Flexible interconnection device addressing and sizing method oriented to maximum power supply income improvement

Abstract

The invention discloses a flexible interconnection device locating and sizing method for maximum power supply income improvement, and belongs to the technical field of power distribution network planning. According to the flexible interconnection device locating and sizing method oriented to the maximum power supply income improvement, the influence of the access position and capacity of the flexible interconnection device on the maximum power supply income of a flexible interconnection system is fully considered, and the optimal locating and sizing strategy of the flexible interconnection device is obtained through solving. According to the method, the optimization of the load balancing index of the power distribution network is taken as a target, a feeder line mutual aid potential optimization model oriented to the load balancing capacity is constructed to determine the optimal access position of the SOP, and then the SOP constant-capacity addressing and constant-capacity strategy is mainly determined by load increment setting, constant-capacity optimization model construction and addressing and constant-capacity scheme determination. According to the method, the influence of the access position and capacity of the flexible interconnection device on the maximum power supply benefit of the flexible interconnection system is explored, and reference is expected to be provided for guiding a planning scheme of the flexible interconnection power distribution network.

Description

Technical Field

[0001] This invention belongs to the field of power distribution network planning technology. Background Technology

[0002] As a key hub connecting the main grid and users, the distribution network is facing problems such as uneven load distribution and insufficient load supply caused by the large-scale access of new low-carbon loads such as distributed photovoltaic, electric vehicles, energy storage and electric heating, which poses a severe challenge to the planning and operation of the distribution network.

[0003] To advance the construction of flexible interconnected distribution networks, existing research has focused on load balancing and optimized dispatching. However, a lack of research on site selection and capacity allocation strategies for flexible interconnected devices aimed at maximizing load supply remains a gap. Current research largely focuses on voltage and network loss optimization, lacking configuration methods with the core objective of enhancing power supply capacity. Given the high penetration of distributed energy resources and the widespread integration of flexible loads, conducting research on the optimized configuration of flexible interconnected devices to enhance load supply is of great significance for improving the economy and reliability of distribution networks. Summary of the Invention

[0004] The purpose of this invention is to fully consider the impact of the access location and capacity of flexible interconnect devices on the maximum power supply benefits of flexible interconnect systems, and to provide a flexible interconnect device location and capacity determination method aimed at improving the maximum power supply benefits by solving for the optimal location and capacity determination strategy of flexible interconnect devices.

[0005] The steps of this invention are: S1. Construct a feeder mutual assistance potential optimization model oriented towards load balancing capabilities: S11. After obtaining the 24-hour normalized average load rate of the main feeder of each transformer area using equation (1), the transformer areas are classified according to the light and heavy load conditions based on the conditions described in equation (2): (1) (2) In the formula, The normalized average load rate of the main feeder line k in the transformer area over 24 hours. The normalized load rate of the i-th section of the main feeder in transformer area k over 24 hours. The total number of main feeders in the k-type transformer area. Let t be the load rate of the i-th segment of the main feeder in area k during time period t. This is the weighting factor for the load rate of each hour within a day. This represents the total number of stations within the system. S12, Select Minimum in the set The value corresponds to the end node of the feeder and Largest in the set The corresponding feeder end nodes are interconnected. As shown in equation (3): (3) In the formula, The normalized redundancy capacity of the i-th main feeder in transformer area k for 24 hours. This represents the maximum capacity of the main feeder line in area k. Let be the capacity of the i-th main feeder in transformer area k. S13. The feeder mutual support capability is initially determined using the 24-hour normalized average load rate of the branch lines. The steps are as follows: S131. The normalized average load rate of each substation branch feeder over 24 hours is calculated using equation (4); secondly, the feeder characteristics are classified according to the conditions described in equation (5) based on light and heavy load conditions: (4) (5) In the formula, The normalized average load rate of the feeder of branch k in the transformer area over 24 hours. Normalized load rate of the i-th branch feeder in transformer area k over 24 hours. Let t be the load rate of the i-th segment of the main feeder in area k during time period t. The load factor for each hour of the day; This represents the total number of feeders in the k-branch area of ​​the transformer substation. S132, to The elements in the set are ordered Sort the values ​​in descending order and select the first two elements of the sequence as negative nodes to be interconnected; similarly, for The elements in the set are ordered Sort the values ​​in ascending order and select the first two elements in the sequence as the nodes to be interconnected. The calculation steps are shown in equation (6): (6) In the formula, The normalized redundancy capacity of the i-th branch feeder in transformer area k is given by [reference to a specific function / name]. Let i be the maximum capacity of the feeder segment i of the k-branch feeder in the transformer area. Let i be the capacity of the i-th branch feeder in transformer area k; S14. Based on the obtained nodes to be interconnected, combine them according to the following rules to obtain the preliminary SOP location scheme: S141. Considering that internal interconnection violates the principle of location and capacity economy, it is stipulated that at most one node can be selected for interconnection within the same branch feeder. S142. It is specified that each interconnection scheme of the branch feeder includes two positive interconnection nodes and one negative interconnection node. S15. The preliminary location scheme of the distribution network SOP device is imported into an optimization model with the objective of minimizing the weighted average load balance index between distribution units and between feeders. The objective function is: (7) In the formula, The 24-hour normalized load balance index. and These are the load balance index of the main feeder between transformer stations and the load balance index between branch feeders within the transformer station during time period t. and These are the weighting coefficients for the load balancing index of the main feeder between transformer substations and the weighting coefficients for the load balancing index of the branch feeder within the transformer substation. The load factor is the weighting factor for the load rate of each hour within a day; T is the number of time periods. The load balancing index between branch feeders within the transformer area is: (8) In the formula, The number of branch feeders in transformer area j; Let i be the set of downstream nodes of feeder i; The load connected to node u during time period t; Let be the maximum transmission power of the i-th branch feeder; The balance index of the main feeder between stations is: (9) In the formula, This represents the total number of backbone feeders for all flexible interconnected transformer substations. The set of downstream branches of the main feeder i; The total load connected to the branch feeder v during time period t; Let be the maximum transmission power of the i-th main feeder; S16. The safety constraints for optimizing the model operation can be simplified as shown in the following formula: (10) In the formula, The load carried by transformer i; The net load carried by feeder section m; This indicates that feeder segment m originates from the busbar corresponding to transformer i; The net load carried by feeder section m; The feeder segment m connects to the shared energy storage device to provide power output; The network loss is for feeder segment m. This refers to the rated capacity of transformer i. The rated capacity of feeder segment m; The voltage amplitude at node r; , These are the lower and upper limits of the node voltage, respectively. , The discharge and charging power of the shared energy storage device t connected to feeder segment m are respectively the discharge and charging power during time period t. S17. Considering port capacity constraints, the transmission power of the i-th port of SOP... It should be smaller than its own capacity. : (11) SOP satisfies the active power conservation constraint: (12) In the formula, This is the set of all ports for the SOP; S18. The operating constraints for shared energy storage devices are as follows: (13) (14) (15) (16) In the formula, The shared energy storage device's charge capacity during time period t; and These represent the charging power and discharging power of the shared energy storage device during time period t, respectively. and These are charging efficiency and discharging efficiency, respectively. and These are the minimum and maximum charge values ​​of the shared energy storage device, respectively. and These are the charging and discharging state variables of the shared energy storage device, respectively. and These are the maximum charging power and maximum discharging power of the shared energy storage device, respectively. S2. Grid operation revenue mainly includes the load growth potential after the flexible interconnection device is connected. Revenue from electricity sales Total cost of SOP device construction and maintenance And the total cost of construction and maintenance of energy storage devices. Among them, the potential for load growth With maximum load supply The relationship is: (17) In the formula, The original basic load of the i-th node during time period j; n is the total number of nodes in the system; objective function for: (18) In the formula, Let j be the electricity price for the i-th node during time period j. Total revenue from power grid operation; The specific calculation formula is as follows: (19) (20) In the formula, The fixed investment cost is calculated per year based on the SOP. d is the annual maintenance cost of the SOP; y is the discount rate; and y is the economic lifespan of the SOP. The unit capacity investment cost of SOP; SOP installation capacity; This is the annual maintenance cost coefficient for SOP; , These are the initial investment cost and operation and maintenance cost of the energy storage system, respectively. is the investment discount factor; k is the discount rate; z is the lifespan of the energy storage system; The unit capacity investment cost of the energy storage system; The equivalent coefficient for the operation and maintenance cost of energy storage devices; Based on the above objective function and constraints, after obtaining the specific capacities of SOP and ESS in the capacity determination section, these are substituted back into the location optimization model section to replace the initial capacities of SOP and ESS in the original location model. It is then determined whether the location determination strategy still satisfies the optimality of the location strategy under the base load level, i.e., the minimum multi-level load balancing index. If the condition is met, the optimal SOP and the location determination strategy for the shared energy storage device are output; otherwise, the capacity determination section is repeated according to the optimal access location of the updated SOP until the verification is passed.

[0006] This invention analyzes the site selection and capacity determination method for flexible interconnection devices aimed at maximizing power supply benefits, and explores the impact of the access location and capacity of flexible interconnection devices on the maximum power supply benefits of flexible interconnection systems. It is hoped that this invention can provide reference for guiding the planning of flexible interconnection distribution networks. Attached Figure Description

[0007] Figure 1 This is a diagram of a flexible interconnected power distribution network structure; Figure 2 This is a typical daily power output diagram for photovoltaic systems and various loads; Figure 3 This is a comparison chart of load balancing indices within the transformer area; Figure 4 This is a comparison chart of load balancing indices between different stations; Figure 5 This is a time-series chart of electricity prices in various regions; Figure 6 This is a time-series diagram of the incremental power of the load in each region; Figure 7 This is a comparison chart of the maximum load supply in the industrial zone over 24 hours; Figure 8 This is a comparison chart of the maximum load supply in residential areas over 24 hours; Figure 9 This is a comparison chart of the maximum load supply in the commercial area over 24 hours.

[0008] Figure 10 This is a timing diagram of the upstream feeder load rate under scenario 2 SOP at maximum load level.

[0009] Figure 11 This is a timing diagram of the upstream feeder load rate under scenario 3 SOP at maximum load level. Detailed Implementation

[0010] This invention relates to a site selection and capacity determination method for flexible interconnection devices (SOPs) aimed at maximizing power supply revenue. The method includes: (1) a feeder mutual assistance potential assessment method based on load balancing capability; (2) a SOP site selection method based on feeder mutual assistance potential optimization considering the distribution network feeder capacity and the randomness of node load access; and (3) a SOP capacity determination method oriented towards maximizing the system's annual comprehensive revenue, taking into account the costs of flexible interconnection-related devices, thereby maximizing the distribution network load supply. This method fully considers the impact of the access location and capacity of flexible interconnection devices on the maximum power supply revenue of the flexible interconnection system. By solving for the optimal site selection and capacity determination strategy for flexible interconnection devices, it improves the maximum power supply revenue of the system while enhancing the feeder mutual assistance potential of the interconnection system.

[0011] The problem described in this invention is solved by the following technical solution: (1) Considering the capacity of the distribution network feeders and the randomness of the load access at the nodes, a feeder mutual assistance potential assessment method based on load balancing capability is proposed by dividing the distribution network feeders into two categories: main lines and branch lines. (2) Based on the load balancing characteristics of flexible interconnected distribution networks, load balancing indices for flexible interconnected distribution networks are defined, and a SOP location optimization method for feeder mutual support potential is further constructed. (3) Based on the optimal access location, in order to determine the optimal installation capacity of SOP, a SOP capacity determination method oriented towards the maximum annual comprehensive benefit of the system was constructed.

[0012] The site selection and capacity determination method for flexible interconnection devices aimed at maximizing power supply benefits proposed in this invention is as follows: In the flexible interconnection system of distribution substations, considering the capacity of distribution network feeders and the randomness of load access at nodes, a feeder mutual assistance potential assessment method based on load balancing capability is proposed by classifying distribution network feeders into two main categories: main lines and branch lines. Based on this, a load balancing index for flexible interconnected distribution networks is defined, and a SOP (Start of Production) location method for feeder mutual assistance potential optimization is further constructed to determine the optimal SOP location scheme, laying the foundation for the next step of capacity optimization of flexible interconnection devices.

[0013] Considering the economics of distribution network operation, increasing load supply aims to increase electricity sales revenue. However, overemphasizing load supply can lead to excessively high investment costs for Standard Operating Procedures (SOPs) and Energy Storage Systems (ESSs), contradicting the principle of economic efficiency. Therefore, this patent combines these two considerations in its capacity determination objective function to determine a more realistic and feasible SOP location and capacity determination scheme. Based on this method, considering the costs of interconnection devices and energy storage devices, and taking into account the initially determined access locations of flexible interconnection devices, a flexible interconnection device capacity determination optimization model aimed at maximizing power supply revenue is proposed. This model aims to maximize the system's annual comprehensive revenue and determines the optimal installation capacity of SOPs based on their optimal access locations, thereby fully utilizing the power mutual assistance capability of SOPs and expanding the system load supply. It still uses the power mutual assistance capability of flexible interconnection devices as a constraint, and can autonomously choose the optimal access capacity of flexible interconnection devices that meets the relevant constraints, thus determining the optimal SOP access scheme.

[0014] The flexible interconnection device location and capacity determination model proposed in this invention for maximizing power supply benefits consists of two sub-models: a feeder mutual assistance potential optimization model and a maximum power supply benefit optimization model. The optimal location and capacity determination scheme for the State of Operation (SOP) is determined through these two sub-models. 1. Based on the load balancing characteristics of multi-level flexible interconnected distribution networks, and with the goal of optimizing the load balancing index of the distribution network, a feeder mutual assistance potential optimization model oriented towards load balancing capability is constructed to determine the optimal access location of the SOP.

[0015] To define the load balancing index of a multi-level flexible interconnected distribution network, feeders are divided into two main categories: trunk lines and branch lines. The specific definitions are as follows: Branch lines have a radial structure, with one and only one power flow path from the first node to the last node, and each node is connected to no more than two feeders; Trunk lines are connected to the upstream power source at one end and to at least two branch lines at the other end, that is, there is at least one node connected to multiple feeders (at least three).

[0016] Because feeder capacity in a distribution network often decreases sequentially from beginning to end, and the load capacity connected to each node is often random, the load factor of each feeder cannot accurately reflect its redundancy capacity. Therefore, a single indicator cannot provide a precise assessment of feeder mutual support capability. Thus, this paper proposes a load balancing capability as an evaluation index for feeder mutual support capability, combining the feeder load factor with its redundancy capacity. By comparing the load balancing capability values ​​of the main feeders and branch feeders in each distribution area, the optimal connection location (SOP) is selected to optimize the system load balancing index.

[0017] Considering the load power fluctuations of each feeder and the timing of distributed power generation output, in order to optimize the location scheme for the mutual support potential of 24-hour feeders, a subjective and objective weighting method using an improved entropy weighting method and an improved analytic hierarchy process is adopted to assign weights to the indicators. By balancing subjective judgment and objective attributes, the weight coefficients for each time period are determined. This achieves 24-hour load rate normalization.

[0018] Considering that the main feeder and the branch feeder are at different levels, the selection principle of the benchmark value is different when calculating and evaluating. Therefore, the evaluation process of the mutual support capability of the main feeder and the branch feeder is carried out separately. The specific implementation process is as follows.

[0019] (1) The mutual support capacity of the transformer substations is initially judged by the 24-hour normalized average load rate of the main line. After determining the approximate power flow direction between the transformer substations, the specific SOP interconnection location is determined according to the load balance index of each main feeder. The steps are as follows: After calculating the 24-hour normalized average load rate of the main feeder of each transformer area using equation (1), the transformer areas are classified according to the light and heavy load conditions based on the conditions described in equation (2). If the average load rate of the main feeder of transformer area m is less than the overall average load rate of the main feeder of the system, its corresponding terminal node is placed into the set. If not, place in the set. The classification of transformer substations can serve as a reference for determining the interconnection nodes between substations in the next step. (1) (2) In the formula, The normalized average load rate of the main feeder line k in the transformer area over 24 hours. The normalized load rate of the i-th section of the main feeder in transformer area k over 24 hours. The total number of main feeders in the k-type transformer area. Let t be the load rate of the i-th segment of the main feeder in area k during time period t. The load factor for each hour of the day (determined by subjective and objective weighting methods); This represents the total number of stations within the system.

[0020] (2) Based on the results of the substation classification, select Minimum in the set The value corresponds to the end node of the feeder and Largest in the set The corresponding feeder end nodes are interconnected to achieve the best load balancing effect between stations. The calculation steps are shown in equation (3): (3) In the formula, The normalized redundancy capacity of the i-th main feeder in transformer area k for 24 hours. This represents the maximum capacity of the main feeder line in area k. Let be the capacity of the i-th main feeder in the k-th transformer area.

[0021] (3) The feeder mutual support capability within the transformer area is initially judged by the 24-hour normalized average load rate of the branch lines. After roughly classifying each feeder according to the proposed criteria, the specific SOP interconnection location within the transformer area is determined based on the redundancy capacity of each branch feeder. The steps are as follows: 1) First, the normalized average load rate of each substation branch feeder over 24 hours is calculated using equation (4); second, the feeder characteristics are classified according to the conditions described in equation (5) based on light and heavy load conditions: (4) (5) In the formula, The normalized average load rate of the feeder of branch k in the transformer area over 24 hours. Normalized load rate of the i-th branch feeder in transformer area k over 24 hours. Let t be the load rate of the i-th segment of the main feeder in area k during time period t. The load factor for each hour of the day; This represents the total number of feeders in the k-branch of the transformer area.

[0022] If the average load rate of branch feeder m in transformer area k is less than the overall average load rate of the main feeder of the system, then its corresponding end node is placed into the set. If not, place in the set. Finally, based on the characteristics of the feeders, a reference is provided for determining the interconnection nodes within the transformer area in the next step.

[0023] 2) Based on the division results according to the feeder characteristics, for The elements in the set are ordered Sort the values ​​in descending order and select the first two elements of the sequence as negative nodes to be interconnected; similarly, for The elements in the set are ordered Sort the values ​​in ascending order and select the first two elements in the sequence as the nodes to be interconnected. The calculation steps are shown in equation (6): (6) In the formula, The normalized redundancy capacity of the i-th branch feeder in transformer area k is given by [reference to a specific function / name]. Let i be the maximum capacity of the feeder segment i of the k-branch feeder in the transformer area. Let be the capacity of the i-th branch feeder in transformer area k.

[0024] By combining the nodes to be interconnected obtained from the above steps according to the following rules, a preliminary SOP location scheme is obtained: (1) Since the feeder capacity decreases from front to back, the load rate of the feeder section is likely to be light at the front and heavy at the back. Considering that internal interconnection is contrary to the principle of economical location and capacity, it is stipulated that at most one node can be selected for interconnection within the same branch feeder.

[0025] (2) In order to achieve the best load balancing effect between feeders while minimizing the system load rate, it is stipulated that each interconnection scheme of branch feeders includes two positive interconnection nodes and one negative interconnection node.

[0026] The preliminary site selection scheme for the distribution network Standard Operating Procedure (SOP) device is imported into an optimization model with the objective of minimizing the weighted average load balance index between distribution substations and between feeders. By comparing the target values ​​of each scheme, the final installation location of the SOP is determined, thereby minimizing the load imbalance of the interconnected system and enhancing the feeder mutual support potential. The objective function is: (7) In the formula, The 24-hour normalized load balance index. and The two terms are the load balance index of the main feeder between stations and the load balance index between branch feeders within the station during time period t, respectively. The specific calculation methods are shown in equations (8) and (9). and These are the weighting coefficients for the load balancing index of the main feeder between transformer substations and the weighting coefficients for the load balancing index of the branch feeder within the transformer substation. The load factor is the weighting factor for each hour of the day; T is the number of time periods.

[0027] The load balancing index between branch feeders within the transformer area is: (8) In the formula, The number of branch feeders in transformer area j; Let i be the set of downstream nodes of feeder i; The load connected to node u during time period t; Let be the maximum transmission power of the i-th branch feeder.

[0028] The balance index of the main feeder between stations is: (9) In the formula, This represents the total number of backbone feeders for all flexible interconnected transformer substations. The set of downstream branches of the main feeder i; The total load connected to the branch feeder v during time period t; Let be the maximum transmission power of the i-th main feeder.

[0029] The safety constraints for the above optimization model can be simplified as shown in the following equation: (10) In the formula, The load carried by transformer i; The net load carried by feeder section m; This indicates that feeder segment m originates from the busbar corresponding to transformer i; The net load carried by feeder section m; The feeder segment m connects to the shared energy storage device to provide power output; The network loss is for feeder segment m. This refers to the rated capacity of transformer i. The rated capacity of feeder segment m; The voltage amplitude at node r; , These are the lower and upper limits of the node voltage, respectively. , The discharge and charging power of the shared energy storage device connected to feeder segment m during time period t are respectively.

[0030] Considering port capacity constraints, the transmission power of the i-th port of SOP It should be smaller than its own capacity. : (11).

[0031] In addition, the SOP must also satisfy the active power conservation constraint: (12) In the formula, This is the set of all ports for the SOP.

[0032] The operating constraints of shared energy storage devices are as follows: (13) (14) (15) (16) In the formula, The shared energy storage device's charge capacity during time period t; and These represent the charging power and discharging power of the shared energy storage device during time period t, respectively. and These are charging efficiency and discharging efficiency, respectively. and These are the minimum and maximum charge values ​​of the shared energy storage device, respectively. and These are the charging and discharging state variables for the shared energy storage device, respectively. If it is in the charging state, then... , If it is in a discharge state, then , ; and These are the maximum charging power and maximum discharging power of the shared energy storage device, respectively.

[0033] Based on the aforementioned objective function and constraints, each preliminary SOP location scheme is imported into the location optimization model for traversal solving. Following the principle of optimal overall network load balancing index, the optimal SOP location scheme is selected. After operational optimization, this scheme should minimize the load rate difference between feeders, achieving optimal load balancing and thus establishing the initial modeling environment for subsequent SOP capacity determination.

[0034] 2. The SOP (Standard Operating Procedure) capacity setting and location strategy mainly consists of three parts: load increment setting, capacity optimization model construction, and location and capacity setting scheme determination. This optimization process considers two main objectives: maximum power supply revenue and the combined costs of flexible interconnection devices and energy storage devices.

[0035] To better reflect the actual operation of the distribution network, the load increment settings for different areas of the distribution network are as follows: During the daytime period (6:00-20:00), the load increment is set for industrial and commercial areas in the form of a multiple increase of the existing load; during the nighttime period (20:00-6:00 the next day), the load increment is set for residential and commercial areas in the form of new electric vehicle charging stations. The specific implementation details of the load growth spatial analysis method are as follows: (1) Obtain power grid structure parameters, determine the initial capacity of SOP and ESS with reference to the base load level, and set the initial load values ​​for each area. Load growth factor Related restrictions; (2) Based on the optimal access location of SOP obtained from the location model, a new network topology oriented towards the maximum load supply is formed, and a SOP and ESS capacity model oriented towards the overall system benefit with the maximum load growth multiple is constructed. (3) Solve the fixed capacity model. While determining the SOP and ESS location fixed capacity scheme, calculate the load results of the power distribution system for each time period of 24 hours according to the maximum load increment of each area to obtain the maximum power supply revenue value.

[0036] This section on grid operation benefits mainly includes the potential for load growth after the integration of flexible interconnection devices. Revenue from electricity sales Total cost of SOP device construction and maintenance And the total cost of construction and maintenance of energy storage devices. Among them, the potential for load growth. With maximum load supply The relationship is: (17) In the formula, is the original basic load of the i-th node during time period j; n is the total number of nodes in the system.

[0037] objective function for: (18) In the formula, Let j be the electricity price for the i-th node during time period j. This represents the total revenue generated by the power grid operation.

[0038] The specific calculation formula is as follows: (19) (20) In the formula, The fixed investment cost is calculated per year based on the SOP. d is the annual maintenance cost of the SOP; y is the discount rate; and y is the economic lifespan of the SOP. The unit capacity investment cost of SOP; SOP installation capacity; This is the annual maintenance cost coefficient for SOP; , These are the initial investment cost and operation and maintenance cost of the energy storage system, respectively. is the investment discount factor; k is the discount rate; z is the lifespan of the energy storage system; The unit capacity investment cost of the energy storage system; This is the equivalent coefficient for the operation and maintenance costs of energy storage devices.

[0039] The fixed-capacity optimization model is still subject to constraints such as operational safety constraints and flexible interconnection device constraints. These constraints have been described in detail in the site selection optimization model and will not be repeated here.

[0040] Based on the above objective function and constraints, after obtaining the specific capacities of SOP and ESS in the capacity determination section, these are substituted back into the location optimization model section to replace the initial capacities of SOP and ESS in the original location model. It is then determined whether the location determination strategy still satisfies the optimality of the location strategy under the base load level, i.e., the minimum multi-level load balancing index. If the condition is met, the optimal SOP and the location determination strategy for the shared energy storage device are output; otherwise, the capacity determination section is repeated according to the optimal access location of the updated SOP until the verification is passed.

[0041] Simulation analysis is performed using an improved IEEE 33-node interconnect system, with two IEEE 33-node flexible interconnect systems as the case study. The structure is as follows: Figure 1 As shown. In the two interconnected systems, branch lines L4 and L5 are connected to typical residential loads, L6 to typical commercial loads, and L7 to typical industrial loads. Forecast data of load and photovoltaic output for each transformer area over a one-year period with a one-hour time step are selected and clustered according to load attributes to obtain typical daily data of load power and photovoltaic output, as shown below. Figure 2 As shown in Table 1, this patent sets up four scenarios for subsequent model validation and result comparison analysis. The specific details of each scenario are shown in Table 1. The model is solved using Matlab programming and by calling the Yalmip toolbox and the Gurobi solver.

[0042] Table 1

[0043] This patent first classifies the corresponding nodes based on the feeder mutual support capability assessment method, and selects candidate nodes. The load balancing capability calculation results of each type of candidate node are shown in Table 2. Then, according to the load balancing capability values ​​of each feeder, they are combined according to the set principles to obtain the initial SOP access position, which reduces the model calculation load to a certain extent. Finally, the node combination of the initial SOP access position is imported into the operation optimization layer to calculate the power flow control and obtain the load balancing index of each scheme. Based on this, the final SOP access scheme is determined, and the specific results are shown in Table 3.

[0044] Table 2

[0045] Table 3

[0046] Based on the traditional interconnection site selection requirements for line end voltage management, a comparative experiment was set up (in scenario 2, all SOPs in the distribution area are connected to the feeder end). This patent imports the load balancing index after power flow regulation into the operation optimization layer for each of the candidate SOP connection locations and selects the optimal SOP connection scheme. The SOP connection locations for each scenario in this example are shown in Table 4.

[0047] Table 4

[0048] Figure 3-4 The results compare the load balancing indices within and between distribution zones in three scenarios. It can be seen that, compared to traditional location methods, the location method proposed in this patent yields a lower multi-level load balancing index. Therefore, when minimizing this index is the optimization objective, the location method proposed in this patent is more advantageous.

[0049] Scenario 2 and 3 were selected as comparative schemes to verify the effectiveness of the constant-capacity model of this patent. The time-of-use electricity prices in each region are as follows: Figure 5 As shown, the load increment settings for each area are as follows: Figure 6 As shown in Table 5, the capacity model was solved using the Gurobi solver to obtain the capacity results of each port of the SOP in each scenario and the corresponding annual comprehensive system revenue.

[0050] Table 5

[0051] The specific addressing and sizing schemes for SOP and ESS in Scenario 4 were back-substituted into the addressing optimization model for verification. The verification results are shown in Table 6. It can be seen that the multi-level load balancing index of the above addressing strategy is still kept to the minimum, which ensures the optimality of the addressing strategy.

[0052] Table 6

[0053] Table 7 shows the maximum load supply of each area in the system under each scenario. In terms of annual comprehensive revenue, the patented solution (Scenario 4) is 3.95% higher than Scenario 2 and 2.44% higher than Scenario 3. In terms of maximum load supply, the patented solution is 14.58% and 7.4% higher than Scenario 2 in commercial and industrial areas, respectively; and 15.12% higher than Scenario 3 in industrial areas. It is worth noting that although the maximum load supply of Scenario 4 is lower than that of Scenario 2 (residential area) and Scenario 3 (residential and commercial areas), the corresponding value in the industrial area is significantly increased due to the better power mutual assistance characteristics of each area within the transformer substation, resulting in better comprehensive revenue than the other two scenarios.

[0054] Table 7

[0055] Figure 7-9 The chart presents a comparison of the maximum 24-hour load supply for each area in the system under three scenarios. It can be seen that the unconnected system, lacking reactive power compensation capability, is prone to voltage over-limit situations when the load increases significantly; therefore, the TSC values ​​for each area are generally low in this scenario. The timing diagrams of the upstream feeder load rate of the SOP in each transformer area under scenarios 2 and 3 at maximum load levels are shown below. Figure 10-11 As shown, since the feeder capacity decreases sequentially from front to back in the actual power grid, the SOP devices connected to each feeder end in Scenario 2, which is oriented towards the voltage management interconnection method at the feeder end, are easily affected by the capacity limitation of the feeder end, thus affecting their power mutual assistance capability. At the same time, in Scenario 3, since the feeder load balancing capability assessment is not taken into account, the SOPs in the transformer area are not connected to the optimal location, and the capacity limitation of the connected upstream feeder prevents its power mutual assistance capability from being fully utilized. The location and capacity determination strategy of this patent can identify areas with weak feeder capacity and determine capacity through economical location and capacity determination of SOPs. Compared with the location and capacity determination strategy that does not consider load balancing, the strategy proposed in this patent increases the 24-hour comprehensive maximum load supply by 2.48%, and can reach up to 15.12% during the peak load period in industrial areas.

[0056] This invention proposes a site selection and capacity determination method for flexible interconnection devices aimed at maximizing power supply benefits. It achieves optimization of the mutual support potential of feeders in flexible interconnection distribution networks and enhances the maximum power supply benefits. The proposed method can be used for capacity selection of distribution network interconnection equipment. It combines the technical advantages of flexible interconnection and energy storage devices, alleviates the limitations of voltage and capacity constraints at the feeder end of traditional systems on the improvement of maximum load supply, and provides an economical and reasonable solution for the configuration of flexible interconnection equipment in the context of large-scale access to new loads.

Claims

1. A method for site selection and capacity determination of flexible interconnection devices aimed at maximizing power supply benefits, characterized in that: The steps are: S1, constructing a feeder mutual aid potential optimization model oriented to load balancing capability: S11, obtaining the 24h normalized average load rate of each main feeder of the substation through formula (1), and dividing the substation properties according to the conditions of formula (2) according to the light and heavy load conditions: （1） （2） wherein, is the average of the 24-hour normalized load rate of the main feeder 24 of the kth district, is the 24-hour normalized load rate of the ith section of the main feeder 24 of the kth district, is the total number of main feeders of the kth district, is the load rate of the ith section of the main feeder 24 of the kth district at time t, is the weight coefficient of the load rate of each hour in a day, is the total number of districts in the system; S12, select the minimum value in the set and interconnect the feeder end nodes corresponding to the minimum value in the set, the maximum value in the set and interconnect the feeder end nodes corresponding to the maximum value in the set, as shown in equation (3): （3） wherein is the 24-hour normalized redundancy capacity of the i-th backbone feeder line in the k-th district, is the maximum capacity of the backbone feeder line in the k-th district, is the capacity of the i-th backbone feeder line in the k-th district. S13, using the 24h normalized average load rate of the branch to preliminarily judge the mutual aid capability of the feeder, and the steps are as follows: S131, calculating the 24h normalized average load rate of each branch feeder of the substation through formula (4); secondly, dividing the feeder properties according to the conditions of formula (5) according to the light and heavy load conditions: （4） （5） wherein, is the average of the 24-hour normalized load rate of the branch feeder of the kth substation, is the 24-hour normalized load rate of the ith branch feeder of the kth substation, is the load rate of the ith main feeder of the kth substation in the tth period, is the load rate weight coefficient of each hour in a day; is the total number of branch feeders of the kth substation; S132, to elements in the set are arranged in descending order of value and the first two elements in the sequence are filtered as negative nodes to be interconnected; elements in the set are arranged in descending order of value and the first two elements in the sequence are filtered as negative nodes to be interconnected; elements in the set are arranged in descending order of value and the first two elements in the sequence are filtered as negative nodes to be interconnected; elements in the set are arranged in descending order of value and the first two elements in the sequence are filtered as negative nodes to be interconnected, The calculation step is shown in formula (6): （6） wherein is the 24-hour normalized redundancy capacity of the ith branch feeder of the kth district, is the maximum capacity of the feeder on which the ith branch feeder segment of the kth district is located, is the capacity of the ith branch feeder of the kth district. S14, combining the obtained nodes to be interconnected according to the following rules to obtain a preliminary SOP site selection scheme: S141, considering that internal interconnection is contrary to the economic principle of site selection and capacity determination, so it is stipulated that at most one node in the same branch feeder is selected for interconnection; S142, stipulating that each interconnection scheme of the branch feeder contains two positive nodes to be interconnected and one negative node to be interconnected; S15, importing the preliminary site selection scheme of the power distribution network SOP device into an optimization model with the weighted minimum of the load balance index between substations and the load balance index between feeders as the target, and the objective function is: （7） In the formula, is a 24-hour normalized load balance index, and are a period t inter-substation main feeder load balance index and an intra-substation branch feeder load balance index, respectively; and are an inter-substation main feeder load balance index weight coefficient and an intra-substation branch feeder load balance index weight coefficient, respectively; is a weight coefficient of load rate in each hour in a day; and T is the number of time periods. The load balance index between branch feeders in the substation is: （8） wherein, is the number of branch feeders in the zone j; is the set of downstream nodes of feeder i; is the load connected to node u at time t; is the maximum transmission power of the i-th branch feeder; The main feeder balance index between substations is: （9） In the formula, is the total number of flexible interconnection area backbone feeder lines; is the downstream branch set of the backbone feeder line i; is the total amount of load accessed by the branch feeder line v in the t period; is the maximum transmission power of the i th backbone feeder line; S16, the safety constraint of the optimization model can be simplified as shown in the following formula: （10） wherein, is the load carried by transformer i; is the net load carried by feeder segment m; denotes the busbar from which feeder segment m comes out of transformer i; is the net load carried by feeder segment m; is the output of the shared energy storage device connected to feeder segment m; is the network loss of feeder segment m; is the rated capacity of transformer i; is the rated capacity of feeder segment m; is the voltage amplitude of node r; , are the lower and upper voltage limits of the node, respectively; , are the discharging and charging power of the shared energy storage device t when connected to feeder segment m, respectively; S17, transmission power of the i-th port of the SOP considering the port capacity constraint should be less than its own capacity : （11） The SOP satisfies the active power conservation constraint: （12） In the formula, is the set of all ports of the SOP; S18, the operation constraint of the shared energy storage device is as follows: （13） （14） （15） （16） wherein, is the state of charge of the shared energy storage device at time t; and are the charging and discharging power of the shared energy storage device at time t, respectively; and are the charging and discharging efficiency, respectively; and are the minimum and maximum value of the state of charge of the shared energy storage device, respectively; and are the state of charge and state of discharge of the shared energy storage device, respectively; and are the maximum charging and discharging power of the shared energy storage device, respectively. S2, the grid operation benefit mainly includes the load growth space after the flexible interconnection device is accessed The electricity sales benefit brought by The total cost of the SOP device construction and maintenance , and the total cost of the energy storage device construction and maintenance ; wherein, the relationship between the load growth space and the maximum load supply amount is: （17） In the formula, is the original base load of the i-th node j in the period; n is the total number of nodes in the system; Objective function is: （18） In the formula, is the i-th node j period electricity price, is the total income of grid operation; The specific calculation formula is: （19） （20） In the formula, is the fixed investment cost of SOP converted to each year; is the annual operation and maintenance cost of SOP; d is the discount rate; y is the economic service life of SOP; is the unit capacity investment cost of SOP; is the installation capacity of SOP; is the annual operation and maintenance cost coefficient of SOP; , are the initial investment cost and operation and maintenance cost of the energy storage system respectively; is the investment discount coefficient; k is the discount rate; z is the service life of the energy storage system; is the unit capacity investment cost of the energy storage system; is the equivalent coefficient of the operation and maintenance cost of the energy storage device; Based on the above objective function and constraint conditions, after obtaining the specific capacity of SOP and ESS in the capacity determination part, it is substituted back into the site selection optimization model part to replace the preliminary capacity of SOP and ESS in the original site selection model, and it is judged whether the site selection and capacity determination strategy still satisfies the optimality of the site selection strategy under the basic load level, that is, the minimum of the multi-level load balancing index, if the condition is satisfied, the optimal SOP and shared energy storage device site selection and capacity determination strategy is output; otherwise, the optimal access position of the SOP is updated, and the capacity determination part is repeated until the check is passed.

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