Method, device and equipment for evaluating adaptability of multi-terminal embedded direct current in power grid

Abstract

The invention discloses an adaptability evaluation method, device and equipment for multi-terminal embedded direct current in a power grid, and the method comprises the steps: determining a stabilizing effect evaluation index of a multi-terminal embedded direct current scheme for the fluctuation of new energy output power; determining an influence evaluation index of the multi-terminal embedded direct current scheme on the voltage supporting capability of a load center; determining an influence evaluation index of the multi-terminal embedded DC scheme on the primary frequency modulation capability of the load center; and determining adaptability evaluation of the multi-terminal embedded DC scheme in the target power grid based on the stabilizing effect evaluation index, the influence evaluation index of the voltage supporting capability and the influence evaluation index of the primary frequency modulation capability. According to the method, the adaptability of the multi-terminal embedded direct current in the power grid is comprehensively and reasonably evaluated from multiple aspects, the power grid planning is scientifically and reasonably guided, and a reliable basis is provided for the power grid planning.

Description

Technical Field

[0001] The present application relates to the technical field of power systems, and in particular to a method, device, and equipment for evaluating the adaptability of a multi-terminal embedded direct current in a power grid. Background Art

[0002] Multi-terminal embedded DC technology, a key development direction for new power grids, has made significant progress in provincial transmission networks. By leveraging existing overhead lines or reserved cable channels to construct hybrid AC / DC power grids, this technology effectively addresses the problem of insufficient capacity at key transmission sections (such as those crossing rivers). Its core lies in control and protection technologies, such as the use of special topologies, DC fault ride-through restart strategies, and optimized open-line test (OLT) control. It also addresses the adaptability challenges of AC protection devices (for example, analyzing distance protection characteristics).

[0003] In terms of application scenarios, multi-terminal embedded DC technology primarily serves to tap the potential of power grids, increase efficiency, and transform new power systems. First, it addresses capacity expansion needs in areas with tight transmission corridors (such as urban agglomerations and cross-river corridors) by increasing existing corridor utilization by over 30% through coordinated AC / DC operation. Second, it supports the stable operation of power grids with high penetration of new energy sources, smoothing the intermittent and volatile nature of wind and solar power generation through flexible regulation. Third, as a structural reinforcement for the power grid, it provides an alternative solution when new AC corridors are impractical or cost-prohibitive. As multi-terminal control technology improves in the future, its application scenarios will expand to include distributed energy aggregation, microgrid interconnection, and other areas.

[0004] When multi-terminal embedded DC technology is applied to power grids, one or more solutions may exist for the same grid. The adaptability of these solutions within the grid needs to be evaluated, and the optimal solution identified based on the evaluation results. However, the factors considered in the adaptability evaluation methods used in related technologies for multi-terminal embedded DC solutions within the grid are incomplete or unreasonable, leading to irrational adaptability evaluations and, consequently, irrational grid planning. Summary of the Invention

[0005] The embodiments of the present application provide a method, device, and equipment for evaluating the adaptability of a multi-terminal embedded DC in a power grid, which can comprehensively and reasonably evaluate the adaptability of a multi-terminal embedded DC in a power grid from multiple aspects, and can scientifically and reasonably guide power grid planning and provide a reliable basis for power grid planning.

[0006] In a first aspect, the present application provides a method for evaluating the adaptability of a multi-terminal embedded DC system in a power grid, comprising:

[0007] Determine the evaluation indicators for the effectiveness of multi-terminal embedded DC solutions in smoothing the fluctuation of renewable energy output power;

[0008] Determine an evaluation index for the impact of the multi-terminal embedded DC solution on the voltage support capability of the load center;

[0009] Determining an impact evaluation index of the multi-terminal embedded DC solution on the primary frequency regulation capability of the load center;

[0010] An adaptability evaluation of the multi-terminal embedded direct current solution in a target power grid is determined based on the suppression effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index.

[0011] In a second aspect, the present application provides a device for evaluating the adaptability of a multi-terminal embedded DC system in a power grid, comprising:

[0012] The first determination module is used to determine the evaluation index of the multi-terminal embedded DC solution's effect of smoothing the fluctuation of renewable energy output power;

[0013] A second determination module is used to determine an evaluation index of the impact of the multi-terminal embedded DC solution on the voltage support capability of the load center;

[0014] A third determination module is used to determine an impact evaluation index of the multi-terminal embedded DC solution on the primary frequency regulation capability of the load center;

[0015] An evaluation module is used to determine the adaptability evaluation of the multi-terminal embedded DC solution in the target power grid based on the smoothing effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index.

[0016] In a third aspect, the present application provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method provided in an embodiment of the present application is implemented.

[0017] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed in a computer, it enables the computer to execute the method provided in the embodiment of the present application.

[0018] The technical solution provided in the embodiment of the present application evaluates the adaptability of the multi-terminal embedded DC solution in the target power grid through the evaluation index of the multi-terminal embedded DC solution on the smoothing effect of the power fluctuation of the new energy transmission, the evaluation index of the impact on the voltage support capacity of the load center, and the evaluation index of the impact on the primary frequency regulation capacity of the load center. That is, by evaluating the adaptability from three aspects: the smoothing of the fluctuation of the power transmission of new energy, the voltage support capacity of the load center, and the coordination of the new energy at the sending end and the improvement of the primary frequency regulation capacity of the load center at the receiving end, the adaptability of the multi-terminal embedded DC solution in the power grid can be comprehensively and reasonably evaluated from multiple aspects; by using the hierarchical analysis method to carry out the adaptability evaluation of various multi-terminal embedded DC solutions, the evaluation process can be presented in a hierarchical manner, making the evaluation process clear and unambiguous; in summary, through the above scheme, the adaptability of the multi-terminal embedded DC solution in the power grid can be scientifically and reasonably evaluated, the power grid planning can be reasonably guided, and a reliable basis for power grid rules can be provided. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flow chart of a method for evaluating the adaptability of a multi-terminal embedded DC system in a power grid is provided for the implementation of this application.

[0020] Figure 2 This is a flowchart for evaluating the adaptability of a multi-terminal embedded DC solution in a target power grid using the analytic hierarchy process, provided in an embodiment of the present application;

[0021] Figure 3 It is a schematic diagram of the adaptability evaluation module framework;

[0022] Figure 4 This is a structural block diagram of a multi-terminal embedded DC adaptability evaluation device in a power grid provided by the present application;

[0023] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The present application is further described in detail below through the accompanying drawings and specific implementation methods.

[0025] Figure 1 This is a flow chart of a method for evaluating the adaptability of a multi-terminal embedded DC in a power grid, provided in an embodiment of the present application. The method can be performed by a device for evaluating the adaptability of a multi-terminal embedded DC in a power grid. The device can be implemented by software and / or hardware. The method can be applied to power grids with the need to transmit new energy and receive power from load centers.

[0026] like Figure 1 As shown, the method provided in the embodiment of the present application includes the following steps:

[0027] S110: Determine the evaluation indicators of the multi-terminal embedded DC solution’s effect on smoothing the fluctuation of renewable energy output power.

[0028] In this embodiment, a multi-terminal embedded DC solution can be implemented by adding an AC grid near the renewable energy source. This new energy source and the added AC grid serve as the sending end, supplying power to the load center. Specifically, a new converter station port is added to the AC grid near the renewable energy source, building upon the existing output converter station port. This new converter station port is then used to mobilize the connected AC grid to smooth fluctuations in renewable energy output power. Different multi-terminal embedded DC solutions can feature different receiving load center locations and capacities.

[0029] In this embodiment, an evaluation index of the multi-terminal embedded DC solution's effect of smoothing the fluctuation of renewable energy power transmission can be determined based on the maximum fluctuation of renewable energy power transmission within a preset time range and the maximum power variation that can be provided by the AC power grid in the vicinity of the renewable energy. Specifically, the evaluation index of the smoothing effect can be obtained in the form of a ratio.

[0030] Specifically, in one embodiment, determining an evaluation index of the multi-terminal embedded DC solution's effect of smoothing fluctuations in renewable energy output power includes determining the evaluation index based on the following formula:

[0031]

[0032] Wherein, χ is the suppression rate of the multi-terminal embedded DC solution on the fluctuation of the power output of renewable energy, and the suppression rate is the evaluation index of the smoothing effect; It is the maximum fluctuation of the renewable energy power transmission within a preset time range; wherein, the historical data of the renewable energy power transmission can be provided by the renewable energy transmitting end, and the maximum fluctuation of the renewable energy power transmission can be calculated by using the historical data within the preset time range.

[0033] in, The maximum power change rate provided by the AC grid near the renewable energy area can be calculated based on historical power data provided by the AC grid near the renewable energy area. The preset time range can be 15 minutes, 30 minutes, or other timeframes.

[0034] S120: Determine an evaluation index of the impact of the multi-terminal embedded DC solution on the voltage support capability of the load center.

[0035] In this embodiment, the impact of the multi-terminal embedded DC solution on the voltage support capacity of the load center is analyzed by analyzing the change in the time it takes for the node voltage to recover to 0.95pu after the AC line N-1 fault occurs in the key load node before and after the multi-terminal embedded DC solution. The multi-terminal embedded DC solution can be a multi-terminal embedded flexible DC solution. The key load node can be a load node with a heavy load; the load center is connected to the load node, and the load center connected to the key load node can be understood as a key load center, that is, a load center with a heavy load, that is, a load center with a load exceeding the preset load standard. Pu is the unit of per unit value. Per unit value is a numerical notation method commonly used in power system analysis and engineering calculations to represent the relative values ​​of various physical quantities and parameters.

[0036] Specifically, in one embodiment, determining the impact evaluation index of the multi-terminal embedded DC solution on the voltage support capability of the load center includes: determining the impact evaluation index of the multi-terminal embedded DC solution on the voltage support capability of the load center based on the following formula:

[0037]

[0038] in, is the overall change rate of the voltage support capability of the multi-terminal embedded DC solution on the load center, and the overall change rate is an impact evaluation indicator of the multi-terminal embedded DC solution on the voltage support capability of the load center;

[0039] in, and The time it takes for the node voltage to recover to 0.95pu after a fault occurs in the AC line N-1 connected to the i-th critical load node before and after adding the multi-terminal embedded DC solution.

[0040] in, is the rate of change of the voltage support capability of the multi-terminal embedded DC solution for the i-th load center. When it is less than 1, the smaller the value, the stronger the voltage support capability for the load center. When it is greater than 1, the larger the value, the greater the voltage weakening damage to the load center.

[0041] Among them, A i is the weight coefficient of the i-th load center, where the key load node is connected to the load center, A i Greater than or equal to 0 and less than or equal to 1. The weight coefficient of the load center can be determined based on factors such as the function and nature of the load center. For example, if the load centers are a shopping mall and an administrative building, the weight coefficient of the administrative building is greater than the weight coefficient of the shopping mall.

[0042] S130: Determine an evaluation index of the impact of the multi-terminal embedded DC solution on the primary frequency regulation capability of the load center.

[0043] In this embodiment, the change in the primary frequency regulation capability of the load center before and after the addition of the multi-terminal embedded DC solution can be calculated, and an impact evaluation index of the multi-terminal embedded DC solution on the primary frequency regulation capability of the load center can be determined based on this change. Specifically, the impact evaluation index of the multi-terminal embedded DC solution on the primary frequency regulation capability of the load center can be determined based on the maximum frequency deviation of the load center before and after the addition of the multi-terminal embedded DC solution.

[0044] Specifically, in one embodiment, determining an impact evaluation index of the multi-terminal embedded DC solution on the primary frequency regulation capability of the load center includes:

[0045] The impact assessment index of the primary frequency modulation capability is determined based on the following formula:

[0046]

[0047] Wherein, μ is the rate of change of the primary frequency regulation capability of the load center after adding the multi-terminal embedded DC solution, and the rate of change of the primary frequency regulation capability is an impact assessment indicator of the primary frequency regulation capability;

[0048] in,

[0049] Where Δf steady =K f ΔP max ;

[0050] Where Δf steady and Before and after adding the multi-terminal embedded DC solution, the maximum frequency deviation of the load center is in per-unit values; K f is the regulation coefficient, which is obtained by counting the frequency regulation capabilities of the primary frequency regulation resources in the target power grid and remains unchanged before and after adding the multi-terminal embedded DC.

[0051] Where ΔP max and They are the maximum power loss of the load center before and after adding the multi-terminal embedded DC solution, ΔP dc The primary frequency regulation support power provided by the multi-terminal embedded DC solution to the load center is a per-unit value. After the multi-terminal embedded DC solution is determined, ΔP max 、 ΔP dc The values ​​can be obtained directly.

[0052] S140: Determine an adaptability evaluation of the multi-terminal embedded DC solution in the target power grid based on the suppression effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index.

[0053] In one embodiment, for multiple multi-terminal embedded DC solutions, a hierarchical analysis method can be used to determine the adaptability of the multi-terminal embedded DC solution in a target power grid based on the evaluation indicators of the multi-terminal embedded DC solution's effect on smoothing the fluctuation of renewable energy power output, the impact on the voltage support capability of the load center, and the impact on the primary frequency regulation capability of the load center. The adaptability evaluation is then ranked, and the multi-terminal embedded DC solution with the best adaptability is selected. This method can present the evaluation process in a hierarchical manner, making the evaluation process clear and unambiguous, and can scientifically and rationally evaluate the adaptability of the multi-terminal embedded DC solution in the power grid, thereby more rationally guiding grid regulations and solution selection.

[0054] In another embodiment, for each embedded DC solution, a score can be assigned based on the multi-terminal embedded DC solution's evaluation indicators for its effectiveness in smoothing renewable energy power output fluctuations, its impact on the load center's voltage support capability, and its impact on the load center's primary frequency regulation capability, according to corresponding preset criteria, to obtain an adaptability evaluation score for the multi-terminal embedded DC solution in the target power grid. Specifically, each evaluation indicator can be scored based on the corresponding preset criteria, and a total adaptability evaluation score can be determined through weighted summation or direct summation, thereby evaluating the adaptability of the multi-terminal embedded DC solution in the target power grid. Furthermore, the solutions can be ranked based on the total adaptability evaluation scores to select the best solution.

[0055] The technical solution provided in the embodiment of the present application evaluates the adaptability of the multi-terminal embedded DC solution in the target power grid through the evaluation index of the multi-terminal embedded DC solution on the smoothing effect of the power fluctuation of the new energy transmission, the evaluation index of the impact on the voltage support capability of the load center, and the evaluation index of the impact on the primary frequency regulation capability of the load center. That is, by evaluating the adaptability from three aspects: the smoothing of the fluctuation of the power transmission of the new energy, the voltage support capability of the load center, and the coordination of the new energy at the sending end and the improvement of the primary frequency regulation capability of the load center at the receiving end, the adaptability of the multi-terminal embedded DC solution in the power grid can be comprehensively and reasonably comprehensively evaluated from multiple aspects, which can scientifically and reasonably guide the power grid planning and provide a reliable basis for power grid rules.

[0056] In one embodiment, the adaptability evaluation of the multi-terminal embedded DC scheme in the target power grid is determined based on the smoothing effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index, including: for multiple multi-terminal embedded DC schemes, using a hierarchical analysis method to determine the adaptability evaluation of the multi-terminal embedded DC scheme in the target power grid based on the smoothing effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index, and ranking the adaptability evaluation; wherein, the target power grid has the needs of transmitting new energy and receiving power at the load center.

[0057] Figure 2 The embodiment of the present application provides a flowchart for evaluating the adaptability of a multi-terminal embedded DC solution in a target power grid using a hierarchical analysis method based on a leveling effect evaluation index, a voltage support capability impact evaluation index, and a primary frequency regulation capability impact evaluation index. Figure 2 As shown, the technical solution provided in the embodiment of the present application includes the following steps:

[0058] S210: Construct an adaptability evaluation model, which includes a target layer, a criterion layer, and a solution layer, wherein the target layer is a multi-terminal embedded DC solution for optimizing the target power grid, the criterion layer includes the volatility of renewable energy transmission power, the voltage support capability of the load center, and the primary frequency regulation capability of the load center, and the solution layer is a multi-terminal embedded DC solution.

[0059] In this embodiment, the framework of the constructed adaptability evaluation model can refer to Figure 3 , among which, the multi-terminal embedded DC solution is not limited to Figure 3 The adaptability evaluation model is a model constructed based on the hierarchical analysis method, which has a target layer, a criterion layer, and a scheme layer. The target layer is generally the target or rational result of the evaluation; the criterion layer includes all the intermediate links taken to achieve the target, including the criteria that need to be considered; the scheme layer includes various alternative schemes selected to achieve the target. Therefore, the adaptability evaluation model in this embodiment is divided into three layers, with the multi-terminal embedded DC scheme for optimizing the target power grid as the target layer, the various influencing factors affecting the adaptability evaluation as the criterion layer, and the multi-terminal embedded DC scheme as the scheme layer.

[0060] S220: Construct a criterion layer matrix, determine a weight vector of the criterion layer matrix, and perform consistency check on the criterion layer matrix.

[0061] In this embodiment, each criterion in the criterion layer can be scored based on the needs of the target power grid, or based on the relative importance of each criterion in the criterion layer relative to the factors in the target layer. The score can be 1-9, with a higher score indicating greater attention. After scoring each criterion, a criterion layer matrix can be constructed based on the importance of each criterion.

[0062] Among them, the criterion layer matrix is:

[0063] A=(a ij ) n×n ;

[0064] Among them, a ij >0;

[0065] Among them, a ij It is expressed as the importance of the i-th criterion relative to the j-th criterion, and n is the number of criteria in the criterion layer. For example, if the scores of the three criteria in the criterion layer are 2, 3, and 5 respectively, that is, (1) the most important, (2) relatively important, and (3) not very important, the resulting criterion layer matrix is:

[0066]

[0067] In this embodiment, the calculation formula of the weight vector of the criterion layer matrix is ​​as follows:

[0068]

[0069] in, is the weight vector of the criterion layer matrix;

[0070] in,

[0071] Among them, W Ai is the weight coefficient of the ith layer of the criterion layer matrix;

[0072] In this embodiment, performing consistency check on the criterion layer matrix includes: performing consistency check on the criterion layer matrix based on the following formula:

[0073]

[0074] in,

[0075] Among them, CI A is the consistency index of the criterion layer matrix; CR Ais the random consistency index of the criterion layer matrix, which changes with the order of the criterion layer matrix. In this application, there are three criteria in the criterion layer, and the order of the criterion layer matrix is ​​3. By querying Table 1, we can get RI A It is 0.58; Table 1 is the random consistency index value table.

[0076] Among them, λ Amax is the maximum eigenvalue of the criterion layer matrix; if CR A <0.1, indicating that the consistency of the criterion layer matrix is ​​considered to be within the acceptable range; CR A ≥0.1, the criterion layer matrix is ​​modified; if there is CR A If the value is ≥0.1, the criterion layer matrix may be input incorrectly. You can input the correct criterion layer matrix after verification.

[0077] Table 1

[0078]

[0079] S230: For each multi-terminal embedded DC solution, the implementation effect of each multi-terminal embedded DC solution is scored under each criterion in the criterion layer based on the smoothing effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index, and a solution layer matrix of the solution layer relative to each criterion in the criterion layer is constructed based on the implementation effect score.

[0080] In this embodiment, if the criterion is the volatility of renewable energy output power, the implementation effect of each scheme is scored based on the corresponding stabilization effect index. If the criterion is the voltage support capability of the load center, the implementation effect of each scheme is scored based on the impact assessment index of the voltage support capability. If the criterion is the primary frequency regulation capability of the load center, the implementation effect of each scheme is scored based on the impact assessment index of the primary frequency regulation capability. The scores can be 1-9, with higher scores indicating better implementation effects.

[0081] In this embodiment, after scoring the implementation effect, a solution layer matrix can be constructed relative to each criterion of the criterion layer. The solution layer matrix is:

[0082] B p =(b pij ) m×m

[0083] Among them, B p represents the solution layer matrix corresponding to the pth criterion of the criterion layer; b pijIt indicates the importance of the i-th option relative to the j-th option in terms of criterion p, which can be reflected by the ratio of the implementation effect scores; m is the number of options.

[0084] In this embodiment, consistency check may also be performed on the solution layer matrix, and the check method may be the same as the check method for the criterion layer matrix.

[0085] S240: Determine the weight coefficients of the various criteria in the criterion layer for the schemes in the scheme layer based on the scheme layer matrix, and determine the final evaluation result of the adaptability of the multi-terminal embedded DC scheme in the target power grid based on the weight vector of the criterion layer matrix and the weight coefficients.

[0086] In this embodiment, the calculation formula for determining the weight coefficient of each criterion in the criterion layer for the scheme in the scheme layer is as follows:

[0087]

[0088] in, is the weight coefficient of the i-th option in criterion p;

[0089] In this embodiment, the elements in the weight vector of the criterion layer matrix include the weight coefficients of each criterion relative to the target; the elements in the weight vector of the criterion layer matrix are multiplied by the weight coefficients of the corresponding solutions in the criterion and summed to obtain the final evaluation result.

[0090] Specifically, the calculation formula for the final evaluation result of the adaptability of the multi-terminal embedded DC solution in the target power grid is as follows:

[0091]

[0092] Among them, b i is the final evaluation score of the adaptability of the i-th solution in the target power grid.

[0093] In an embodiment of the present application, a hierarchical analysis method is used to evaluate the adaptability of various multi-terminal embedded DC solutions in a target power grid. This evaluation method can present the evaluation process in a hierarchical manner, making the evaluation process clear and unambiguous, and can scientifically and reasonably evaluate the adaptability of the multi-terminal embedded DC solution in the power grid, thereby more reasonably guiding the power grid rules and solution selection, and providing a reliable basis for the power grid rules.

[0094] It should be noted that, for the sake of simplicity, the "solution" mentioned in this application can be understood as a multi-terminal embedded DC solution. In addition, when the hierarchical analysis method is used to carry out adaptability evaluation, steps S210 and S220 can also be performed before S110-S130.

[0095] For example, the present application uses target software to evaluate the adaptability of a multi-terminal embedded DC solution in a target power grid. For ease of description, the renewable energy transmission terminals are designated as A1, A2, ..., Ak, the renewable energy near-region interconnection terminals (i.e., the terminals near the renewable energy area connected to the AC power grid) are designated as B1, B2, ..., Bs, and the load center receiving terminals are designated as C1, C2, ..., Ct. The calculation process is described below using a set of implementation schemes with k = 2, s = 1, and t = 2 (hereinafter referred to as "Scheme 1") as an example.

[0096] (1) Calculate the evaluation index of the effect of multi-terminal embedded DC on the fluctuation of renewable energy power transmission

[0097] The time-varying curve of the total output power of renewable energy transmission terminals A1 and A2 in Scheme 1 (statistics were collected every 15 minutes) shows that the maximum fluctuation in renewable energy transmission power within 15 minutes is 5 MW. Since the maximum power variation provided by renewable energy local interconnection terminal B1 is 3 MW, the suppression rate of renewable energy transmission power fluctuation in Scheme 1 can be calculated as 3 / 5 × 100% = 60%.

[0098] (2) Calculate the impact evaluation indicators of the multi-terminal embedded DC solution on the voltage support capability of the load center.

[0099] In Scheme 1, there are two DC points in the load center, both of which can use flexible DC converter stations and adopt constant AC voltage control. The weight coefficients of C1 and C2 are 0.4 and 0.6 respectively. Before adding the multi-terminal embedded DC solution, the voltage recovery time of the load nodes corresponding to the C1 and C2 load centers are 1.2s and 1.4s respectively; after adding the multi-terminal embedded DC solution, the voltage recovery time of the load nodes corresponding to the C1 and C2 load centers are 1.0s and 1.1s respectively. It can be obtained

[0100] (3) Calculate the impact evaluation indicators of the multi-terminal embedded DC solution on the primary frequency regulation capability of the load center.

[0101] By calculating the primary frequency regulation resources and the maximum possible power loss at the load center, we obtain a droop coefficient and maximum power loss of 0.04 and 0.15 pu, respectively, which translates to a maximum frequency deviation of 0.04 × 0.15 = 0.006 pu. With the addition of a multi-terminal embedded DC solution, the multi-terminal embedded DC solution can provide 0.08 pu of primary frequency regulation power to the load center, resulting in a maximum frequency deviation of 0.04 × (0.15 - 0.08) = 0.0024. Furthermore, with the addition of the multi-terminal embedded DC solution, the change rate of the load center's primary frequency regulation capacity is (1 - 0.0024 / 0.006) × 100% = 60%.

[0102] The above are the calculation results of the above three aspects of a multi-terminal embedded DC solution. After performing the above analysis and calculation on different solutions, the scales achieved by different solutions under various criteria (i.e., the scores obtained) can be obtained. Then, through hierarchical analysis and calculation, all solutions are ranked to obtain the multi-terminal embedded DC solution that best meets the needs of urban power grid improvement.

[0103] Figure 4 This is a structural block diagram of a multi-terminal embedded DC adaptability evaluation device in a power grid provided by an embodiment of the present application. The device includes:

[0104] The first determination module 410 is used to determine an evaluation index of the multi-terminal embedded DC solution's effect of smoothing the fluctuation of renewable energy output power;

[0105] A second determination module 420 is configured to determine an impact evaluation index of the multi-terminal embedded DC solution on the voltage support capability of the load center;

[0106] A third determination module 430 is configured to determine an impact evaluation index of the multi-terminal embedded DC solution on the primary frequency regulation capability of the load center;

[0107] The evaluation module 440 is configured to determine the adaptability evaluation of the multi-terminal embedded DC solution in the target power grid based on the suppression effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index.

[0108] In one embodiment, the evaluation module 440 is specifically configured to:

[0109] For a variety of multi-terminal embedded DC schemes, a hierarchical analysis method is used to determine the adaptability evaluation of the multi-terminal embedded DC schemes in the target power grid based on the smoothing effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index, and to rank the adaptability evaluation; wherein, the target power grid has the needs of transmitting new energy and receiving power at the load center.

[0110] In one possible embodiment, the first determining module 410 is specifically configured to determine the suppression effect evaluation index based on the following formula:

[0111]

[0112] Wherein, χ is the suppression rate of the multi-terminal embedded DC solution on the fluctuation of the power output of renewable energy, and the suppression rate is the evaluation index of the smoothing effect; The maximum fluctuation of the power output of renewable energy within a preset time range; It is the maximum power variation that can be provided by the AC power grid in the vicinity of the new energy source.

[0113] In one possible embodiment, the second determining module 420 is specifically configured to determine an impact evaluation index of the multi-terminal embedded DC solution on the voltage support capability of the load center based on the following formula:

[0114]

[0115] in, is the overall change rate of the multi-terminal embedded DC solution on the voltage support capability of the load center, and the overall change rate is an impact evaluation indicator of the multi-terminal embedded DC solution on the voltage support capability of the load center;

[0116] in, and are the time it takes for the node voltage to recover to 0.95 pu after a fault occurs in the AC line N-1 connected to the i-th critical load node before and after adding the multi-terminal embedded DC solution; is the voltage support capability change rate of the multi-terminal embedded DC solution for the i-th load center, wherein the key load node is connected to the load center,

[0117] Among them, A i is the weight coefficient of the i-th load center, A i Greater than or equal to 0 and less than or equal to 1.

[0118] In one possible embodiment, the third determining module 430 is specifically configured to determine the impact assessment index of the primary frequency modulation capability based on the following formula:

[0119]

[0120] Wherein, μ is the rate of change of the primary frequency regulation capability of the load center after adding the multi-terminal embedded DC solution, and the rate of change of the primary frequency regulation capability is an impact assessment indicator of the primary frequency regulation capability;

[0121] in,

[0122] Where Δf steady =K f ΔP max ;

[0123] Where Δf steady and The maximum frequency deviation of the load center before and after adding the multi-terminal embedded DC solution; K f is the adjustment coefficient; ΔP max and They are the maximum power loss of the load center before and after adding the multi-terminal embedded DC solution, ΔPdc The primary frequency regulation support power provided by the multi-terminal embedded DC solution to the load center.

[0124] In one possible embodiment, the evaluation module 440 is specifically configured to:

[0125] Constructing an adaptability evaluation model, the adaptability evaluation model including a target layer, a criterion layer, and a solution layer, wherein the target layer is a multi-terminal embedded DC solution for optimizing the target power grid, the criterion layer includes the volatility of renewable energy output power, the voltage support capability of the load center, and the primary frequency regulation capability of the load center, and the solution layer is a multi-terminal embedded DC solution;

[0126] Constructing a criterion layer matrix, determining a weight vector of the criterion layer matrix, and performing a consistency check on the criterion layer matrix;

[0127] For each multi-terminal embedded DC solution, score the implementation effect of each multi-terminal embedded DC solution under each criterion based on the leveling effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index, and construct a solution layer matrix of the solution layer relative to each criterion in the criterion layer based on the implementation effect scores;

[0128] Based on the scheme layer matrix, the weight coefficients of the various criteria in the criterion layer of the scheme in the scheme layer are determined, and based on the weight vector of the criterion layer matrix and the weight coefficients, the final evaluation result of the adaptability of the multi-terminal embedded DC scheme in the target power grid is determined.

[0129] In one possible embodiment, the criterion layer matrix is:

[0130] A=(a ij ) n×n ;

[0131] Among them, a ij >0;

[0132] Among them, a ij It is expressed as the importance of the i-th criterion relative to the j-th criterion, and n represents the number of criteria in the criterion layer;

[0133] Correspondingly, the calculation formula of the weight vector of the criterion layer matrix is ​​as follows:

[0134]

[0135] in, is the weight vector of the criterion layer matrix;

[0136] in,

[0137] Among them, W Ai is the weight coefficient of the ith layer of the criterion layer matrix;

[0138] Accordingly, performing consistency check on the criterion layer matrix includes: performing consistency check on the criterion layer matrix based on the following formula:

[0139]

[0140] in,

[0141] Among them, CI A is the consistency index of the criterion layer matrix; CR A is the random consistency index of the criterion layer matrix; Amax is the maximum eigenvalue of the criterion layer matrix; if CR A <0.1, indicating that the consistency of the criterion layer matrix is ​​considered to be within the acceptable range; CR A ≥0.1, then the criterion layer matrix is ​​modified;

[0142] Correspondingly, the solution layer matrix is:

[0143] B p =(b pij ) m×m

[0144] Among them, B p represents the solution layer matrix corresponding to the pth criterion of the criterion layer; b pij It indicates the importance of the i-th option relative to the j-th option in terms of criterion p; m is the number of options;

[0145] Accordingly, the calculation formula for determining the weight coefficient of each criterion in the criterion layer for the scheme in the scheme layer is as follows:

[0146]

[0147] in, is the weight coefficient of the i-th option in criterion p;

[0148] Accordingly, the calculation formula for the final evaluation result of the adaptability of the multi-terminal embedded DC solution in the target power grid is as follows:

[0149]

[0150] Among them, b i is the final evaluation score of the adaptability of the i-th solution in the target power grid.

[0151] like Figure 5 As shown, an embodiment of the present application provides an electronic device, including a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other through the communication bus 114.

[0152] Memory 113, for storing computer programs;

[0153] In one embodiment of the present application, the processor 111 is configured to execute a program stored in the memory 113 to implement the method provided by any of the aforementioned method embodiments, including:

[0154] Determine the evaluation indicators for the effectiveness of multi-terminal embedded DC solutions in smoothing the fluctuation of renewable energy output power;

[0155] Determine an evaluation index for the impact of the multi-terminal embedded DC solution on the voltage support capability of the load center;

[0156] Determining an impact evaluation index of the multi-terminal embedded DC solution on the primary frequency regulation capability of the load center;

[0157] An adaptability evaluation of the multi-terminal embedded direct current solution in a target power grid is determined based on the suppression effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index.

[0158] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method provided in any of the aforementioned method embodiments are implemented.

[0159] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0160] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a general hardware platform, or of course, by hardware. Based on this understanding, the above technical solution, in essence, or the part that contributes to the relevant technology, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiment.

[0161] The above embodiments are provided for illustrative purposes only and are not intended to limit the scope of implementation. Those skilled in the art will appreciate that other variations or modifications based on the above descriptions are possible. It is not necessary and impossible to provide an exhaustive list of all implementations. Obvious variations or modifications arising therefrom remain within the scope of protection of this application.

Claims

1. A method for evaluating the adaptability of a multi-terminal embedded DC system in a power grid, characterized in that: include: Determine the evaluation indicators for the effectiveness of multi-terminal embedded DC solutions in smoothing the fluctuation of renewable energy output power; Determine an evaluation index for the impact of the multi-terminal embedded DC solution on the voltage support capability of the load center; Determining an impact evaluation index of the multi-terminal embedded DC solution on the primary frequency regulation capability of the load center; An adaptability evaluation of the multi-terminal embedded direct current solution in a target power grid is determined based on the suppression effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index.

2. The method according to claim 1, characterized in that The determining of the adaptability evaluation of the multi-terminal embedded DC solution in the target power grid based on the leveling effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index includes: For a variety of multi-terminal embedded DC schemes, a hierarchical analysis method is used to determine the adaptability evaluation of the multi-terminal embedded DC schemes in the target power grid based on the smoothing effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index, and to rank the adaptability evaluation; wherein, the target power grid has the needs of transmitting new energy and receiving power at the load center.

3. The method according to claim 1, characterized in that The evaluation index for determining the effect of the multi-terminal embedded DC solution on smoothing the fluctuation of renewable energy output power includes: The suppression effect evaluation index is determined based on the following formula: Wherein, χ is the suppression rate of the multi-terminal embedded DC solution on the fluctuation of the power output of renewable energy, and the suppression rate is the evaluation index of the smoothing effect; The maximum fluctuation of the power output of renewable energy within a preset time range; It is the maximum power variation that can be provided by the AC power grid in the vicinity of the new energy source.

4. The method according to claim 1, wherein Determining the impact evaluation index of the multi-terminal embedded DC solution on the voltage support capability of the load center includes: The impact evaluation index of the multi-terminal embedded DC solution on the voltage support capability of the load center is determined based on the following formula: in, is the overall change rate of the voltage support capability of the multi-terminal embedded DC solution to the load center; in, and are the time it takes for the node voltage to recover to 0.95 pu after a fault occurs in the AC line N-1 connected to the i-th critical load node before and after adding the multi-terminal embedded DC solution; is the rate of change of the voltage support capability of the multi-terminal embedded DC solution for the i-th load center, wherein the critical load node is connected to the load center; Among them, A i is the weight coefficient of the i-th load center, A i Greater than or equal to 0 and less than or equal to 1.

5. The method according to claim 1, characterized in that Determining the impact evaluation index of the multi-terminal embedded DC solution on the primary frequency regulation capability of the load center includes: The impact assessment index of the primary frequency modulation capability is determined based on the following formula: Wherein, μ is the rate of change of the primary frequency regulation capability of the load center after adding the multi-terminal embedded DC solution, and the rate of change of the primary frequency regulation capability is an impact assessment indicator of the primary frequency regulation capability; in, Where Δf steady =K f ΔP max ;Δf steady and The maximum frequency deviation of the load center before and after adding the multi-terminal embedded DC solution; K f is the adjustment coefficient; ΔP max and They are the maximum power loss of the load center before and after adding the multi-terminal embedded DC solution, ΔP dc The primary frequency regulation support power provided by the multi-terminal embedded DC solution to the load center.

6. The method according to claim 2, characterized in that The adaptability evaluation of the multi-terminal embedded DC solution in the target power grid is determined by using the analytic hierarchy process, including: Constructing an adaptability evaluation model, the adaptability evaluation model including a target layer, a criterion layer, and a solution layer, wherein the target layer is a multi-terminal embedded DC solution for optimizing the target power grid, the criterion layer includes the volatility of renewable energy output power, the voltage support capability of the load center, and the primary frequency regulation capability of the load center, and the solution layer is a multi-terminal embedded DC solution; Constructing a criterion layer matrix, determining a weight vector of the criterion layer matrix, and performing a consistency check on the criterion layer matrix; For each multi-terminal embedded DC solution, score the implementation effect of each multi-terminal embedded DC solution under each criterion in the criterion layer based on the leveling effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index, and construct a solution layer matrix of the solution layer relative to each criterion in the criterion layer based on the implementation effect scores; Based on the scheme layer matrix, the weight coefficients of the various criteria of the multi-terminal embedded DC scheme in the scheme layer in the criterion layer are determined, and based on the weight vector of the criterion layer matrix and the weight coefficients, the final evaluation result of the adaptability of the multi-terminal embedded DC scheme in the target power grid is determined.

7. The method according to claim 6, characterized in that The criterion layer matrix is: A=(a ij ) n×n ; Among them, a ij >0; Among them, a ij It is expressed as the importance of the i-th criterion relative to the j-th criterion, and n represents the number of criteria in the criterion layer; Correspondingly, the calculation formula of the weight vector of the criterion layer matrix is ​​as follows: in, is the weight vector of the criterion layer matrix; W Ai is the weight coefficient of the ith layer of the criterion layer matrix; Performing a consistency check on the criterion layer matrix includes: performing a consistency check on the criterion layer matrix based on the following formula: in, Among them, CI A is the consistency index of the criterion layer matrix; CR A is the random consistency index of the criterion layer matrix; Amax is the maximum eigenvalue of the criterion layer matrix; if CR A <0.1, indicating that the consistency of the criterion layer matrix is ​​considered to be within the acceptable range; CR A ≥0.1, then the criterion layer matrix is ​​modified; The solution layer matrix is: B p =(b pij ) m×m Among them, B p represents the solution layer matrix corresponding to the pth criterion of the criterion layer; b pij It indicates the importance of the i-th option relative to the j-th option in terms of criterion p; m is the number of options; The calculation formula for determining the weight coefficient of each criterion in the criterion layer for the scheme in the scheme layer is as follows: in, is the weight coefficient of the i-th option in criterion p; The calculation formula for the final evaluation result of the adaptability of the multi-terminal embedded DC solution in the target power grid is as follows: Among them, b i is the final evaluation score of the adaptability of the i-th solution in the target power grid.

8. A multi-terminal embedded DC adaptability evaluation device in a power grid, characterized in that: include: The first determination module is used to determine the evaluation index of the multi-terminal embedded DC solution's effect of smoothing the fluctuation of renewable energy output power; A second determination module is used to determine an evaluation index of the impact of the multi-terminal embedded DC solution on the voltage support capability of the load center; A third determination module is used to determine an impact evaluation index of the multi-terminal embedded DC solution on the primary frequency regulation capability of the load center; An evaluation module is used to determine the adaptability evaluation of the multi-terminal embedded DC solution in the target power grid based on the smoothing effect evaluation index, the voltage support capability impact evaluation index, and the primary frequency regulation capability impact evaluation index.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the computer program is executed in a computer, the computer is caused to execute the method according to any one of claims 1 to 7.

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