Planning Methods and Systems for Medium-Voltage Flexible Interconnected Power Distribution Systems Aiming at Enhanced Flexibility

Abstract

This paper presents a planning method and system for medium-voltage flexible interconnected distribution systems aimed at improving flexibility. It uses the ratio of distribution network regulation capacity to net load power change during the dispatch cycle as the supply-demand balance index, and the average sum of the current margins of lines and flexible tie switches as the transmission capacity index. An optimized planning model for the medium-voltage flexible interconnected system is established, including a planning layer model with the goal of minimizing annual comprehensive operating costs and an operation layer model with the goal of maximizing the difference between the supply-demand balance index and the transmission capacity index. Using the configuration schemes of energy storage systems and flexible tie switches as decision variables in a game, and the optimization objectives of the planning layer model and the operation layer model as the game objects, a Nash equilibrium model is established. The particle swarm optimization algorithm is used to solve the Nash equilibrium model, obtaining the optimal configuration scheme of the energy storage system and flexible tie switches as the planning result for the medium-voltage flexible interconnected distribution system, thus resolving the problem of the mutual exclusion of economy and flexibility in the planning process.

Description

Technical Field

[0001] This invention belongs to the field of electrical engineering and relates to the optimization planning technology of flexible interconnected power distribution systems. Specifically, it relates to an optimization planning method and system for medium-voltage flexible interconnected power distribution systems that takes into account both economic efficiency and flexibility. Background Technology

[0002] As the final stage of power supply, the distribution network has become the main force for accommodating these flexible resources. Against this backdrop, traditional AC radial distribution networks are facing challenges of weak power supply capacity and insufficient system flexibility. AC / DC distribution networks, due to their flexible power transfer capabilities, are receiving increasing attention. Research and demonstration projects related to flexible interconnection of low-voltage distribution networks have been widely carried out; however, with the increasing proportion of new power sources, the system capacity and regulation capabilities on the low-voltage side can no longer meet the diverse and widespread access demands of flexible resources. In recent years, research on flexible interconnection of medium-voltage distribution networks has also gradually begun. However, medium-voltage systems have larger capacities and higher equipment costs. How to balance the system's flexibility requirements with the economic costs of retrofitting plans, and how to optimize the planning of medium-voltage flexible interconnection systems, is currently a highly concerning issue.

[0003] In existing technologies, methods for assessing the flexibility of distribution networks considering the coordinated interaction of flexible resources construct a flexibility assessment index system encompassing three aspects: coordinated adjustment capability, quality of collaborative benefits, and grid reliability. A Gaussian mixture model is used to construct typical operating scenarios and evaluate the flexibility indicators. A three-layer coordinated planning model for improving the flexibility of new distribution systems is also proposed. The upper layer aims to minimize the equivalent annual investment cost, the middle layer aims to minimize the annual comprehensive operating cost of the distribution network, and the lower layer aims to optimize operation by maximizing the daily average flexibility level. A hybrid optimization algorithm is used to solve the three-layer model. However, this method treats the flexibility objective as a subordinate condition for economic planning. A grid-storage joint planning method considering the operational flexibility of carbon capture power plants separates the operation and planning layers, uses a snake optimization algorithm to calculate the flexibility index of the planning layer, and transforms the model into a linear optimization model for solution. While existing technologies can effectively solve the problem of mutual iteration between two-layer models, they still have shortcomings in solving multi-objective problems and addressing the issue of mutually exclusive objective trends. First, traditional multi-objective transformation methods based on weighted processing struggle to determine reasonable objective weights; second, it is difficult to select the final solution from the Pareto multi-objective solution set. Regarding the optimization planning of medium-voltage flexible interconnection, the following aspects still require breakthroughs: First, there is a lack of methods to accurately characterize the flexibility of medium-voltage flexible interconnection distribution systems that possess flexible power transfer capabilities and include various types of flexible resources; second, given the high planning and construction costs of medium-voltage systems, how to scientifically and rationally balance the two important indicators of economy and flexibility is an issue that needs further consideration. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a planning method and system for medium-voltage flexible interconnected power distribution systems aimed at improving flexibility. First, using soft open points (SOPs) as interconnection devices, a typical structural form of the medium-voltage interconnected power distribution system is constructed, and power transfer constraints for the medium-voltage flexible interconnected system are given. Second, the main flexibility indicators of the flexible interconnected system are given from the source side, load side, and grid side, and the calculation methods for these indicators are provided, thus accurately characterizing the flexibility of the interconnected system. Then, a medium-voltage interconnected operation model considering the mutual support of flexibility resources and a planning model balancing economy and flexibility are established.

[0005] The present invention adopts the following technical solution.

[0006] This invention proposes a planning method for medium-voltage flexible interconnected distribution systems aimed at improving flexibility. The flexibility resources of the distribution network include energy storage systems and distributed generation. The planning method includes:

[0007] The operating parameters and regulation capabilities of energy storage systems and distributed power sources are obtained. Based on the flexibility resource regulation capability model, the flexibility resource adequacy index is determined. Based on the flexibility resource adequacy index and the regulation capability of flexible tie switches, the distribution network regulation capability is determined. The ratio of the distribution network regulation capability to the change in net load power during the scheduling cycle is used as the supply and demand balance index. The average value of the sum of the current margins of lines and flexible tie switches during the scheduling cycle is used as the transmission capacity index.

[0008] Based on a two-layer model structure, an optimization planning model for a medium-voltage flexible interconnection system is established, comprising: a planning layer model with the goal of minimizing annual comprehensive operating costs, and an operation layer model with the goal of maximizing the difference between the supply-demand balance index and the transmission capacity index. The planning layer model provides the operation layer model with the configuration schemes of the energy storage system and flexible interconnection switches when the annual comprehensive operating costs are minimized, while the operation layer model provides the planning layer model with the system operating losses when the difference between the supply-demand balance index and the transmission capacity index is maximized. The planning layer model updates the annual comprehensive operating costs based on the received system operating losses.

[0009] Using the configuration schemes of energy storage systems and flexible interconnection switches as decision variables in a game, and the optimization objectives of the planning layer model and the operation layer model as game objects, a Nash equilibrium model is established. The particle swarm optimization algorithm is used to solve the Nash equilibrium model to obtain the optimal configuration schemes of energy storage systems and flexible interconnection switches, which serve as the planning results for medium-voltage flexible interconnected power distribution systems.

[0010] Preferably, a flexible resource regulation capability model is established; the operating parameters and regulation capabilities of the energy storage system and distributed power sources are obtained, and the flexibility resource adequacy index is determined through the flexible resource regulation capability model.

[0011] The flexible resource adjustment capability model satisfies the following relationship:

[0012]

[0013]

[0014] In the formula, and These represent the up-adjustment and down-adjustment capabilities of the energy storage system at node i at time t, respectively. and , , are the battery charge / discharge state variables of the energy storage system at node i at time t, both of which are 0-1 variables; and , respectively, represent the active power of energy storage charging and discharging at node i at time t; and These represent the maximum active power of energy storage charging and discharging at node i at time t, respectively.

[0015] and P represents the up-modulation and down-modulation capabilities of the distributed power source at node i at time t, respectively. DG,i,t P represents the active power of the distributed power source at node i at time t. DG,i,t,max and P DG,i,t,min These are the maximum and minimum active power outputs of the distributed power source at node i, respectively. and These are the upward and downward ramp power limits for the distributed power source at node i, respectively.

[0016] Preferably, the distribution network regulation capacity is determined based on the flexibility resource adequacy index and the regulation capacity of the flexible interconnection switch, and the ratio of the distribution network regulation capacity to the change in net load power during the dispatching cycle is used as the supply and demand balance index.

[0017] The supply and demand balance index satisfies the following relationship:

[0018]

[0019]

[0020]

[0021]

[0022] In the formula, I FRAs a supply and demand balance indicator, I UFR I is the sum of the ratios of the available schedulable margin of flexible resources to the change in net load when the net load increases within a scheduling cycle. DFR F is the sum of the ratios of the available schedulable margin of flexible resources to the change in net load when the net load decreases within a scheduling cycle, where T is the total number of time periods within the scheduling cycle; t U F t D Let w represent the up-regulation capacity and down-regulation capacity of the distribution network at time t, respectively; w represents the sum of the up-regulation capacity of the energy storage system and the distributed power generation, respectively; w represents the sum of the down-regulation capacity of the energy storage system and the distributed power generation. t Let P be the state variable representing the change in power of the net load at time t; t nl , These are the net load power at time t and time t+1, respectively; and These represent the sets of installation nodes for energy storage systems and distributed power sources, respectively; N is the number of flexible interconnection switches; P ESS Let be the rated power of the energy storage system, and take the minimum value of the rated power of the energy storage system as the up-adjustment capability of the energy storage system at node i at time t. and These represent the upper and lower limits of the flexible interconnection switch's adjustment capability at time t, respectively.

[0023] Preferably, the average value of the sum of the current margins of the line and the flexible tie switch within the scheduling cycle is used as the transmission capacity index, satisfying the following relationship:

[0024]

[0025] In the formula, I GM For transmission capacity indicators, L represents the total number of lines, and N represents the total number of flexible tie switches; I WM,t and I SOPM,t Let be the current margins of the line and the flexible tie switch at time t, respectively, satisfying the following relationship:

[0026]

[0027]

[0028] In the formula, I ij,MAX I represents the maximum allowable current through branch ij; ij,t Let be the current flowing through branch ij at time t; P is the set of branches containing the flexible interconnection switch; SOP,MAX P represents the maximum active power that the port of the flexible tie switch is allowed to transmit; SOP,n,i,t and P SOP,n,j,tThese represent the active power transmitted at time t on one port i and the other port j of the nth flexible interconnection switch.

[0029] Preferably, the planning layer model uses the annual comprehensive operating cost C T The minimum is the optimization objective, satisfying the following relationship:

[0030]

[0031] In the formula, These are the investment costs for flexible interconnection switches and energy storage systems, respectively. The operating and maintenance costs of the flexible interconnection switch and the energy storage system are respectively, C PL This refers to the system's operating costs.

[0032] in,

[0033] 1) The investment cost and operation and maintenance cost of the flexible interconnection switch satisfy the following relationship:

[0034]

[0035]

[0036] In the formula, d SOP The discount rate for flexible interconnection switches, y SOP To extend the service life of the flexible interconnecting switch, c SOP η represents the investment cost per unit capacity of flexible interconnection switch. SOP S represents the annual operation and maintenance cost coefficient of the flexible interconnection switch. SOP,i Let N be the configuration capacity of the i-th flexible tie switch, and N be the total number of flexible tie switches.

[0037] 2) The investment cost and operation and maintenance cost of ESS satisfy the following relationship:

[0038]

[0039]

[0040] In the formula, d ESS Let y be the discount rate for ESS. ESS For the lifespan of ESS, and These are the rated power and rated capacity of the ESS, respectively. ESS,P and c ESS,E The installation costs per unit power and per unit capacity of the ESS are respectively. ESS For the maintenance cost per unit capacity of ESS, Y T For working hours;

[0041] 3) The system operating loss cost satisfies the following relationship:

[0042]

[0043] In the formula, η PL This is the power loss cost conversion factor. and These are network operation losses and flexible interconnection switching losses, respectively.

[0044] Preferably, the constraints on the optimization objective in the planning layer model include:

[0045] 1) The capacity constraint of the flexible interconnection device satisfies the following relationship:

[0046]

[0047]

[0048] In the formula, S k,i and S k,j Let be the installed capacities of the k-th converter at nodes i and j, respectively. Let be the active power and reactive power of the nth flexible tie switch at node i at time t, respectively. These are the active power and reactive power of the nth flexible tie switch at node j at time t, respectively.

[0049] 2) The capacity constraints of the energy storage system satisfy the following relationship:

[0050]

[0051] In the formula, and Let be the upper and lower limits of the capacity of the i-th energy storage system, respectively. Let be the capacity of the i-th energy storage system at time t. and Let represent the charging efficiency and discharging efficiency of the i-th energy storage system, respectively, and Δt be the charging time.

[0052] Preferably, the operation layer model takes maximizing the difference between the supply-demand balance index and the transmission capacity index as its optimization objective, satisfying the following relationship:

[0053] maxF DOWN =I FR,s -I GM,s

[0054] In the formula, F DOWN For scenario s, the supply and demand balance index I FR,s Transmission capability index I under scenario sGM,s The difference.

[0055] Preferably, the constraints for the optimization objective in the runtime model include:

[0056] 1) The node voltage constraint condition satisfies the following relationship:

[0057] U i,min ≤U i (t)≤U i,max

[0058] In the formula, U i (t) represents the voltage value at node i at time t, U i,min and U i,max These are the lower and upper limits of the voltage at node i, respectively;

[0059] 2) The line transmission power constraint condition satisfies the following relationship:

[0060] P l (t)≤P l,max

[0061] In the formula, P l (t) represents the active power transmitted by line l at time t, P l,max This represents the maximum active power that line l is allowed to transmit.

[0062] 3) The power flow balance constraint condition satisfies the following relationship:

[0063]

[0064] In the formula, P ac,i and Q ac,i G represents the active power and reactive power injected at node i, respectively. ac,ij B ij and θ ij U represents the conductance, susceptance, and voltage phase difference between node i and node j, respectively. ac,i and U ac,j P1 represents the voltage at node i and node j, respectively. β1 and β2 are 0-1 variables, indicating whether the node is connected to the flexible interconnection switch. SOP,ac The active power injected by the SOP at one port. N represents the active power flowing out of the SOP at another port. ac The total number of nodes;

[0065] 4) The power balance constraint condition for flexible interconnection devices satisfies the following relationship:

[0066]

[0067] In the formula, The active power loss of SOP;

[0068] 5) The ESS charge / discharge constraint conditions satisfy the following relationship:

[0069]

[0070]

[0071] In the formula, and Let represent the battery charge / discharge state variables of the energy storage system at node i at time t, both of which are 0-1 variables. and Let be the maximum active power of energy storage charging and discharging at node i at time t, respectively. and Let be the active power of energy storage charging and discharging at node i at time t, respectively.

[0072] Preferably, the Nash equilibrium model satisfies the following relationship:

[0073] F OBF =max(F DOWN -d DOWN (C) T -d UP )

[0074] In the formula, F OBF For the Nash equilibrium model, d UP and d DOWN These are the negotiation breakdown points for the planning layer model and the operational layer model, respectively. In this embodiment, the specific numerical values ​​of the negotiation breakdown points are obtained by considering only the economic and flexibility scenarios in the numerical example analysis. T For annual comprehensive operating costs, F DOWN This represents the difference between the supply-demand balance index and the transmission capacity index in the given scenario.

[0075] This invention also proposes a planning system for a medium-voltage flexible interconnected distribution system aimed at improving flexibility. The flexibility resources of the distribution network include energy storage systems and distributed power sources. The planning system includes:

[0076] The flexible indicator establishment module is used to obtain the operating parameters and regulation capabilities of energy storage systems and distributed power sources. Based on the flexible resource regulation capability model, it determines the flexibility resource adequacy index; based on the flexibility resource adequacy index and the regulation capability of flexible tie switches, it determines the distribution network regulation capability. The ratio of the distribution network regulation capability to the change in net load power within the scheduling cycle is used as the supply and demand balance index; and the average value of the sum of the current margins of lines and flexible tie switches within the scheduling cycle is used as the transmission capacity index.

[0077] The optimization planning model building module is used to establish an optimization planning model for a medium-voltage flexible interconnected power distribution system based on a two-layer model structure. This model includes: a planning layer model with the goal of minimizing annual comprehensive operating costs, and an operation layer model with the goal of maximizing the difference between supply-demand balance indicators and transmission capacity indicators. The planning layer model provides the operation layer model with the configuration schemes of the energy storage system and flexible interconnection switches when the annual comprehensive operating costs are minimized. The operation layer model provides the planning layer model with the system operating losses when the difference between the supply-demand balance indicators and transmission capacity indicators is maximized. The planning layer model updates the annual comprehensive operating costs based on the received system operating losses.

[0078] The model solving module is used to establish a Nash equilibrium model with the configuration schemes of the energy storage system and flexible interconnection switch as decision variables in a game, and the optimization objectives of the planning layer model and the operation layer model as game objects. The particle swarm optimization algorithm is used to solve the Nash equilibrium model to obtain the optimal configuration schemes of the energy storage system and flexible interconnection switch, which serve as the planning results of the medium-voltage flexible interconnected power distribution system.

[0079] A terminal includes a processor and a storage medium; the storage medium is used to store instructions; the processor is used to perform operations according to the instructions to execute the steps of a method.

[0080] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of a method.

[0081] The beneficial effects of this invention are that, compared with the prior art, it at least includes the following: This invention establishes a flexibility index system for flexible interconnected systems from three dimensions: sufficiency of flexibility resources, supply-demand balance, and system source load carrying capacity, and provides a calculation method for the flexibility index to characterize the flexibility of the flexible interconnected system. To solve the problem of the mutual exclusion of economy and flexibility in the planning process, this invention establishes a two-layer optimization planning model based on Nash equilibrium. The upper-layer model plans the interconnection devices and energy storage with the goal of achieving an optimal balance between economy and flexibility, while the lower-layer optimizes the operation of the medium-voltage flexible interconnected system considering the mutual support of flexibility resources. Attached Figure Description

[0082] Figure 1 This is a flowchart of a medium-voltage flexible interconnected power distribution system planning method proposed in this invention, aimed at improving flexibility.

[0083] Figure 2 This is a topology diagram of two IEEE 33 nodes before modification in an embodiment of the present invention;

[0084] Figure 3 This is a bar chart showing the cost composition in various scenarios in the embodiments of the present invention. Detailed Implementation

[0085] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0086] A flexible interconnection switch (SOP) is a type of interconnection switch based on power electronic equipment. SOPs can control the magnitude and direction of active power flow while also absorbing reactive power to maintain voltage. Therefore, they have been widely used in low-voltage distribution areas to balance internal resources and improve the carrying capacity of new load sources. Similarly, connecting two distribution areas using SOPs and medium-voltage lines not only enables flexible resource exchange between areas but also allows for connections based on the needs and resource differences of different areas, thereby achieving the goal of coordinated planning and unified scheduling. In a typical medium-voltage flexible interconnection system topology, the ends of one distribution area and the ends of another are connected via SOPs to exchange flexible resources.

[0087] Taking a back-to-back voltage source converter (SOP) structure as an example, the SOP connects two voltage source converters (VSCs) back-to-back to form a symmetrical structure via DC-side capacitors. The control modes differ under different operating scenarios. Specifically, in the closed-loop operation of the distribution network, the SOP is mainly used to realize power exchange between feeders, and the flexible power transfer needs to meet the following constraints:

[0088]

[0089] In the formula, P1 SOP (t) and Let be the active power at one end of SOP and the active power at the other end, respectively, at time t. and Let be the reactive power at one end of SOP and the reactive power at the other end, respectively, at time t. and These represent the capacities of the first VSC and the second VSC connected to the SOP, respectively.

[0090] This invention proposes a planning method for medium-voltage flexible interconnected distribution systems aimed at improving flexibility. The flexibility resources of the distribution network include energy storage systems and distributed generation, such as... Figure 1 As shown, the planning methods include:

[0091] Step 1: Obtain the operating parameters and regulation capabilities of the energy storage system and distributed power sources. Based on the flexibility resource regulation capability model, determine the flexibility resource adequacy index. Based on the flexibility resource adequacy index and the regulation capability of flexible tie switches, determine the distribution network regulation capability. The ratio of the distribution network regulation capability to the net load power change during the scheduling cycle is used as the supply and demand balance index. The average value of the sum of the current margins of lines and flexible tie switches during the scheduling cycle is used as the transmission capacity index.

[0092] Specifically, step 1 includes:

[0093] Step 1.1: Establish a flexible resource regulation capability model; obtain the operating parameters and regulation capabilities of the energy storage system and distributed power sources, and determine the flexibility resource adequacy index through the flexible resource regulation capability model.

[0094] Flexibility resources in a distribution network include energy storage systems (ESS) and distributed generation (DG). ESS can provide upward or downward flexibility by controlling the power of battery charging and discharging; DG can provide upward or downward flexibility by controlling its output. The sum of the flexibility capabilities of each ESS and DG within a distribution area constitutes the flexibility resources of that area. The adequacy of flexibility resources is used to characterize their quantity. Therefore, by obtaining the operating parameters and regulation capabilities of energy storage systems and distributed generation, and using a flexibility resource regulation capability model, the adequacy index of flexibility resources can be determined.

[0095] Specifically, the flexible resource adjustment capability model satisfies the following relationship:

[0096]

[0097]

[0098] In the formula, and These represent the up-adjustment and down-adjustment capabilities of the energy storage system at node i at time t, respectively. and , , are the battery charge / discharge state variables of the energy storage system at node i at time t, both of which are 0-1 variables; and , respectively, represent the active power of energy storage charging and discharging at node i at time t; and These represent the maximum active power of energy storage charging and discharging at node i at time t, respectively.

[0099] and P represents the up-modulation and down-modulation capabilities of the distributed power source at node i at time t, respectively. DG,i,t P represents the active power of the distributed power source at node i at time t. DG,i,t,max and P DG,i,t,min These are the maximum and minimum active power outputs of the distributed power source at node i, respectively. and These are the upward and downward ramp power limits for the distributed power source at node i, respectively.

[0100] Furthermore, the ESS charging and discharging constraints of the flexibility resource adjustment capability model satisfy the following relationship:

[0101]

[0102]

[0103]

[0104] In the formula, and Let represent the battery charge / discharge state variables of the energy storage system at node i at time t, both of which are 0-1 variables. and Let be the maximum active power of energy storage charging and discharging at node i at time t, respectively. and The active power of energy storage charging and discharging at node i at time t are respectively.

[0105] Step 1.2: Based on the flexibility resource adequacy index and the flexible interconnection switch regulation capacity, determine the distribution network regulation capacity, and use the ratio of the distribution network regulation capacity to the net load power change during the dispatching cycle as the supply and demand balance index.

[0106] In this embodiment, the flexibility resource adequacy index is determined based on the actual operating parameters of the flexibility resources. The flexibility of the distribution network mainly comes from flexibility resources such as ESS and SOP, while the flexibility demand of the distribution network is mainly reflected in the supply and demand relationship between the load and the flexibility resources. Therefore, the flexibility resource adequacy index provides a basis for determining the supply and demand balance index, avoiding the problem of over-configuration and over-investment caused by only considering the supply and demand relationship, which is conducive to improving the operating economy of the system.

[0107] Specifically, the supply-demand balance index reflects the adaptability of the distribution network's regulation capacity under random fluctuations in net load power. Therefore, the supply-demand balance index of the distribution network satisfies the following relationship:

[0108]

[0109]

[0110]

[0111]

[0112] In the formula, I FR As a supply and demand balance indicator, I UFR I is the sum of the ratios of the available schedulable margin of flexible resources to the change in net load when the net load increases within a scheduling cycle. DFR The ratio of the available schedulable margin of flexible resources to the change in net load when the net load decreases within a scheduling cycle is the sum of these ratios. T is the total number of time periods within the scheduling cycle; in this example, the scheduling cycle is 24 hours, and the interval between time periods is 1 hour. t U F t D Let F represent the upward and downward adjustment capabilities of the distribution network at time t, respectively, which are the sum of the upward adjustment capabilities of the energy storage system and distributed power sources, and the sum of the downward adjustment capabilities of the energy storage system and distributed power sources. In this embodiment, F is determined jointly by the flexible resource adjustment capability model and the flexible tie switch adjustment capability. t U F t D Therefore, the upward and downward adjustment capabilities of the distribution network are based on the flexibility resource adequacy index, and the net load adaptability rate is also based on the flexibility resource adequacy index; w t Let P be the state variable representing the change in power of the net load at time t; t nl , These are the net load power at time t and time t+1, respectively; and These represent the sets of installation nodes for energy storage systems and distributed power sources, respectively; N is the number of flexible interconnection switches; P ESS Let be the rated power of the energy storage system, and take the minimum value of the rated power of the energy storage system as the up-adjustment capability of the energy storage system at node i at time t. and These represent the upper and lower limits of the flexible interconnection switch's adjustment capability at time t, respectively.

[0113] I FR A larger value indicates that the flexibility resources are better able to meet the random fluctuations of net load power, and that the overall flexibility of the distribution network is better.

[0114] The method proposed in this invention does not use a single flexibility resource adequacy index as an evaluation index for distribution network flexibility. Instead, based on the flexibility resource adequacy index, it further determines a supply-demand balance index to characterize the flexibility resource adequacy of the distribution network in meeting the random fluctuations of net load power.

[0115] Step 1.3: The average value of the sum of the current margins of the line and the flexible tie switch within the scheduling cycle is used as the transmission capacity index.

[0116] Existing technologies generally describe distribution network flexibility as either nodal flexibility (flexible resources) or branch flexibility (flexible transmission capacity). A typical distribution area has numerous flexible resources, and the sufficiency of these resources and the supply-demand balance index jointly determine the upper limit of distribution network flexibility. However, due to the small maximum current carrying capacity of lines, the sufficiency of flexible resources and the supply-demand balance index cannot be fully realized, thus hindering the distribution network's scheduling tasks. In other words, relying solely on dispatchable power is insufficient to achieve the goal of flexible distribution network operation, resulting in low utilization of flexible resources. Similarly, if a distribution area has a large maximum current carrying capacity but lacks flexible resources within the distribution network, the area can only be scheduled in real-time, and the source of the scheduled power can only rely on adjustments from the upper-level grid, failing to achieve the goal of interconnecting flexible resources within the distribution area. Therefore, distribution network flexibility assessment indicators include the flexible transmission capacity indicator in response to flexible resource scheduling.

[0117] Specifically, the higher the line's carrying capacity and the lower the average current carrying capacity, the stronger its ability to respond to flexible resource scheduling, i.e., the better its flexible transmission capability index. Therefore, the average value I of the sum of the current margins of the line and flexible tie switches within the scheduling cycle is used. GM As an indicator of flexible transmission capability, it satisfies the following relationship:

[0118]

[0119] In the formula, I GM For transmission capacity indicators, L represents the total number of lines, and N represents the total number of flexible tie switches; I WM,t and I SOPM,t Let be the current margins of the line and the flexible tie switch at time t, respectively, satisfying the following relationship:

[0120]

[0121]

[0122] In the formula, I ij,MAX I represents the maximum allowable current through branch ij; ij,t Let be the current flowing through branch ij at time t; P is the set of branches containing the flexible interconnection switch; SOP,MAX P represents the maximum active power that the port of the flexible tie switch is allowed to transmit; SOP,n,i,t and P SOP,n,j,t These represent the active power transmitted at time t on one port i and the other port j of the nth flexible interconnection switch.

[0123] The flexibility transmission capacity index characterizes the distribution network's ability to respond flexibly to random fluctuations in net load power. GM The smaller the value, the greater the current margin of each line and flexible interconnection switch, and the greater the flexible transmission capability.

[0124] This invention analyzes the flexibility resources of medium-voltage distribution networks containing standard operating procedures (SOPs) and defines supply-demand balance indicators and transmission capacity indicators for medium-voltage distribution networks to construct a distribution network flexibility evaluation index system.

[0125] Step 2: Based on a two-layer model structure, establish an optimization planning model for the medium-voltage flexible interconnection system, including: a planning layer model with the goal of minimizing the annual comprehensive operating cost, and an operation layer model with the goal of maximizing the difference between the supply-demand balance index and the transmission capacity index. The planning layer model provides the operation layer model with the configuration scheme of the energy storage system and flexible interconnection switches when the annual comprehensive operating cost is minimized, while the operation layer model provides the planning layer model with the system operating loss when the difference between the supply-demand balance index and the transmission capacity index is maximized. The planning layer model updates the annual comprehensive operating cost based on the received system operating loss.

[0126] Specifically, step 2 includes:

[0127] The planning-level model uses the annual comprehensive operating cost C T The minimum is the optimization objective, satisfying the following relationship:

[0128]

[0129] In the formula, The investment costs for SOP and ESS are respectively; The operating and maintenance costs of SOP and ESS are respectively, C PL This refers to the system's operating costs.

[0130] in,

[0131] 1) The investment cost and operation and maintenance cost of SOP satisfy the following relationship:

[0132]

[0133]

[0134] In the formula, d SOP y is the discount rate for the SOP. SOP For the lifespan of the SOP, c SOP η is the investment cost per unit capacity SOP. SOP S is the annual operating and maintenance cost coefficient for SOP. SOP,i Let N be the configuration capacity of the i-th SOP, and N be the total number of flexible interconnection switches.

[0135] 2) The investment cost and operation and maintenance cost of ESS satisfy the following relationship:

[0136]

[0137]

[0138] In the formula, d ESS Let y be the discount rate for ESS. ESS For the lifespan of ESS, and These are the rated power and rated capacity of the ESS, respectively. ESS,P and c ESS,E The installation costs per unit power and per unit capacity of the ESS are respectively. ESS For the maintenance cost per unit capacity of ESS, Y T For working hours.

[0139] 3) The system operating loss cost satisfies the following relationship:

[0140]

[0141] In the formula, η PL This is the power loss cost conversion factor. and These are network operation costs and SOP costs, respectively.

[0142] Establish the constraints for the optimization objective in the planning layer model, including:

[0143] 1) The capacity constraint of the flexible interconnection device satisfies the following relationship:

[0144]

[0145]

[0146] In the formula, S k,i and S k,j Let be the installed capacities of the k-th converter at nodes i and j, respectively. Let be the active power and reactive power of the nth SOP at node i at time t, respectively. These are the active power and reactive power of the nth SOP at node j at time t, respectively.

[0147] 2) The capacity constraints of the energy storage system satisfy the following relationship:

[0148]

[0149]

[0150] In the formula, and Let be the upper and lower limits of the capacity of the i-th energy storage system, respectively. Let be the capacity of the i-th energy storage system at time t. and Let represent the charging efficiency and discharging efficiency of the i-th energy storage system, respectively, and Δt be the charging time;

[0151] The planning layer model provides the operation layer model with the configuration scheme of energy storage system and flexible interconnection switch that minimizes the annual comprehensive operating cost.

[0152] The runtime model aims to maximize the difference between the supply-demand balance index and the transmission capacity index, satisfying the following relationship:

[0153] maxF DOWN =I FR,s -I GM,s

[0154] In the formula, F DOWN For scenario s, the supply and demand balance index I FR,s Transmission capability index I under scenario s GM,s The difference;

[0155] I FR A higher value indicates that the flexibility resources are better able to accommodate random fluctuations in net load power, signifying better overall flexibility of the distribution network; GM The smaller the value, the greater the current margin of each line and flexible interconnection switch, and the greater the flexible transmission capability; therefore, under a certain daily scenario s, the supply and demand balance index I FR,s Transmission capability index I under scenario s GM,s The larger the difference, the better the flexibility of the distribution network.

[0156] Establish the constraints for the optimization objective in the runtime model, including:

[0157] 1) The node voltage constraint condition satisfies the following relationship:

[0158] U i,min ≤U i (t)≤U i,max

[0159] In the formula, U i (t) represents the voltage value at node i at time t, U i,min and U i,max These are the lower and upper limits of the voltage at node i, respectively.

[0160] 2) The line transmission power constraint condition satisfies the following relationship:

[0161] Pl (t)≤P l,max

[0162] In the formula, P l (t) represents the active power transmitted by line l at time t, P l,max This represents the maximum active power that line l is allowed to transmit.

[0163] 3) The power flow balance constraint condition satisfies the following relationship:

[0164]

[0165] In the formula, P ac,i and Q ac,i G represents the active power and reactive power injected at node i, respectively. ac,ij B ij and θ ij U represents the conductance, susceptance, and voltage phase difference between node i and node j, respectively. ac,i and U ac,j P1 represents the voltage at node i and node j, respectively. β1 and β2 are 0-1 variables, indicating whether the node is connected to the flexible interconnection switch. SOP,ac The active power injected by the SOP at one port. N represents the active power flowing out of the SOP at another port. ac The total number of nodes;

[0166] 4) The power balance constraint condition for flexible interconnection devices satisfies the following relationship:

[0167]

[0168] In the formula, This refers to the active power loss of the SOP.

[0169] 5) The ESS charge / discharge constraint conditions satisfy the following relationship:

[0170]

[0171]

[0172]

[0173] In the formula, and Let represent the battery charge / discharge state variables of the energy storage system at node i at time t, both of which are 0-1 variables. and Let be the maximum active power of energy storage charging and discharging at node i at time t, respectively. and Let be the active power of energy storage charging and discharging at node i at time t, respectively.

[0174] Meanwhile, the ESS charging and discharging constraints are also constraints on the flexibility resource adjustment capability model. In the process of determining the flexibility resource adequacy index based on the flexibility resource adjustment capability model, the ESS charging and discharging has already been constrained. This is to configure the flexibility index under the premise of ensuring the safety of the energy storage system, reflecting that flexibility is a goal pursued on the basis of system safety and stability. In the process of solving the operation layer model, the optimization objective is constrained by the ESS charging and discharging again. At this time, since the starting basis for solving the operation layer model is the configuration scheme of the energy storage system and flexible interconnection switch provided by the planning layer model to the operation layer model when the annual comprehensive operating cost is the lowest, the flexibility index is configured again under the premise that the operation of the energy storage system meets the system economic requirements, reflecting the pursuit of both system economy and flexibility.

[0175] The operation layer model provides the planning layer model with the system operation loss when the difference between the supply and demand balance index and the transmission capacity index is maximized; the planning layer model updates the annual comprehensive operation cost based on the received system operation loss.

[0176] Step 3: Using the configuration scheme of the energy storage system and flexible interconnection switch as the decision variables of the game, and the optimization objectives of the planning layer model and the operation layer model as the game objects, a Nash equilibrium model is established. The particle swarm optimization algorithm is used to solve the Nash equilibrium model to obtain the optimal configuration scheme of the energy storage system and flexible interconnection switch, which is used as the planning result of the medium-voltage flexible interconnection distribution system.

[0177] Specifically, the configuration scheme for the energy storage system and the flexible interconnection switch includes: the capacity and location of the energy storage system, and the capacity and location of the flexible interconnection switch.

[0178] In this embodiment, the optimization objectives of the operation layer and the planning layer are treated as two individuals in a game. The capacity and position of SOP and ESS are the decision variables in the game. The established Nash equilibrium model satisfies the following relationship:

[0179] F OBF =max(F DOWN -d DOWN (C) T -d UP )

[0180] In the formula, F OBF For the Nash equilibrium model, d UP and d DOWN These are the negotiation breakdown points for the planning layer model and the operational layer model, respectively. In this embodiment, the specific numerical values ​​of the negotiation breakdown points are obtained by considering only the economic and flexibility scenarios in the numerical example analysis. T For annual comprehensive operating costs, FDOWN For scenario s, the supply and demand balance index I FR,s Transmission capability index I under scenario s GM,s The difference.

[0181] The particle swarm optimization algorithm is used to solve the Nash equilibrium model.

[0182] The optimization and upgrading of flexible interconnection in medium-voltage distribution networks is costly and requires high system flexibility. This invention first considers the power regulation characteristics and source-load distribution of flexible interconnection systems, proposing a distribution network flexibility evaluation index system and corresponding calculation methods. Based on this, an optimization planning method for medium-voltage flexible interconnection distribution systems that balances economy and flexibility is proposed. A distribution network flexibility evaluation model including SOPs (System-Operated Power Utilities) is established. Optimization planning is carried out based on a full evaluation of flexibility, which can reasonably allocate the capacity and location of SOPs and ESSs, while considering the operating status of SOPs and ESSs to reduce operating losses. In the process of distribution network planning, there is a mutually exclusive relationship between investment economy and system flexibility. By introducing the Nash equilibrium method, a reasonable equilibrium solution can be obtained, achieving the comprehensive optimization of the planning scheme.

[0183] Two IEEE 33-node diagrams were selected for flexible interconnection. The two terminal units were connected using a Standard Operating Procedure (SOP). The topology before the upgrade was as follows: Figure 2 As shown, Figure 2 The solid line represents the AC line, and the dashed line represents the tie switch. In transformer substation 1, nodes 7 and 30 are connected to the photovoltaic (PV) power station, each with an installed capacity of 1.8MW; nodes 14 and 20 are connected to the wind farm, each with an installed capacity of 1.2MW. In transformer substation 2, nodes 17 and 32 are connected to the photovoltaic (PV) power station, each with an installed capacity of 0.9MW; nodes 4 and 25 are connected to the wind farm, each with an installed capacity of 1.5MW.

[0184] When planning the conversion of two transformer substations to connect the end points through Standard Operating Procedures (SOPs), and intending to add an energy storage system in the substations, the optimal capacity of the SOP and the ESS and the optimal installation location of the ESS are obtained by adjusting the capacity of the SOP and the ESS using the method proposed in this invention, so as to ensure that economy and flexibility are balanced to a certain extent and that the two are relatively optimal.

[0185] Compared to the traditional weighted summation method of multi-objective optimization, the Nash negotiation model, combined with intelligent algorithms, can find the optimal equilibrium solution with flexibility and economy more accurately and quickly. To compare the advantages of Nash negotiation, the following scenarios were set up for simulation calculation, as shown in Table 1.

[0186] Table 1 Scene Design Table

[0187]

[0188]

[0189] In CASE3-1 and CASE3-2, the simulation results of CASE2-1 and CASE2-2 are first used to obtain the maximum and minimum values ​​of investment cost and flexibility, respectively. Then, the maximum-minimum normalization method is used to standardize the objective functions of the upper and lower levels to eliminate the impact of different magnitudes. The cost composition for each scenario is as follows: Figure 3 As shown.

[0190] The specific simulation results are shown in Table 2:

[0191] Table 2 Simulation Results

[0192] CASE3-1 CASE3-2 CASE3-3 SOP capacity(MW) 0.6735 0.6992 1.0322 ESS1 capacity(MW) 1.0008 0.9231 0.5769 ESS2 capacity (MW) 0.3047 0.4562 0.953 ESS1 installation location 30 25 21 ESS2 installation location 59 65 40 Total initial investment (ten thousand yuan) 1035.1968 1088.6757 1312.1081 Total cost (ten thousand yuan) 2487.2229 2555.4235 2786.6727 Operating costs (ten thousand yuan) 1452.0260 1455.7577 1474.5646 Flexibility Index 52.2170 54.6050 66.2114

[0193] As can be seen from Table 2, although CASE3-1 and CASE3-2 have sufficient schedulable flexibility resources overall, their flexibility indices are significantly lower than those of CASE3-3. Specifically, the schedulable time does not fully meet the system's flexibility requirements. This is because the traditional weighting method is not accurate enough when balancing the mutually exclusive and dynamic model of economy and flexibility. Furthermore, the weighting calculation method is often easily affected by objective data or subjective opinions, which can lead to deviations and impacts on actual engineering projects.

[0194] This invention also proposes a planning system for a medium-voltage flexible interconnected distribution system aimed at improving flexibility. The flexibility resources of the distribution network include energy storage systems and distributed power sources. The planning system includes:

[0195] The flexible indicator establishment module is used to obtain the operating parameters and regulation capabilities of energy storage systems and distributed power sources. Based on the flexible resource regulation capability model, it determines the flexibility resource adequacy index; based on the flexibility resource adequacy index and the regulation capability of flexible tie switches, it determines the distribution network regulation capability. The ratio of the distribution network regulation capability to the change in net load power within the scheduling cycle is used as the supply and demand balance index; and the average value of the sum of the current margins of lines and flexible tie switches within the scheduling cycle is used as the transmission capacity index.

[0196] The optimization planning model building module is used to establish an optimization planning model for a medium-voltage flexible interconnected power distribution system based on a two-layer model structure. This model includes: a planning layer model with the goal of minimizing annual comprehensive operating costs, and an operation layer model with the goal of maximizing the difference between supply-demand balance indicators and transmission capacity indicators. The planning layer model provides the operation layer model with the configuration schemes of the energy storage system and flexible interconnection switches when the annual comprehensive operating costs are minimized. The operation layer model provides the planning layer model with the system operating losses when the difference between the supply-demand balance indicators and transmission capacity indicators is maximized. The planning layer model updates the annual comprehensive operating costs based on the received system operating losses.

[0197] The model solving module is used to establish a Nash equilibrium model with the configuration schemes of the energy storage system and flexible interconnection switch as decision variables in a game, and the optimization objectives of the planning layer model and the operation layer model as game objects. The particle swarm optimization algorithm is used to solve the Nash equilibrium model to obtain the optimal configuration schemes of the energy storage system and flexible interconnection switch, which serve as the planning results of the medium-voltage flexible interconnected power distribution system.

[0198] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0199] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0200] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0201] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0202] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A planning method for a medium-voltage flexible interconnected distribution system aimed at improving flexibility, wherein the flexibility resources of the distribution network include energy storage systems and distributed power sources, characterized in that, Planning methods include: The operating parameters and regulation capabilities of energy storage systems and distributed power sources are obtained. Based on the flexibility resource regulation capability model, the flexibility resource adequacy index is determined. Based on the flexibility resource adequacy index and the regulation capability of flexible tie switches, the distribution network regulation capability is determined. The ratio of the distribution network regulation capability to the change in net load power during the scheduling cycle is used as the supply and demand balance index. The average value of the sum of the current margins of lines and flexible tie switches during the scheduling cycle is used as the transmission capacity index. Based on a two-layer model structure, an optimization planning model for a medium-voltage flexible interconnection system is established, comprising: a planning layer model with the goal of minimizing annual comprehensive operating costs, and an operation layer model with the goal of maximizing the difference between the supply-demand balance index and the transmission capacity index. The planning layer model provides the operation layer model with the configuration schemes of the energy storage system and flexible interconnection switches when the annual comprehensive operating costs are minimized, while the operation layer model provides the planning layer model with the system operating losses when the difference between the supply-demand balance index and the transmission capacity index is maximized. The planning layer model updates the annual comprehensive operating costs based on the received system operating losses. Using the configuration schemes of energy storage systems and flexible interconnection switches as decision variables in a game, and the optimization objectives of the planning layer model and the operation layer model as game objects, a Nash equilibrium model is established. The particle swarm optimization algorithm is used to solve the Nash equilibrium model to obtain the optimal configuration schemes of energy storage systems and flexible interconnection switches, which serve as the planning results for medium-voltage flexible interconnected power distribution systems.

2. The planning method for medium-voltage flexible interconnected power distribution systems with improved flexibility according to claim 1, characterized in that, Establish a flexible resource regulation capability model; obtain the operating parameters and regulation capabilities of energy storage systems and distributed power sources, and determine the flexibility resource adequacy index through the flexible resource regulation capability model; The flexible resource adjustment capability model satisfies the following relationship: In the formula, and These represent the up-adjustment and down-adjustment capabilities of the energy storage system at node i at time t, respectively. and , , are the battery charge / discharge state variables of the energy storage system at node i at time t, both of which are 0-1 variables; and , respectively, represent the active power of energy storage charging and discharging at node i at time t; and These represent the maximum active power of energy storage charging and discharging at node i at time t, respectively. and P represents the up-modulation and down-modulation capabilities of the distributed power source at node i at time t, respectively. DG,i,t P represents the active power of the distributed power source at node i at time t. DG,i,t,max and P DG,i,t,min These are the maximum and minimum active power outputs of the distributed power source at node i, respectively. and These are the upward and downward ramp power limits for the distributed power source at node i, respectively.

3. The planning method for medium-voltage flexible interconnected power distribution systems with improved flexibility according to claim 2, characterized in that, Based on the flexibility resource adequacy index and the flexible interconnection switch regulation capacity, the distribution network regulation capacity is determined, and the ratio of the distribution network regulation capacity to the net load power change during the dispatching cycle is used as the supply and demand balance index. The supply and demand balance index satisfies the following relationship: In the formula, I FR As a supply and demand balance indicator, I UFR I is the sum of the ratios of the available schedulable margin of flexible resources to the change in net load when the net load increases within a scheduling cycle. DFR F is the sum of the ratios of the available schedulable margin of flexible resources to the change in net load when the net load decreases within a scheduling cycle, where T is the total number of time periods within the scheduling cycle; t U F t D Let w represent the up-regulation capacity and down-regulation capacity of the distribution network at time t, respectively; w represents the sum of the up-regulation capacity of the energy storage system and the distributed power generation, respectively; w represents the sum of the down-regulation capacity of the energy storage system and the distributed power generation. t Let P be the state variable representing the change in power of the net load at time t; t nl , These are the net load power at time t and time t+1, respectively; and These represent the sets of installation nodes for energy storage systems and distributed power sources, respectively; N is the number of flexible interconnection switches; P ESS Let be the rated power of the energy storage system, and take the minimum value of the rated power of the energy storage system as the up-adjustment capability of the energy storage system at node i at time t. and These represent the upper and lower limits of the adjustment capability of the flexible interconnection switch i at time t, respectively.

4. The planning method for medium-voltage flexible interconnected power distribution systems with improved flexibility according to claim 3, characterized in that, The average value of the sum of the current margins of the line and the flexible tie switch within the scheduling cycle is used as the transmission capacity index, satisfying the following relationship: In the formula, I GM For transmission capacity indicators, L represents the total number of lines, and N represents the total number of flexible tie switches; I WM,t and I SOPM,t Let be the current margins of the line and the flexible tie switch at time t, respectively, satisfying the following relationship: In the formula, I ij,MAX I represents the maximum allowable current through branch ij; ij,t Let be the current flowing through branch ij at time t; P is the set of branches containing the flexible interconnection switch; SOP,MAX P represents the maximum active power that the port of the flexible tie switch is allowed to transmit; SOP,n,i,t and P SOP,n,j,t These represent the active power transmitted at time t on one port i and the other port j of the nth flexible interconnection switch.

5. The planning method for medium-voltage flexible interconnected power distribution systems with improved flexibility according to claim 1, characterized in that, The planning-level model uses the annual comprehensive operating cost C T The minimum is the optimization objective, satisfying the following relationship: In the formula, These are the investment costs for flexible interconnection switches and energy storage systems, respectively. The operating and maintenance costs of the flexible interconnection switch and the energy storage system are respectively, C PL This refers to the system's operating costs. in, 1) The investment cost and operation and maintenance cost of the flexible interconnection switch satisfy the following relationship: In the formula, d SOP The discount rate for flexible interconnection switches, y SOP To extend the service life of the flexible interconnecting switch, c SOP η represents the investment cost per unit capacity of flexible interconnection switch. SOP S represents the annual operation and maintenance cost coefficient of the flexible interconnection switch. SOP,i Let N be the configuration capacity of the i-th flexible tie switch, and N be the total number of flexible tie switches. 2) The investment cost and operation and maintenance cost of ESS satisfy the following relationship: In the formula, d ESS Let y be the discount rate for ESS. ESS For the lifespan of ESS, and These are the rated power and rated capacity of the ESS, respectively. ESS,P and c ESS,E The installation costs per unit power and per unit capacity of the ESS are respectively. ESS For the maintenance cost per unit capacity of ESS, Y T For working hours; 3) The system operating loss cost satisfies the following relationship: In the formula, η PL This is the power loss cost conversion factor. and These are network operation losses and flexible interconnection switching losses, respectively.

6. The planning method for medium-voltage flexible interconnected power distribution systems with improved flexibility according to claim 5, characterized in that, Establish the constraints for the optimization objective in the planning layer model, including: 1) The capacity constraint of the flexible interconnection device satisfies the following relationship: In the formula, S k,i and S k,j Let be the installed capacities of the k-th converter at nodes i and j, respectively. Let be the active power and reactive power of the nth flexible tie switch at node i at time t, respectively. These are the active power and reactive power of the nth flexible tie switch at node j at time t, respectively. 2) The capacity constraints of the energy storage system satisfy the following relationship: In the formula, and Let be the upper and lower limits of the capacity of the i-th energy storage system, respectively. Let be the capacity of the i-th energy storage system at time t. and Let represent the charging efficiency and discharging efficiency of the i-th energy storage system, respectively, and Δt be the charging time.

7. The planning method for medium-voltage flexible interconnected power distribution systems with improved flexibility according to claim 1, characterized in that, The runtime model aims to maximize the difference between the supply-demand balance index and the transmission capacity index, satisfying the following relationship: maxF DOWN =I FR,s -I GM,s In the formula, F DOWN For scenario s, the supply and demand balance index I FR,s Transmission capability index I under scenario s GM,s The difference.

8. The planning method for medium-voltage flexible interconnected power distribution systems with improved flexibility according to claim 7, characterized in that, Establish the constraints for the optimization objective in the runtime model, including: 1) The node voltage constraint condition satisfies the following relationship: U i,min ≤U i (t)≤U i,max In the formula, U i (t) represents the voltage value at node i at time t, U i,min and U i,max These are the lower and upper limits of the voltage at node i, respectively; 2) The line transmission power constraint condition satisfies the following relationship: P l (t)≤P l,max In the formula, P l (t) represents the active power transmitted by line l at time t, P l,max This represents the maximum active power that line l is allowed to transmit. 3) The power flow balance constraint condition satisfies the following relationship: In the formula, P ac,i and Q ac,i G represents the active power and reactive power injected at node i, respectively. ac,ij B ij and θ ij U represents the conductance, susceptance, and voltage phase difference between node i and node j, respectively. ac,i and U ac,j P1 represents the voltage at node i and node j, respectively. β1 and β2 are 0-1 variables, indicating whether the node is connected to the flexible interconnection switch. SOP,ac The active power injected by the SOP at one port. N represents the active power flowing out of the SOP at another port. ac The total number of nodes; 4) The power balance constraint condition for flexible interconnection devices satisfies the following relationship: In the formula, The active power loss of SOP; 5) The ESS charge / discharge constraint conditions satisfy the following relationship: In the formula, and Let represent the battery charge / discharge state variables of the energy storage system at node i at time t, both of which are 0-1 variables. and Let be the maximum active power of energy storage charging and discharging at node i at time t, respectively. and Let be the active power of energy storage charging and discharging at node i at time t, respectively.

9. The planning method for medium-voltage flexible interconnected power distribution systems with improved flexibility according to claim 1, characterized in that, The Nash equilibrium model satisfies the following relationship: F OBF =max(F DOWN -d DOWN )(C T -d UP ) In the formula, F OBF For the Nash equilibrium model, d UP and d DOWN The negotiation breakdown points for the planning layer model and the operational layer model are C, respectively. T For annual comprehensive operating costs, F DOWN This represents the difference between the supply-demand balance index and the transmission capacity index in the given scenario.

10. A planning system for a medium-voltage flexible interconnected distribution system aimed at improving flexibility, wherein the flexibility resources of the distribution network include energy storage systems and distributed power sources, characterized in that, The planning system includes: The flexible indicator establishment module is used to obtain the operating parameters and regulation capabilities of energy storage systems and distributed power sources. Based on the flexible resource regulation capability model, it determines the flexibility resource adequacy index; based on the flexibility resource adequacy index and the regulation capability of flexible tie switches, it determines the distribution network regulation capability. The ratio of the distribution network regulation capability to the change in net load power within the scheduling cycle is used as the supply and demand balance index; and the average value of the sum of the current margins of lines and flexible tie switches within the scheduling cycle is used as the transmission capacity index. The optimization planning model building module is used to establish an optimization planning model for a medium-voltage flexible interconnected power distribution system based on a two-layer model structure. This model includes: a planning layer model with the goal of minimizing annual comprehensive operating costs, and an operation layer model with the goal of maximizing the difference between supply-demand balance indicators and transmission capacity indicators. The planning layer model provides the operation layer model with the configuration schemes of the energy storage system and flexible interconnection switches when the annual comprehensive operating costs are minimized. The operation layer model provides the planning layer model with the system operating losses when the difference between the supply-demand balance indicators and transmission capacity indicators is maximized. The planning layer model updates the annual comprehensive operating costs based on the received system operating losses. The model solving module is used to establish a Nash equilibrium model with the configuration schemes of the energy storage system and flexible interconnection switch as decision variables in a game, and the optimization objectives of the planning layer model and the operation layer model as game objects. The particle swarm optimization algorithm is used to solve the Nash equilibrium model to obtain the optimal configuration schemes of the energy storage system and flexible interconnection switch, which serve as the planning results of the medium-voltage flexible interconnected power distribution system.

11. A terminal, comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method according to any one of claims 1-9.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1-9.

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