Method, system and device for determining transformer area energy storage system and storage medium

Abstract

The invention discloses a transformer area energy storage system determination method, system and device and a storage medium, and the method comprises the steps: constructing a transformer area site selection comprehensive evaluation hierarchical structure model which comprises an index layer, a factor layer and a target layer, each of the index layer and the factor layer comprises a plurality of indexes and weights corresponding to the indexes; obtaining operation data of the transformer area, and determining whether an energy storage system needs to be configured according to the operation data of the transformer area and the transformer area site selection comprehensive evaluation hierarchical structure model; and if the energy storage system needs to be configured, obtaining a transformer area predicted annual maximum load daily curve and a transformer area predicted annual minimum load daily curve, and determining the energy storage capacity of the transformer area energy storage system according to the transformer area predicted annual maximum load daily curve and the transformer area predicted annual minimum load daily curve. The method can more accurately evaluate energy storage system site selection, saves computing resources, improves the operation efficiency of a power system, and can be widely applied to the technical field of power systems.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a method, system, device and storage medium for determining an energy storage system in an electric power substation. Background Art

[0002] Photovoltaic power generation uses sunlight to generate electricity. It is a clean and renewable energy source that does not produce greenhouse gas emissions and helps reduce dependence on fossil fuels. Therefore, the access capacity of photovoltaic power in distribution network systems around the world continues to increase. With the widespread access of distributed photovoltaic power and charging piles, the distribution network system faces a series of challenges such as load fluctuations, equipment overload, voltage over-limit, and power flow reversal. Photovoltaic output depends on variable sources, and it is necessary to combine battery energy storage systems (BESS) with photovoltaic power to convert photovoltaic power into dispatchable resources. Installing BESS in the distribution system in combination with photovoltaic power can reduce system losses, increase system capacity, improve photovoltaic absorption, balance loads, and enhance power supply reliability, but it faces problems such as low utilization, excess capacity, and high cost. The optimal location and capacity configuration of the energy storage system are crucial.

[0003] At present, the research on site selection and sizing of battery energy storage systems is mostly aimed at economic efficiency, and the optimization goal is relatively single, and the site selection is inaccurate. In addition, the site selection and sizing of battery energy storage systems mostly use various artificial intelligence and meta-heuristic methods for optimization. Artificial intelligence algorithms usually require a large amount of historical data to train models, and AI models are complex and require a lot of computing resources. Compared with traditional search algorithms, meta-heuristic algorithms may take more time to converge to the optimal solution, and in some cases, the computational cost of meta-heuristic algorithms is still high. Summary of the invention

[0004] In view of this, the purpose of the embodiments of the present invention is to provide a method, system, device and storage medium for determining a substation energy storage system, which can more accurately evaluate the site selection of the energy storage system, save computing resources, and improve the operating efficiency of the power system.

[0005] On the one hand, an embodiment of the present invention provides a method for determining a regional energy storage system, comprising:

[0006] Constructing a hierarchical structure model for comprehensive evaluation of substation site selection, wherein the hierarchical structure model for comprehensive evaluation of substation site selection includes an indicator layer, a factor layer and a target layer, wherein both the indicator layer and the factor layer include a number of indicators and weights corresponding to the indicators;

[0007] Acquire the operation data of the substation area, and determine whether it is necessary to configure an energy storage system according to the operation data of the substation area and the hierarchical structure model of comprehensive evaluation of the substation area site selection;

[0008] If it is necessary to configure an energy storage system, obtain the daily curve of the maximum load in the predicted year and the daily curve of the minimum load in the predicted year, and determine the energy storage capacity of the energy storage system in the substation based on the daily curve of the maximum load in the predicted year and the daily curve of the minimum load in the predicted year.

[0009] Optionally, determining whether to configure an energy storage system according to the operation data of the substation and the substation site selection comprehensive evaluation hierarchical structure model includes:

[0010] Normalizing the operation data of the substation according to the indicators of the indicator layer to obtain normalized data;

[0011] Determining a fuzzy evaluation matrix according to the normalized data and a preset membership function;

[0012] A comprehensive fuzzy evaluation matrix is ​​determined according to the fuzzy evaluation matrix and the weights, and whether an energy storage system needs to be configured is determined according to the comprehensive fuzzy evaluation matrix.

[0013] Optionally, normalizing the operation data of the substation according to the indicators of the indicator layer to obtain normalized data includes:

[0014] Determine a first function and a second function according to the indicators of the indicator layer;

[0015] Acquire first type data and second type data according to the operation data of the station area;

[0016] The first type of data is normalized using the first function, and the second type of data is normalized using the second function to obtain normalized data.

[0017] Optionally, determining whether an energy storage system needs to be configured according to the comprehensive fuzzy evaluation matrix includes:

[0018] If the probability of the comprehensive operating state in the comprehensive fuzzy evaluation matrix being very poor is the highest, it is necessary to configure an energy storage system; the comprehensive operating state includes any one of normal, general, poor or very poor;

[0019] Otherwise, there is no need to configure an energy storage system.

[0020] Optionally, determining the energy storage capacity of the energy storage system in the substation area according to the daily curve of the predicted annual maximum load of the substation area and the daily curve of the predicted annual minimum load of the substation area includes:

[0021] Determine the first energy storage capacity according to the predicted annual maximum load daily curve of the substation;

[0022] Determine the second energy storage capacity according to the predicted annual minimum load daily curve of the substation;

[0023] The larger value between the first energy storage capacity and the second energy storage capacity is determined as the energy storage capacity of the substation energy storage system.

[0024] Optionally, determining the first energy storage capacity according to the predicted annual maximum load daily curve of the substation includes:

[0025] Determine the peak and valley time periods according to the predicted annual maximum load daily curve of the substation area, determine the capacity difference of each peak and valley time period according to the preset adjustment power, and determine the charge and discharge power of each peak and valley time period according to the capacity difference;

[0026] The first energy storage capacity is determined according to the maximum value of the charge and discharge quantities in all peak and valley time periods.

[0027] Optionally, the adjusted power is determined by the following method:

[0028] Determine the power over-limit value and proportional factor of the substation;

[0029] The regulated power is determined according to the power over-limit value and the proportional factor.

[0030] On the other hand, an embodiment of the present invention provides a system for determining a substation energy storage system, including:

[0031] The first module is used to construct a hierarchical structure model for comprehensive evaluation of substation site selection, wherein the hierarchical structure model for comprehensive evaluation of substation site selection includes an indicator layer, a factor layer and a target layer, wherein both the indicator layer and the factor layer include a number of indicators and weights corresponding to the indicators;

[0032] The second module is used to obtain the operation data of the substation area, and determine whether it is necessary to configure the energy storage system according to the operation data of the substation area and the hierarchical structure model of comprehensive evaluation of the substation area site selection;

[0033] The third module is used to obtain the predicted annual maximum load daily curve and the predicted annual minimum load daily curve of the substation if the energy storage system needs to be configured, and determine the energy storage capacity of the substation energy storage system based on the predicted annual maximum load daily curve and the predicted annual minimum load daily curve of the substation.

[0034] On the other hand, an embodiment of the present invention provides a device for determining a substation energy storage system, including:

[0035] at least one processor;

[0036] at least one memory for storing at least one program;

[0037] When the at least one program is executed by the at least one processor, the at least one processor implements the above method.

[0038] On the other hand, an embodiment of the present invention provides a storage medium, in which a program executable by a processor is stored. When the program executable by the processor is executed by the processor, it is used to perform the above method.

[0039] The implementation of the embodiment of the present invention includes the following beneficial effects: In the present embodiment, firstly, a hierarchical structure model for comprehensive evaluation of substation site selection is constructed, and the hierarchical structure model for comprehensive evaluation of substation site selection includes an indicator layer, a factor layer and a target layer, and both the indicator layer and the factor layer include a number of indicators and weights corresponding to the indicators. Then, the operation data of the substation is obtained, and it is determined whether an energy storage system needs to be configured based on the operation data of the substation and the hierarchical structure model for comprehensive evaluation of substation site selection. If an energy storage system needs to be configured, a comprehensive evaluation of the operation status of the substation is performed from multiple dimensions, and it can be flexibly adjusted according to different evaluation standards and weights, and is suitable for various complex and multi-factor evaluation problems. The evaluation factors and weights can be adjusted according to the specific local conditions and policy requirements. Compared with some complex Artificial intelligence models usually require less computing resources and time, and are therefore more cost-effective. They obtain the predicted annual maximum load daily curve and the predicted annual minimum load daily curve of the substation, and determine the energy storage capacity of the substation energy storage system based on the predicted annual maximum load daily curve and the predicted annual minimum load daily curve of the substation. The energy storage capacity analysis algorithm with the goal of peak shaving and valley filling can effectively absorb the output peak and load peak of distributed photovoltaic resources, meet the power grid's demand for energy storage systems, and improve the operating efficiency of the power system. The calculation is relatively simple and easy to program. It does not require complex models and a large amount of computing resources. At the same time, it takes into account the load growth margin and can adapt to load changes in different seasons and time periods, and is suitable for a variety of different application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic flow chart of the steps of a method for determining a district energy storage system provided by an embodiment of the present invention;

[0041] Figure 2 is a schematic flow chart of steps of another method for determining a district energy storage system provided by an embodiment of the present invention;

[0042] Figure 3 is a schematic diagram of a single peak curve energy storage configuration provided by an embodiment of the present invention;

[0043] Figure 4 is a schematic diagram of a multi-peak curve energy storage configuration provided by an embodiment of the present invention;

[0044] Figure 5 It is a schematic diagram of a process flow of determining the energy storage capacity of an area energy storage system provided by an embodiment of the present invention;

[0045] Figure 6is a structural block diagram of a determination system of a district energy storage system provided by an embodiment of the present invention;

[0046] Figure 7 It is a structural block diagram of a determination device for a district energy storage system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The step numbers in the following embodiments are only provided for the convenience of explanation and description, and the order between the steps is not limited in any way. The execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0048] like Figure 1 As shown, an embodiment of the present invention provides a method for determining a substation energy storage system, including the following steps S100 to S300.

[0049] S100. Construct a hierarchical structure model for comprehensive evaluation of substation site selection. The hierarchical structure model for comprehensive evaluation of substation site selection includes an indicator layer, a factor layer and a target layer. Both the indicator layer and the factor layer include a number of indicators and their corresponding weights.

[0050] The evaluation system for the site selection of the energy storage system in the substation is complex and has many factors, and it is necessary to comprehensively consider factors such as the substation operating status, load demand, and economy. The comprehensive evaluation system for the substation mainly analyzes the substation load characteristics, substation line loss, substation heavy overload, photovoltaic absorption rate, load peak-to-valley difference, and substation voltage over-limit, and establishes a hierarchical structure model for the comprehensive evaluation of the substation site. Starting from the analysis of the substation operating status indicators, the membership function is used to determine the status of each underlying indicator in the evaluation concentration, and the importance of each item in the indicator layer and factor layer is determined by weight value calculation. It should be noted that the indicators of the indicator layer and the factor layer and the corresponding weights of the indicators are determined according to the actual application, and this embodiment does not make specific restrictions.

[0051] Referring to Table 1, in a specific embodiment, the target layer is the comprehensive operating status of the substation, the factor layer includes heavy overload conditions, photovoltaic absorption, voltage over-limit, peak-to-valley difference and line loss, the indicators of the indicator layer corresponding to the heavy overload condition include heavy load days, overload days, reverse heavy load days and reverse overload days, the indicators of the indicator layer corresponding to photovoltaic absorption include the minimum photovoltaic absorption rate, the average photovoltaic absorption rate and the photovoltaic reverse transmission days, the indicators of the indicator layer corresponding to the voltage over-limit include the maximum value of the upper limit deviation, the maximum value of the lower limit deviation, the duration of the voltage over-limit and the duration of the voltage over-limit, the indicators of the indicator layer corresponding to the peak-to-valley difference include the maximum value of the daily peak-to-valley difference rate and the average value of the peak-to-valley difference rate, and the indicators of the indicator layer corresponding to the line loss include the maximum value of the daily line loss rate and the number of days with abnormal line loss.

[0052] Table 1

[0053]

[0054]

[0055] The input of the hierarchical structure model for comprehensive evaluation of substation site selection is the index data of the index layer. The index data of the input index layer is calculated by the hierarchical structure model for comprehensive evaluation of substation site selection. The output of the target layer of the hierarchical structure model for comprehensive evaluation of substation site selection is the comprehensive operation status of the substation.

[0056] S200: Obtain the operation data of the substation, and determine whether it is necessary to configure an energy storage system based on the operation data of the substation and the hierarchical structure model for comprehensive evaluation of the substation site selection.

[0057] The operation data of the substation is obtained, and the corresponding input data is selected from the operation data of the substation according to the input of the hierarchical structure model for comprehensive evaluation of the substation site selection. The hierarchical structure model for comprehensive evaluation of the substation site selection calculates the comprehensive operation status of the substation according to the input data, and determines whether the energy storage system needs to be configured according to the comprehensive operation status of the substation.

[0058] S300: If it is necessary to configure an energy storage system, obtain the daily curve of the maximum load in the predicted year and the daily curve of the minimum load in the predicted year, and determine the energy storage capacity of the energy storage system in the predicted year according to the daily curve of the maximum load in the predicted year and the daily curve of the minimum load in the predicted year.

[0059] If it is determined that an energy storage system needs to be configured based on the hierarchical structure model of comprehensive evaluation of substation site selection, first, obtain the substation's predicted annual maximum load daily curve and the substation's predicted annual minimum load daily curve. Then, determine the energy storage capacity corresponding to the substation's energy storage system based on the substation's predicted annual maximum load daily curve and the substation's predicted annual minimum load daily curve. Finally, determine the final energy storage capacity of the substation's energy storage system based on the energy storage capacity determined by different load curves.

[0060] Optionally, whether to configure an energy storage system is determined based on the operation data of the substation and the hierarchical structure model for comprehensive evaluation of the substation site selection, including:

[0061] S210, normalizing the operation data of the substation according to the indicators of the indicator layer to obtain normalized data.

[0062] Different indicators have different impacts on the indicator layer. For example, some indicators are rising indicators, while some indicators are falling indicators. The larger the rising indicator, the worse the operating status, such as heavy overload, voltage limit, peak-to-valley difference, photovoltaic reverse transmission days, line loss correlation, etc.; the larger the falling indicator, the better the operating status, such as photovoltaic absorption rate, etc. In order to facilitate calculation, the operation data of the substation is normalized.

[0063] Optionally, the operation data of the substation is normalized according to the indicators of the indicator layer to obtain normalized data, including:

[0064] S211, determining a first function and a second function according to the indicators of the indicator layer;

[0065] S212, acquiring first type data and second type data according to the operation data of the substation;

[0066] S213: normalize the first type of data using a first function, and normalize the second type of data using a second function to obtain normalized data.

[0067] The first function corresponds to an ascending indicator, and the first function uses a larger function. The second function corresponds to a descending indicator, and the second function uses a larger function. The first type of data refers to data belonging to an ascending indicator, and the second type of data refers to data belonging to a descending indicator.

[0068] In a specific embodiment, the first function is calculated using the following formula (1), and the second function is calculated using the following formula (2).

[0069]

[0070] Among them, a and b are constants, x i represents the data before normalization, and x represents the normalized data.

[0071] S220, determining a fuzzy evaluation matrix according to the normalized data and a preset membership function.

[0072] It should be noted that the membership function is determined according to actual application, and this embodiment does not impose any specific restrictions. The membership function is determined according to the comprehensive operation status of the substation area.

[0073] In a specific embodiment, the degree to which each indicator of the indicator layer belongs to the four states in the evaluation set V = {normal, average, poor, very poor} is determined by using a membership function A = {A v1 (x),A v2 (x),A v3 (x), A v4 (x)}, considering that the main value interval is widely distributed, a semi-trapezoidal and semi-ridge membership function formula (3-6) is adopted.

[0074]

[0075]

[0076] Among them, x represents normalized data. After the normalized data of multiple indicators in the indicator layer are matrixed according to the results of the membership function calculation, a fuzzy evaluation matrix is ​​formed.

[0077] The indicator layer membership matrices of the same type of factors are combined to obtain the factor layer fuzzy evaluation matrix R. In a specific embodiment, the factor layer includes a heavy overload X 1 , Photovoltaic consumption rate X 2 、Voltage exceeds limit X 3 , peak-to-valley difference X 4 , Line loss rate X 5 , we can get the five-factor fuzzy evaluation matrix R xi :

[0078]

[0079] Among them, i is [1,2,3,4,5], which is the number of factor layers, j is the number of indicators in each factor layer, and a j1 It indicates the probability of the substation belonging to the first comprehensive operation state according to the jth index, a j2 It indicates the probability of the substation belonging to the second comprehensive operation state according to the jth index, a j3 It indicates the probability of the substation belonging to the third comprehensive operation state according to the jth index, a j4 It represents the probability that the substation belongs to the fourth comprehensive operating state according to the jth indicator.

[0080] S230, determining a comprehensive fuzzy evaluation matrix according to the fuzzy evaluation matrix and the weights, and determining whether an energy storage system needs to be configured according to the comprehensive fuzzy evaluation matrix.

[0081] To establish a hierarchical model, it is necessary to give each level a reasonable weight to correctly reflect their different degrees of influence in the same level evaluation. In this embodiment, through the decision analysis of multiple expert groups, the weights of each level index are assigned by the expert scoring method. The factor level index adopts the five factor level fuzzy evaluation matrix R calculated. X1、 R X2、 R X3、 R X4、 R X5 , the weight of each indicator is ω i , multiply the membership degree and the weight to obtain the index layer comprehensive fuzzy evaluation matrix B xi , whose matrix contains the original b ij The calculation method of is as follows:

[0082]

[0083] Among them, i is the factor number with a value of [1,2,3,4,5], j is the number of indicators in each factor layer, and w ijrepresents the weight of the jth indicator in the i-th factor layer, r ij The fuzzy evaluation matrix of the jth indicator of the i-th factor layer belonging to each operating state of the substation is obtained. The comprehensive evaluation matrix B of the five indicator layers is obtained. X1 , B X2 , B x3 , B X4 , B X5 , using fuzzy algorithm calculation, as shown in formula (9), the comprehensive fuzzy evaluation matrix B can be obtained:

[0084]

[0085] Among them, w x1 represents the weight of the first factor layer, w x2 represents the weight of the second factor layer, w x3 represents the weight of the third factor layer, w x4 represents the weight of the fourth factor layer, w x5 represents the weight of the fifth factor layer, V 1 represents the probability of belonging to the first area comprehensive operation state, V 2 represents the probability of belonging to the comprehensive operation state of the second substation, V 3 represents the probability of belonging to the comprehensive operation state of the third substation, V 4 Indicates the probability of belonging to the fourth zone comprehensive operation status.

[0086] Optionally, determining whether to configure an energy storage system according to a comprehensive fuzzy evaluation matrix includes:

[0087] S241. If the probability of the comprehensive operating state in the comprehensive fuzzy evaluation matrix being very poor is the highest, an energy storage system needs to be configured; the comprehensive operating state includes any one of normal, general, poor or very poor;

[0088] S242. Otherwise, there is no need to configure an energy storage system.

[0089] Specifically, {V 1 ,V 2 ,V 3 ,V 4 The corresponding comprehensive operation status of the substation belongs to the four states of {normal, general, poor, very poor}. According to the principle of maximum membership, the state with the highest proportion is {very poor}, and the corresponding energy storage site selection state gives suggestions on the need to configure the energy storage system; in other cases, such as when the comprehensive operation status of the substation is normal, general or poor, there is no need to configure the energy storage system.

[0090] In a specific embodiment, see Figure 2First, a hierarchical model for comprehensive evaluation of substation site selection is established to determine the result set of comprehensive evaluation of substation site selection, and the weight of the indicator layer and the weight of the factor layer are determined according to the expert score of the indicator importance; then, the operation data of the substation is obtained, the operation data of the substation is normalized, the membership function of the indicator layer is determined, and the fuzzy matrix of the indicator layer is established according to the membership function and the normalized data; then, the comprehensive fuzzy matrix of the indicator layer is calculated according to the fuzzy matrix of the indicator layer and the weight of the indicator layer, and the comprehensive fuzzy matrix of the substation site selection is calculated according to the comprehensive fuzzy matrix of the indicator layer and the weight of the factor layer; finally, the evaluation result is determined according to the comprehensive fuzzy matrix of the substation site selection, that is, whether the substation needs to be configured with an energy storage system.

[0091] The energy storage capacity configuration principle of the regional energy storage system is as follows: Assuming P max For load peaks, after energy storage is configured on the user side, the capacity of the distribution transformer in the substation area changes from S 0 Drop to S1, configuring energy storage needs to reduce the maximum load (peak) on the user side to S 1 , assuming that the configured energy storage capacity is A, the configuration principle of A should follow the following principles:

[0092] (1) Configuration of energy storage capacity under single peak load: see Figure 3 , the rated capacity of the distribution transformer in the substation is S 1 At peak load, it is necessary to ensure that there is sufficient energy storage capacity A when the load is greater than S 1 The maximum load of the distribution transformer can be reduced to S 1 The red shaded area is the minimum energy storage capacity required to reduce the peak load, and the reduced peak height is the minimum discharge power of the energy storage.

[0093] (2) Configuration of energy storage capacity A under multi-peak load: Figure 4 When the load characteristics are multi-peak characteristics, it is necessary to consider whether the energy storage can be fully charged in the time interval between peak loads. When the time interval is not enough to fully charge the energy, the planned energy storage capacity needs to be increased. The red part is the discharge energy at the peak of the energy storage, and the green part is the rechargeable energy between the two peaks. Then the energy storage capacity A 1 must be greater than the discharge energy of each peak; at the same time, considering the charging process between different peaks, the energy storage capacity A 1 Should also be greater than T start With T end Load P in time load The integral value of the difference between (m, t) and the transformer capacity S1, that is, the energy corresponding to the total area of ​​the red part minus the area of ​​the green part.

[0094] Optionally, the energy storage capacity of the energy storage system in the substation area is determined according to the daily curve of the maximum load in the substation area and the daily curve of the minimum load in the substation area, including:

[0095] S310, determining the first energy storage capacity according to the predicted annual maximum load daily curve of the substation;

[0096] S320, determining the second energy storage capacity according to the predicted annual minimum load daily curve of the substation;

[0097] S330: Determine the larger value of the first energy storage capacity and the second energy storage capacity as the energy storage capacity of the substation energy storage system.

[0098] Each load curve corresponds to a different energy storage capacity. The annual maximum load day curve corresponds to the first energy storage capacity, and the annual minimum load day curve corresponds to the second energy storage capacity. The first energy storage capacity and the second energy storage capacity can cover the annual energy storage capacity change demand; finally, the larger value of the first energy storage capacity and the second energy storage capacity is determined as the energy storage capacity of the substation energy storage system, thereby meeting the annual energy storage capacity demand.

[0099] Optionally, determining the first energy storage capacity according to the predicted annual maximum load daily curve of the substation area includes:

[0100] S311, determine the peak and valley time period according to the predicted annual maximum load daily curve of the substation area, determine the capacity difference of each peak and valley time period according to the preset adjustment power, and determine the charge and discharge power of each peak and valley time period according to the capacity difference;

[0101] S312: Determine a first energy storage capacity according to a maximum value of the charge and discharge quantities in all peak and valley time periods.

[0102] It should be noted that the regulated power is determined according to actual application, and this embodiment does not impose any specific restrictions. The capacity difference refers to the difference between the peak value of the load and the regulated power or the difference between the regulated power and the low peak value of the load.

[0103] In a specific embodiment, see Figure 5 First, the predicted annual maximum load daily curve of the substation is selected as the basic data, the energy storage capacity is initialized, the peak and valley periods of the benchmark regulation power and load curve are determined, and the capacity difference ΔP of the peak / valley period of each period is determined according to the regulation power. k (t), then calculate the peak period / valley period integrated charge and discharge power S according to the following formula (10): j .

[0104]

[0105] Then, the charging and discharging power between adjacent peak / valley value sections is further determined. Starting from midnight every day, according to the charging power required during the peak / valley value period, the energy storage charging / discharging power during the flat value period is determined in sequence, and then the charging and discharging power is combined according to the multi-peak principle to obtain Ci, and the energy storage capacity is determined as E. 1=max{Ci}.

[0106] Those skilled in the art can understand that the specific method for determining the second energy storage capacity based on the predicted annual minimum load daily curve of the substation can be analogized to the calculation method of the first energy storage capacity.

[0107] Optionally, the regulated power is determined by:

[0108] S3111, determining the power over-limit value and proportional factor of the substation;

[0109] S3112. Determine the adjustment power according to the power over-limit value and the proportional factor.

[0110] First, select the power limit value P M The proportional factor λ can be considered comprehensively based on the photovoltaic access capacity and load growth of the substation, and the general value range is 0.8-0.95. Then, according to the adjustment power P base =λP M Determine the peak / valley period ΔP for each period k (t).

[0111] The implementation of the embodiment of the present invention includes the following beneficial effects: In the present embodiment, firstly, a hierarchical structure model for comprehensive evaluation of substation site selection is constructed, and the hierarchical structure model for comprehensive evaluation of substation site selection includes an indicator layer, a factor layer and a target layer, and both the indicator layer and the factor layer include a number of indicators and weights corresponding to the indicators. Then, the operation data of the substation is obtained, and it is determined whether an energy storage system needs to be configured based on the operation data of the substation and the hierarchical structure model for comprehensive evaluation of substation site selection. If an energy storage system needs to be configured, a comprehensive evaluation of the operation status of the substation is performed from multiple dimensions, and it can be flexibly adjusted according to different evaluation standards and weights, and is suitable for various complex and multi-factor evaluation problems. The evaluation factors and weights can be adjusted according to the specific local conditions and policy requirements. Compared with some complex Artificial intelligence models usually require less computing resources and time, and are therefore more cost-effective. They obtain the predicted annual maximum load daily curve and the predicted annual minimum load daily curve of the substation, and determine the energy storage capacity of the substation energy storage system based on the predicted annual maximum load daily curve and the predicted annual minimum load daily curve of the substation. The energy storage capacity analysis algorithm with the goal of peak shaving and valley filling can effectively absorb the output peak and load peak of distributed photovoltaic resources, meet the power grid's demand for energy storage systems, and improve the operating efficiency of the power system. The calculation is relatively simple and easy to program. It does not require complex models and a large amount of computing resources. At the same time, it takes into account the load growth margin and can adapt to load changes in different seasons and time periods, and is suitable for a variety of different application scenarios.

[0112] See also Figure 6 The embodiment of the present invention provides a system for determining a regional energy storage system, including:

[0113] The first module is used to construct a hierarchical structure model for comprehensive evaluation of substation site selection. The hierarchical structure model for comprehensive evaluation of substation site selection includes an indicator layer, a factor layer and a target layer. Both the indicator layer and the factor layer include several indicators and their corresponding weights.

[0114] The second module is used to obtain the operation data of the substation area and determine whether the energy storage system needs to be configured based on the operation data of the substation area and the hierarchical structure model of comprehensive evaluation of the substation area site selection;

[0115] The third module is used to obtain the predicted annual maximum load daily curve and the predicted annual minimum load daily curve of the substation area if the energy storage system needs to be configured, and determine the energy storage capacity of the substation area energy storage system based on the predicted annual maximum load daily curve and the predicted annual minimum load daily curve of the substation area.

[0116] It can be seen that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0117] See also Figure 7 , an embodiment of the present invention provides a device for determining a substation energy storage system, comprising:

[0118] at least one processor;

[0119] at least one memory for storing at least one program;

[0120] When at least one program is executed by at least one processor, the at least one processor implements the above method.

[0121] It can be seen that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0122] In addition, the embodiment of the present application also discloses a computer program product or a computer program, and the computer program product or the computer program is stored in a computer-readable storage medium. The processor of the computer device can read the computer program from the computer-readable storage medium, and the processor executes the computer program, so that the computer device performs the above method. Similarly, the contents in the above method embodiment are all applicable to the storage medium embodiment, and the functions specifically implemented by the storage medium embodiment are the same as those in the above method embodiment, and the beneficial effects achieved are also the same as those achieved by the above method embodiment.

[0123] The above is a specific description of the preferred implementation of the present invention, but the invention is not limited to the embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A method for determining an energy storage system in an area, characterized in that: include: Constructing a hierarchical structure model for comprehensive evaluation of substation site selection, wherein the hierarchical structure model for comprehensive evaluation of substation site selection includes an indicator layer, a factor layer and a target layer, wherein both the indicator layer and the factor layer include a number of indicators and weights corresponding to the indicators; Acquire the operation data of the substation area, and determine whether it is necessary to configure an energy storage system according to the operation data of the substation area and the hierarchical structure model of comprehensive evaluation of the substation area site selection; If it is necessary to configure an energy storage system, obtain the daily curve of the maximum load in the predicted year and the daily curve of the minimum load in the predicted year, and determine the energy storage capacity of the energy storage system in the substation based on the daily curve of the maximum load in the predicted year and the daily curve of the minimum load in the predicted year.

2. The method according to claim 1, characterized in that: Determining whether to configure an energy storage system according to the operation data of the substation and the hierarchical structure model of comprehensive evaluation of the substation site selection includes: Normalizing the operation data of the substation according to the indicators of the indicator layer to obtain normalized data; Determining a fuzzy evaluation matrix according to the normalized data and a preset membership function; A comprehensive fuzzy evaluation matrix is ​​determined according to the fuzzy evaluation matrix and the weights, and whether an energy storage system needs to be configured is determined according to the comprehensive fuzzy evaluation matrix.

3. The method according to claim 2, characterized in that The operation data of the substation is normalized according to the index of the index layer to obtain normalized data, including: Determine a first function and a second function according to the indicators of the indicator layer; Acquire first type data and second type data according to the operation data of the station area; The first type of data is normalized using the first function, and the second type of data is normalized using the second function to obtain normalized data.

4. The method according to claim 1, characterized in that Determining whether an energy storage system needs to be configured according to the comprehensive fuzzy evaluation matrix includes: If the probability of the comprehensive operating state in the comprehensive fuzzy evaluation matrix being very poor is the highest, it is necessary to configure an energy storage system; the comprehensive operating state includes any one of normal, general, poor or very poor; Otherwise, there is no need to configure an energy storage system.

5. The method according to claim 1, characterized in that The determining the energy storage capacity of the energy storage system in the substation area according to the substation area predicted annual maximum load daily curve and the substation area predicted annual minimum load daily curve comprises: Determine the first energy storage capacity according to the predicted annual maximum load daily curve of the substation; Determine the second energy storage capacity according to the predicted annual minimum load daily curve of the substation; The larger value between the first energy storage capacity and the second energy storage capacity is determined as the energy storage capacity of the substation energy storage system.

6. The method according to claim 5, characterized in that Determining the first energy storage capacity according to the predicted annual maximum load daily curve of the substation area includes: Determine the peak and valley time periods according to the predicted annual maximum load daily curve of the substation area, determine the capacity difference of each peak and valley time period according to the preset adjustment power, and determine the charge and discharge power of each peak and valley time period according to the capacity difference; The first energy storage capacity is determined according to the maximum value of the charge and discharge quantities in all peak and valley time periods.

7. The method according to claim 6, characterized in that The regulated power is determined by the following method: Determine the power over-limit value and proportional factor of the substation; The regulated power is determined according to the power over-limit value and the proportional factor.

8. A system for determining an energy storage system in an area, characterized in that: include: The first module is used to construct a hierarchical structure model for comprehensive evaluation of substation site selection, wherein the hierarchical structure model for comprehensive evaluation of substation site selection includes an indicator layer, a factor layer and a target layer, wherein both the indicator layer and the factor layer include a number of indicators and weights corresponding to the indicators; The second module is used to obtain the operation data of the substation area, and determine whether it is necessary to configure the energy storage system according to the operation data of the substation area and the hierarchical structure model of comprehensive evaluation of the substation area site selection; The third module is used to obtain the predicted annual maximum load daily curve and the predicted annual minimum load daily curve of the substation if the energy storage system needs to be configured, and determine the energy storage capacity of the substation energy storage system based on the predicted annual maximum load daily curve and the predicted annual minimum load daily curve of the substation.

9. A device for determining a substation energy storage system, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 7.

10. A storage medium storing a program executable by a processor, characterized in that: The processor-executable program is used to perform the method according to any one of claims 1 to 7 when executed by the processor.

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