[0062] When the active support control performance value of the new energy power station is less than P3, the active support control performance of the new energy power station is poor.

[0063] Among them, P1 and P3 are the comprehensive score thresholds, and P1 > P2 > P3.

[0064] Secondly, this application provides a performance evaluation system for active support control of new energy power stations, including a preset module and a calculation module, wherein:

[0065] The preset module is used to determine the primary indicators of the active support control performance index system of the new energy power station with energy storage configuration, and to construct secondary indicators based on the primary indicators.

[0066] The calculation module is used to determine the weights of the primary and secondary indicators, and based on the weights of the primary and secondary indicators, calculate the active support control performance value of the new energy power station according to the steps in the active support control performance evaluation method for new energy power stations described above, thereby realizing the active support control performance evaluation of new energy power stations.

[0067] Thirdly, this application provides a medium on which a program is stored, which, when executed by a processor, implements the steps in the active support control performance evaluation method for new energy power stations as described in any of the preceding claims.

[0068] Fourthly, this application provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the above-mentioned active support control performance evaluation method for new energy power stations.

[0069] The technical solutions provided in this application embodiment may include the following beneficial effects:

[0070] (1) Construct an evaluation index system for the active support capability of new energy power stations, and divide it into primary and secondary indicators in the active support evaluation index system, which can reflect the active support capability of new energy power stations.

[0071] (2) The weights of the primary and secondary indicators in the active support capability of new energy power stations were considered respectively, so that the evaluation results of the active support capability of new energy power stations have a high degree of credibility.

[0072] (3) The evaluation results of the active support capability of new energy power stations are displayed in the form of evaluation values, which has a high degree of intuitiveness.

[0073] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0074] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0075] Figure 1 This is a flowchart illustrating an active support control performance evaluation method for new energy power stations according to an exemplary embodiment.

[0076] Figure 2 This is a schematic diagram illustrating a secondary frequency drop in the power grid according to an exemplary embodiment;

[0077] Figure 3 This is a schematic diagram of the structure of an active support control performance evaluation system for new energy power stations, according to an exemplary embodiment.

[0078] Figure 4 This is a schematic diagram of the structure of a device according to an exemplary embodiment. Detailed Implementation

[0079] The following description and accompanying drawings fully illustrate specific embodiments described herein to enable those skilled in the art to practice them. Some embodiments may include or substitute parts and features of other embodiments. The scope of the embodiments herein encompasses the entire scope of the claims and all available equivalents thereof. Throughout this document, the terms “first,” “second,” etc., are used only to distinguish one element from another without requiring or implying any actual relationship or order between the elements. Indeed, a first element can also be referred to as a second element, and vice versa. Furthermore, the terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a structure, apparatus, or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a structure, apparatus, or device. Without further limitation, an element defined by the phrase “comprising one…” does not exclude the presence of other identical elements in the structure, apparatus, or device that includes said element. The various embodiments described herein are presented in a progressive manner, with each embodiment focusing on its differences from other embodiments; similar or identical parts between embodiments can be referred to interchangeably.

[0080] The terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer" used herein to indicate orientation or positional relationships are based on the orientation or positional relationships shown in the accompanying drawings and are used only for the convenience of describing this document and simplifying the description. They do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as limiting this application. In the description herein, unless otherwise specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly. For example, they can refer to mechanical or electrical connections, or internal connections between two elements, or direct connections or indirect connections through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms according to the specific circumstances.

[0081] In this document, unless otherwise stated, the term "multiple" means two or more.

[0082] In this article, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0083] In this article, the term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0084] Where there is no conflict, the embodiments and features described in this application may be combined with each other.

[0085] like Figure 1 As shown in the figure, this embodiment provides a method for evaluating the active support control performance of a new energy power station, including the following steps:

[0086] The primary indicators of the active support control performance index system for new energy power stations with energy storage configuration are determined, and secondary indicators are constructed based on the primary indicators;

[0087] The weights of primary and secondary indicators are determined, and the active support control performance values ​​of new energy power stations are calculated based on the weight values ​​of the primary and secondary indicators to achieve the evaluation of the active support control performance of new energy power stations.

[0088] In one embodiment, a performance index system for active support control of new energy power stations with energy storage is determined: the active support capability assessment includes two levels of indicators. The first level includes one or more of the following: dynamic voltage regulation, primary frequency regulation, inertia support, and / or damping adjustment.

[0089] In terms of dynamic voltage regulation indicators, voltage qualification rate and maximum voltage state perception indicators are proposed as secondary indicators.

[0090] In terms of primary frequency regulation indicators, the root mean square value of frequency deviation, the performance evaluation index of primary frequency regulation control, and the evaluation index of input status are proposed as secondary indicators.

[0091] For inertia support indicators, the following secondary indicators are proposed: minimum frequency drop point indicator, power grid frequency damping effect indicator, weak grid stability evaluation indicator, power grid frequency secondary drop evaluation indicator, and joint inertia constant indicator.

[0092] For damping adjustment indicators, the adjustment time indicator and rise time indicator are used as secondary indicators to characterize the impact of the energy storage system on the damping characteristics of the new energy power station after its connection.

[0093] In this embodiment, the active support function is divided into four operating conditions, which makes up for the shortcomings of the original only considering frequency and voltage regulation. The secondary indicators are constructed based on the first-level indicators. After refinement, the representation of the indicators is more specific and easier to quantify. By setting two levels of indicators to evaluate the active support capability, the capability of new energy power stations equipped with energy storage under active support conditions can be fully reflected.

[0094] In one embodiment, the formula for calculating the voltage qualification rate is:

[0095]

[0096] Among them: U qualified For voltage qualification rate, U over For voltage exceeding the power supply / consumption limit, U all Percentage of total electricity supply / consumption;

[0097] The formula for calculating maximum voltage state sensing is:

[0098]

[0099]

[0100]

[0101] Where: γ1(t) is the severity index of voltage drop duration, γ2(t) is the severity index of voltage drop amplitude, and T d (t) represents the duration of the voltage drop, T min T max These represent the minimum and maximum values ​​of the voltage sag duration, respectively; U(t) is the real-time voltage value at the grid connection point; U max U min U lim These are the upper interval value of the steady-state voltage range, the lower interval value of the steady-state voltage range, and the critical voltage value for voltage collapse, respectively.

[0102] In one embodiment, the formula for calculating the root mean square value of frequency deviation is:

[0103]

[0104] Where: f i N represents the frequency sample value at the i-th point; c f represents the total number of sampling points; B The reference frequency for the power grid is 50Hz, which is selected here. result The root mean square value of frequency deviation is an index that represents the frequency adjustment effect and reflects the degree of frequency dispersion in the system. The smaller the deviation between the grid frequency and the rated value, the more ideal the frequency regulation effect.

[0105] The formula for calculating the performance evaluation index of primary frequency regulation control is as follows:

[0106]

[0107] Where T is the evaluation period, and ΔP Gt With ΔP St These are the calculated and sampled values ​​of the power change at time t, respectively, for the primary frequency modulation.

[0108] Where, when the calculated C p When C = 0, it indicates that the physical meaning of the primary frequency modulation control performance evaluation is no regulation effect; when C p When C < 0, it indicates that the physical meaning of the primary frequency modulation control performance evaluation is reverse regulation; when C p When C > 1, it indicates that the physical meaning of the primary frequency modulation control performance evaluation is excessive regulation; when C p When C = 1, it indicates that the physical meaning of the primary frequency regulation control performance evaluation is normal regulation; when 0 < C p When <1, it indicates that the physical meaning of the primary frequency modulation control performance evaluation is insufficient regulation.

[0109] The evaluation formula for the input performance evaluation indicators is as follows:

[0110]

[0111] Where, N P.Cq To evaluate the number of qualified points for the input performance indicator Cq within a given time period, N S.Cq The total number of points (Cq) is an indicator used to evaluate the input during the evaluation period.

[0112] In one embodiment, the formula for calculating the frequency drop minimum point indicator is as follows:

[0113]

[0114] Wherein: S B，sys This represents the system's baseline capacity; r pThe power growth rate; Δf DB M is the dead zone frequency; sys The system's total inertia level; f B The reference frequency for the power grid is 50Hz, which is selected here; ΔP L =P m0 -P e0 That is, unbalanced power, P m0 For mechanical power, P e0 Electromagnetic power;

[0115] Formula for calculating the power grid frequency damping effect index:

[0116]

[0117] Where, Δf max f is the maximum value of the change in grid frequency during the dynamic process. B The reference value for the power grid frequency is 50Hz, which is selected here.

[0118] Figure 2 This is a schematic diagram of the second frequency sag in the power grid. The formula for calculating the second frequency sag index is as follows:

[0119]

[0120] Where, Δf 2-max f is the maximum deviation value of the second frequency drop in the power grid. B The reference frequency for the power grid is 50Hz, which is selected here. Figure 2 It can be seen that, given a fixed grid frequency reference value, the larger the maximum deviation of the grid frequency second drop, the larger the grid frequency second drop index value.

[0121] Formula for calculating the joint inertia constant:

[0122]

[0123] Wherein: S NEW For the rated capacity of new energy power stations, E ESS E provides energy to the energy storage system. NEW The energy provided by the renewable energy power station, J is the moment of inertia of the renewable energy power station, ω s This is the system's synchronous speed.

[0124] In one embodiment, the adjustment time index is the shortest time that, after the introduction of the energy storage system to form a virtual synchronous generator, the output active and reactive power of the virtual synchronous generator recovers from the original steady state to within ±2% to ±5% of the new steady state value in the dynamic process and no longer exceeds it.

[0125] The rise time metric is the time required for the output active and reactive power of a virtual synchronous generator to rise from 10% of the steady-state value to 90% of the steady-state value during a dynamic process.

[0126] In one embodiment, determining the weight values ​​of each indicator includes: using a subjective weighting method to determine the weights of the first-level indicators; and using the fact that the results of pairwise comparisons using AHP (Analytic Hierarchy Process) are reciprocals of each other and do not conform to the actual scoring results; combining the advantages of DEMATEL (Decision-making Trial and Evaluation Laboratory), using DEMATEL-ANP (Decision-making Trial and Evaluation Laboratory-Analytic Network Process) to determine the weights of the first-level indicators; and since the second-level indicators are not all independent of each other, using the highly applicable CRITIC (Criteria Importance Though Intercrieria Correlation) method to assign weights to the second-level indicators.

[0127] In one embodiment, the weights of each primary indicator are determined using DEMATEL-ANP, and the steps are as follows:

[0128] Suppose that the network layer of ANP (Analytic Network Process) has a criterion element C. i ,i∈(1,2……n), criterion element C j For C i The degree of direct influence of (j≠i) is y ji The initial judgment matrix Y is obtained: where y ji Based on subjective scoring by individuals using their own experience:

[0129]

[0130] Remove the criterion element C from the network layer. i The influence of all elements other than i∈(1,2……n) on the criterion element is compared pairwise. The influence of all elements in the network layer other than the criterion element on the criterion element is used as elements in the matrix, that is, the corresponding judgment matrix is ​​obtained according to the secondary criterion:

[0131]

[0132] The weight vector under this criterion is obtained using the eigenvalue method:

[0133]

[0134] In the formula, W i For the i-th criterion element C i The weight vector; C represents the i-th criterion element in the n-th column. i The weight.

[0135] By combining the weight vectors under all sub-criteria into a weight matrix, we obtain the direct influence matrix in the DEMATEL method:

[0136]

[0137] In the formula, C represents the i-th criterion element in the n-th column. i The weight, W d This directly affects the matrix.

[0138] To avoid the situation where the comprehensive influence matrix fails to converge, the direct influence matrix W is calculated. d The average comprehensive influence matrix W:

[0139]

[0140] When the limit of the comprehensive influence weight matrix is ​​unique

[0141]

[0142] When multiple limit values ​​exist, the matrix exhibits periodic changes. Taking the average of these points yields the limit value of the average comprehensive influence matrix.

[0143]

[0144] The weighting matrix A is obtained by referring to the DEMATEL method, and the weighting hypermatrix is ​​obtained.

[0145]

[0146] In the formula, This represents the element in the i-th row and j-th column of the weighted hypermatrix.

[0147] Performing 2k+1 evolutions on the above weighted hypermatrix yields a long-term stable matrix, resulting in the weight vector ω for each first-level index. s :

[0148]

[0149] In one embodiment, the steps for determining the weights of secondary indicators using the CRTIC method are as follows:

[0150] To establish the original data matrix for the secondary indicators, taking the dynamic voltage regulation indicator as an example, the calculation steps for the primary frequency regulation indicator, inertia support indicator, and damping adjustment indicator are the same. Assume there are q energy storage power stations to be evaluated, and p secondary indicators under dynamic voltage regulation, i∈(1, 2, ..., q), j∈(1, 2, ..., p). Then the original data matrix is:

[0151]

[0152] Since the secondary indicators in this application are of different orders of magnitude, they need to be reduced to the same range. Among them, the voltage qualification rate indicator, the input status evaluation indicator, and the joint inertia constant indicator are extremely large indicators; the voltage state perception indicator, the mean square value of frequency deviation indicator, the grid frequency damping effect indicator, the weak grid stability evaluation indicator, the grid frequency secondary drop evaluation indicator, the adjustment time indicator, and the rise time indicator are extremely small indicators; the primary frequency regulation control performance evaluation indicator and the minimum frequency drop indicator are intermediate indicators. The optimal value of the primary frequency regulation control performance evaluation indicator is 1, and the optimal value of the minimum frequency drop indicator is 50Hz.

[0153] The extremely small index is preprocessed using the following calculation formula:

[0154] x' j =max(x j )-x j (twenty one)

[0155] In the formula, x j Let x' be the secondary indicator in the j-th column of the original data matrix X. j This is the result of positive transformation of the index in column j.

[0156] Intermediate indicators are preprocessed using the following formula:

[0157]

[0158] In the formula, x j Let x' be the secondary indicator in the j-th column of the original data matrix X. j x is the result of positive transformation of the j-th column index. best This is the optimal value for this intermediate index.

[0159] Then use the calculation formula:

[0160]

[0161] In the formula, x ijLet x' be the j-th secondary index value of the i-th energy storage power station in the original data matrix X. ij This is the positive score for the j-th secondary indicator of the i-th energy storage power station.

[0162] All processed indicators are scored positively;

[0163] The comparability of the j-item indicators is represented by their standard deviation:

[0164]

[0165] In the formula, The average value of the secondary indicators in column j after positive transformation. x' ij σ is the positive score for the j-th secondary indicator of the i-th energy storage power station. j For the comparative analysis of the j-th indicator.

[0166] Let the degree of contradiction between index j and the other indices be (where i ≠ j):

[0167]

[0168] In the formula, r ij f is the Pearson correlation coefficient between indicator i and indicator j. j The contradiction between indicator j and the other indicators.

[0169] Calculate the information carrying capacity of index j:

[0170] C j =σ j f j (26)

[0171] In the formula, f j σ represents the degree of contradiction between indicator j and the other indicators. j For the comparative analysis of the j-th indicator.

[0172] Calculate the information carrying capacity weight of index j:

[0173]

[0174] In the formula, C j The information carrying capacity of indicator j.

[0175] Calculate the dynamic pressure regulation index value S of the primary indicator. 1i :

[0176]

[0177] In the formula, x' ij w is the positive score for the j-th secondary indicator of the i-th energy storage power station. jis the information carrying capacity weight for index j;

[0178] Following the above steps, the primary frequency regulation index value S can be obtained 2i , the inertia support index value S 3i , the damping regulation index value S 4i .

[0179] Based on the above method, the calculated values of the first-level indicators S 1i , S 2i , S 3i , S 4i of the i-th energy storage power station are obtained respectively. Then, using the weight vector ω s obtained by the weight determination method for the first-level indicators (DEMATEL-ANP method), calculate the active support control performance value PERF of the new energy power station with configured energy storage:

[0180]

[0181] Therefore, based on the active support control performance value of the new energy power station, the active support control performance of the energy storage power station is evaluated. The specific process is as follows:

[0182] When PERF ≥ P1, the active support control performance of the new energy power station with configured energy storage is excellent;

[0183] When P2 ≤ PERF < P1, the active support control performance of the new energy power station with configured energy storage is good;

[0184] When P3 ≤ PERF < P2, the active support control performance of the new energy power station with configured energy storage is medium;

[0185] When PERF < P3, the active support control performance of the new energy power station with configured energy storage is poor;

[0186] Among them, P1, P2, and P3 are the comprehensive score thresholds, and P1 > P2 > P3.

[0187] In one embodiment, a new energy power station active support control performance evaluation system is provided. The system structure is as Figure 3 shown, including a preset module and a calculation module, where:

[0188] The preset module is used to determine the first-level indicators of the active support control performance index system of the new energy power station with configured energy storage, and construct the second-level indicators based on the first-level indicators;

[0189] The calculation module is used to determine the weights of the primary and secondary indicators, and based on the weights of the primary and secondary indicators, calculate the active support control performance value of the new energy power station according to the steps in the active support control performance evaluation method of the new energy power station in any of the above embodiments, so as to realize the active support control performance evaluation of the new energy power station.

[0190] In one embodiment, a new energy power station active support control performance evaluation system is provided, which adopts the steps in the new energy power station active support control performance evaluation method provided in any of the above embodiments to realize the active support control performance evaluation of new energy power stations.

[0191] In one embodiment, an electronic device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown, the device includes a processor, memory, and network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores static and dynamic information data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements the steps in the above method embodiments.

[0192] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the electronic device to which the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0193] In one embodiment, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0194] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0195] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0196] It should be noted that the above description is merely some embodiments of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this application 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 with similar functions disclosed in this application.

[0197] 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. Multitasking and parallel processing may be advantageous in certain environments. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this application. 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.

[0198] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for evaluating the active support control performance of a new energy power station, characterized in that, Includes the following steps: This paper establishes a primary index system for the active support control performance of new energy power stations with energy storage configuration. The primary indexes include dynamic voltage regulation, primary frequency regulation, inertia support, and damping adjustment. Secondary indexes are then constructed based on these primary indexes. The dynamic voltage regulation indexes include voltage qualification rate and maximum voltage state perception. The primary frequency regulation indexes include root mean square frequency deviation, primary frequency regulation control performance evaluation, and operational status evaluation. The inertia support indexes include minimum frequency drop, grid frequency damping effect, weak grid stability evaluation, grid frequency secondary drop evaluation, and joint inertia constant. The damping adjustment indexes include adjustment time and rise time. A raw data matrix for the secondary indexes is established. The maximum index for each secondary index is determined, and the remaining secondary indexes are positively processed into maximum indices, bringing all secondary indexes to the same order of magnitude. Standard deviation is used to represent the comparison of a specific index, and the degree of contradiction between that index and the others is determined. The values ​​of the dynamic voltage regulation, primary frequency regulation, inertia support, and damping adjustment indices are calculated sequentially using information carrying capacity. The weights of the primary and secondary indicators are determined, and the active support control performance values ​​of the new energy power stations are calculated based on the weight values ​​of the primary and secondary indicators to achieve the evaluation of the active support control performance of the new energy power stations.

2. The method for evaluating the active support control performance of new energy power stations according to claim 1, characterized in that, The formula for calculating the voltage qualification rate index is as follows: （1） in: For voltage qualification rate, For voltage exceeding the limit, power supply / consumption Percentage of total electricity supply / consumption; The calculation formula for the maximum voltage state sensing is as follows: （2） （3） （4） in: This is an indicator of the severity of the voltage drop duration. As an indicator of the severity of voltage drop amplitude, This represents the duration of the voltage drop. These represent the minimum and maximum values ​​of the voltage drop duration, respectively. This refers to the real-time voltage value at the grid connection point. These are the upper interval value of the steady-state voltage range, the lower interval value of the steady-state voltage range, and the critical voltage value for voltage collapse, respectively.

3. The method for evaluating the active support control performance of new energy power stations according to claim 1, characterized in that, The formula for calculating the root mean square value of the frequency deviation index is as follows: （5） in: This represents the frequency sample value at the i-th point; Indicates the total number of sampling points; The reference value for the power grid frequency is 50Hz, which is taken here. The root mean square value of frequency deviation is the index. The calculation formula for the primary frequency modulation control performance evaluation index is as follows: （6） Where T represents the evaluation period. and These are the calculated and sampled values ​​of the power change at time t, respectively, for the primary frequency modulation. The calculation formula for the input evaluation index is as follows: （7） in, Indicators for evaluating input during a time period Number of qualified points Indicators for evaluating input during a time period Total points.

4. The method for evaluating the active support control performance of new energy power stations according to claim 1, characterized in that, The formula for calculating the frequency drop minimum point index is as follows: （8） in: This is the system's baseline capacity; The power growth rate; Dead zone frequency; This represents the total inertia level of the system. The reference value for the power grid frequency is 50Hz, which is taken here. That is, unbalanced power. For mechanical power, Electromagnetic power; The formula for calculating the power grid frequency damping effect index is as follows: （9） in, This represents the maximum value of the power grid frequency change during the dynamic process; The reference value for the power grid frequency is 50Hz, which is selected here. The formula for calculating the power grid frequency second sag index is as follows: （10） in, This represents the maximum deviation value of the second frequency drop in the power grid. The reference value for the power grid frequency is 50Hz, which is selected here. The formula for calculating the joint inertia constant index is as follows: （11） in: For the rated capacity of new energy power stations, Provide energy for energy storage systems. The energy provided for new energy power plants For the rotational inertia of the new energy power station, This is the system's synchronous speed.

5. The method for evaluating the active support control performance of new energy power stations according to claim 1, characterized in that, The adjustment time index is the shortest time that the output active and reactive power of the virtual synchronous generator recovers from the original steady state to within ±2%-±5% of the new steady state value in the dynamic process after the introduction of the energy storage system to form a virtual synchronous generator, and no longer exceeds the range of ±2%-±5% of the new steady state value. The rise time metric is the time required for the output active and reactive power of the virtual synchronous generator to rise from 10% of the steady-state value to 90% of the steady-state value during the dynamic process.

6. The method for evaluating the active support control performance of new energy power stations according to claim 1, characterized in that, The determination of the weights of the primary indicators adopts a network analysis method based on decision laboratories, and includes the following steps: Suppose that there are criterion elements in the network layer of the network analysis method. The degree of direct influence between each pair of criterion elements is used as matrix elements to obtain the initial judgment matrix. The degree of direct influence of the remaining elements in the network layer, excluding the criterion element, on the criterion element is compared pairwise, that is, the corresponding judgment matrix is ​​obtained according to the secondary criterion. The weight vectors under the secondary criteria are obtained by using the eigenvalue method, and the weight vectors under all the secondary criteria are combined into a weight matrix to obtain the direct influence matrix in decision experiment and evaluation experiment methods. Calculate the average comprehensive influence matrix of the direct influence matrix. When the limit of the comprehensive influence weight matrix is ​​unique, the limit of the comprehensive influence weight matrix is ​​determined as the limit value of the average comprehensive influence matrix. When there are multiple limit values, the matrix exhibits periodic changes, and the average value of each limit point is taken as the limit value of the average comprehensive influence matrix. Calculate the weighted hypermatrix using the limiting value of the average comprehensive influence matrix; Repeat the above steps 2k+1 times to evolve the weighted supermatrix 2k+1 times, forming a long-term stable matrix and obtaining the weight vectors of each first-level index, where k is a natural number.

7. The method for evaluating the active support control performance of new energy power stations according to claim 1, characterized in that, The formula for calculating the active support control performance value of the new energy power station is as follows: （12） in, This represents the active support and control performance value of a new energy power station. The calculated value represents the primary indicator. This represents the weight vector of each primary indicator.

8. The method for evaluating the active support control performance of new energy power stations according to claim 7, characterized in that, when At that time, the active support and control performance of new energy power stations is excellent; When the At that time, the active support and control performance of the new energy power station was good; When the At that time, the active support and control performance of the new energy power station was medium. when At that time, the active support control performance of the new energy power station was poor; in, , , This is the overall score threshold, and > > .

9. A performance evaluation system for active support control of new energy power stations, characterized in that, It includes a preset module and a calculation module, wherein: The preset module is used to determine the primary indicators of the active support control performance index system for new energy power stations with energy storage configuration. The primary indicators include dynamic voltage regulation indicators, primary frequency regulation indicators, inertia support indicators, and damping adjustment indicators. Secondary indicators are constructed based on these primary indicators. The dynamic voltage regulation indicators include voltage qualification rate indicators and maximum voltage state perception indicators. The primary frequency regulation indicators include the root mean square value of frequency deviation, primary frequency regulation control performance evaluation indicators, and operational status evaluation indicators. The inertia support indicators include the minimum frequency drop indicator, grid frequency damping effect indicator, and weak grid stability indicator. The evaluation indicators include a voltage regulation index, a power grid frequency secondary drop evaluation index, and a joint inertia constant index. The damping adjustment index includes a regulation time index and a rise time index. A raw data matrix of secondary indicators is established, the maximum index of each secondary indicator is determined, and the remaining secondary indicators are positively processed into maximum indexes, so that all secondary indicators are within the same order of magnitude. The standard deviation is used to represent the comparison of a certain indicator and to determine the magnitude of the contradiction between that indicator and the other indicators. The dynamic voltage regulation index value, primary frequency regulation index value, inertia support index value, and damping adjustment index value are calculated sequentially using information carrying capacity. The calculation module is used to determine the weights of the primary and secondary indicators, and based on the weights of the primary and secondary indicators, calculate the active support control performance value of the new energy power station according to the steps in the active support control performance evaluation method for new energy power stations as described in any one of claims 1 to 8, thereby realizing the active support control performance evaluation of new energy power stations.

10. The active support control performance evaluation system for new energy power stations according to claim 9, characterized in that, The formula for calculating the voltage qualification rate index is as follows: （1） in: For voltage qualification rate, For voltage exceeding the limit, power supply / consumption Percentage of total electricity supply / consumption; The calculation formula for the maximum voltage state sensing is as follows: （2） （3） （4） in: This is an indicator of the severity of the voltage drop duration. As an indicator of the severity of voltage drop amplitude, This represents the duration of the voltage drop. These represent the minimum and maximum values ​​of the voltage drop duration, respectively. This refers to the real-time voltage value at the grid connection point. These are the upper interval value of the steady-state voltage range, the lower interval value of the steady-state voltage range, and the critical voltage value for voltage collapse, respectively.

11. The active support control performance evaluation system for new energy power stations according to claim 9, characterized in that, The formula for calculating the root mean square value of the frequency deviation index is as follows: （5） in: This represents the frequency sample value at the i-th point; Indicates the total number of sampling points; The reference value for the power grid frequency is 50Hz, which is taken here. The root mean square value of frequency deviation is the index. The calculation formula for the primary frequency modulation control performance evaluation index is as follows: （6） Where T represents the evaluation period. and These are the calculated and sampled values ​​of the power change at time t, respectively, for the primary frequency modulation. The calculation formula for the input evaluation index is as follows: （7） in, Indicators for evaluating input during a time period Number of qualified points Indicators for evaluating input during a time period Total points.

12. The active support control performance evaluation system for new energy power stations according to claim 9, characterized in that, The formula for calculating the frequency drop minimum point index is as follows: （8） in: This is the system's baseline capacity; The power growth rate; Dead zone frequency; This represents the total inertia level of the system. The reference value for the power grid frequency is 50Hz, which is taken here. That is, unbalanced power. For mechanical power, Electromagnetic power; The formula for calculating the power grid frequency damping effect index is as follows: （9） in, This represents the maximum value of the power grid frequency change during the dynamic process; The reference value for the power grid frequency is 50Hz, which is selected here. The formula for calculating the power grid frequency second sag index is as follows: （10） in, This represents the maximum deviation value of the second frequency drop in the power grid. The reference value for the power grid frequency is 50Hz, which is selected here. The formula for calculating the joint inertia constant index is as follows: （11） in: For the rated capacity of new energy power stations, Provide energy for energy storage systems. The energy provided for new energy power plants For the rotational inertia of the new energy power station, This is the system's synchronous speed.

13. The active support control performance evaluation system for new energy power stations according to claim 9, characterized in that, The adjustment time index is the shortest time that the output active and reactive power of the virtual synchronous generator recovers from the original steady state to within ±2%-±5% of the new steady state value in the dynamic process after the introduction of the energy storage system to form a virtual synchronous generator, and no longer exceeds the range of ±2%-±5% of the new steady state value. The rise time metric is the time required for the output active and reactive power of the virtual synchronous generator to rise from 10% of the steady-state value to 90% of the steady-state value during the dynamic process.

14. The active support control performance evaluation system for new energy power stations according to claim 9, characterized in that, The determination of the weights of the primary indicators adopts a network analysis method based on decision laboratories, and includes the following steps: Suppose that there are criterion elements in the network layer of the network analysis method. The degree of direct influence between each pair of criterion elements is used as matrix elements to obtain the initial judgment matrix. The degree of direct influence of the remaining elements in the network layer, excluding the criterion element, on the criterion element is compared pairwise, that is, the corresponding judgment matrix is ​​obtained according to the secondary criterion. The weight vectors under the secondary criteria are obtained by using the eigenvalue method, and the weight vectors under all the secondary criteria are combined into a weight matrix to obtain the direct influence matrix in decision experiment and evaluation experiment methods. Calculate the average comprehensive influence matrix of the direct influence matrix. When the limit of the comprehensive influence weight matrix is ​​unique, the limit of the comprehensive influence weight matrix is ​​determined as the limit value of the average comprehensive influence matrix. When there are multiple limit values, the matrix exhibits periodic changes, and the average value of each limit point is taken as the limit value of the average comprehensive influence matrix. Calculate the weighted hypermatrix using the limiting value of the average comprehensive influence matrix; Repeat the above steps 2k+1 times to evolve the weighted supermatrix 2k+1 times, forming a long-term stable matrix and obtaining the weight vectors of each first-level index, where k is a natural number.

15. The active support control performance evaluation system for new energy power stations according to claim 9, characterized in that, The formula for calculating the active support control performance value of the new energy power station is as follows: （12） in, This represents the active support and control performance value of a new energy power station. The calculated value represents the primary indicator. This represents the weight vector of each primary indicator.

16. A medium having a program stored thereon, characterized in that, When executed by the processor, the program implements the steps in the active support control performance evaluation method for new energy power stations as described in any one of claims 1 to 8.

17. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the active support control performance evaluation method for new energy power stations as described in any one of claims 1 to 8.

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