Power distribution network expansion planning method and system considering light storage and charging collaborative optimization access

Abstract

The invention discloses a power distribution network extension planning method and system considering light storage and charging collaborative optimization access, and the method comprises the steps: constructing a target function of power distribution network planning, and considering the investment cost and operation cost; considering power generation power supply constraints, including distributed power supply and superior power grid power purchase; energy storage configuration and operation constraints are considered; the constraint of the optical storage and charging access distribution network is considered; considering operation constraints of the power distribution network; based on a target function of power distribution network planning, power generation power supply constraints, energy storage configuration and operation constraints, constraints of optical storage and charging access to a distribution network and operation constraints of the power distribution network, a distribution network extension planning model considering optical storage and charging collaborative optimization access is established, a Gurobi and CPLEX solver is called in MATLAB for solving, and a power distribution network extension planning scheme is obtained. The method can relieve the local load pressure, reasonably expand the infrastructure of the power distribution network, and ensure the safe operation of the power distribution network.

Description

Technical Field

[0001] This invention belongs to the field of power system planning, specifically relating to a distribution network expansion planning method and system that considers the coordinated and optimized access of photovoltaic, energy storage and charging systems. Background Technology

[0002] Electric vehicles, as a crucial support for achieving this goal, are rapidly gaining popularity and becoming an important component of clean energy transportation. Simultaneously, the installed capacity of distributed photovoltaic (PV) power is also showing a rapid growth trend, placing higher demands on the carrying capacity of urban power distribution networks. The grid-connected operation of electric vehicles and highly penetrated distributed PV systems will significantly increase the load on the power distribution network and may lead to problems such as uneven power flow distribution, localized overloads, and voltage exceeding limits. Specifically, there is a significant time-of-day mismatch between distributed PV power generation and electric vehicle charging demand. Since PV power generation is concentrated during the daytime, while electric vehicle charging demand typically occurs at night, the severe load mismatch causes increased fluctuations in grid load, thereby affecting the safe operation of the power grid.

[0003] To address the aforementioned issues, existing research has proposed a collaborative planning method for distributed photovoltaic (PV) power generation and electric vehicle (EV) charging stations. This method aims to optimize the spatial layout of PV systems and charging stations, and mitigate the time mismatch between PV power output and EV charging load through the rational configuration of energy storage systems. Energy storage systems can store energy during periods of excess PV power generation and release energy during peak charging demand, thereby balancing the load, reducing grid pressure, and improving grid operating efficiency and security.

[0004] However, existing research essentially involves the unified planning of distribution networks, distributed photovoltaic (PV) systems, and charging stations, meaning a single entity simultaneously makes decisions regarding the site selection and capacity determination for PV and charging, as well as distribution network expansion. In this framework, PV and charging are typically assumed to be connected to the nearest available grid. In reality, on the one hand, distributed PV and charging stations are usually invested in and constructed by third-party entities, meaning the grid company cannot fully control their capacity and location; on the other hand, due to limitations in land and transportation, suitable sites for PV and charging may not have the conditions for direct grid connection. Therefore, how to further optimize the location of PV, energy storage, and charging connections to the distribution network, rationally plan grid load distribution, and ensure the safe operation of the distribution network under new load conditions has become a pressing technical challenge. Summary of the Invention

[0005] The purpose of this invention is to address the problems of spatiotemporal mismatch between energy source and load caused by the rapid growth in electric vehicle charging demand and the grid connection of distributed photovoltaic (PV) systems. It provides a distribution network expansion planning method and system that considers the coordinated and optimized access of PV, energy storage, and charging. This invention optimizes the access location and energy storage configuration of PV, energy storage, and charging systems by coordinating PV output, electric vehicle charging characteristics, and energy storage regulation capabilities. This alleviates local load pressure, rationally expands distribution network infrastructure, and ensures the safe operation of the distribution network. Simultaneously, it provides technical support for the construction of urban distribution networks for the continued development of electric vehicles and distributed PV, promoting the low-carbon transformation of energy and transportation systems.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: The distribution network expansion planning method considering the coordinated and optimized access of photovoltaic, energy storage, and charging systems includes the following steps: Step 1: Construct the objective function for distribution network planning, considering investment costs and operating costs; where investment costs include distributed generation costs, energy storage construction costs, substation expansion costs, distribution network line expansion costs, and access line construction costs, and all investment costs are calculated on an equal annual basis; operating costs include the cost of electricity purchased from the upper-level grid, the generation costs of distributed generation sources, and the cost of electricity purchased and curtailed from renewable energy sources. Step 2: Consider the constraints of power generation sources, including distributed generation and power purchased from the upper-level grid. The power purchased from the upper-level grid is used as the output of each substation and is regarded as a distributed generation source. At the same time, the upper and lower limits of active and reactive power are considered, and the power output can only be effective when the state variable of the construction is 1. Distributed photovoltaics also satisfy the requirement that the sum of actual output and abandoned power is the actual usable power. Step 3: Consider energy storage configuration and operation constraints, including power constraints and energy constraints. The charging and discharging power must meet the power constraint limit, and the energy stored in the battery must meet the energy constraint limit. Step 4: Consider the constraints of photovoltaic, energy storage, and charging network access to the distribution network; through the deployment and construction status variables of the access lines. The locations for distributed photovoltaic power stations, energy storage power stations, and electric vehicle charging stations to connect to the distribution network are determined, while the connection lines must meet power flow constraints. A linear Dist-flow model is used for modeling, and the Big M method and other methods are employed. Determine whether a current flow constraint needs to be added; Step 5: Consider distribution network operation constraints; distribution network branches must satisfy upper and lower limits of transmission power and power flow constraints, using state variables. Determine the necessary expansion lines for the distribution network, and ensure that the node voltage meets the upper and lower voltage limits. Also, ensure that each node in the distribution network maintains a balance between active and reactive power. Step Six: Based on the objective function of the distribution network planning, the constraints of power generation, the constraints of energy storage configuration and operation, the constraints of photovoltaic, energy storage and charging access to the distribution network, and the constraints of distribution network operation, establish a distribution network extension planning model that considers the coordinated and optimized access of photovoltaic, energy storage and charging. Solve the model in MATLAB using the Gurobi and CPLEX solvers to obtain the distribution network extension planning scheme.

[0007] A further improvement of this invention is that, in step one, the objective function is as shown in equations (1)-(4): (1) (2) (3) (4) In the formula: For total cost, The respective y Annual investment and operating costs of power distribution network facilities; These are the investment costs for distributed power generation and the construction costs for energy storage, respectively. These are the costs of substation expansion and distribution network line expansion, respectively. Cost of access lines for electric vehicle charging stations, distributed photovoltaic and energy storage power stations; Indicates the construction status of the corresponding equipment; This represents the unit investment cost of the corresponding equipment, of which These are the construction costs per unit power and per unit capacity of energy storage power stations, respectively. To maximize the output of distributed power sources, Divided into energy storage power stations up to the [number] y The total power and electricity capacity invested and constructed in the year For the addition of transformer capacity to the substation; All represent distribution network node numbers. This indicates the node number of a distributed photovoltaic power station, an electric vehicle charging station, and an energy storage power station. To extend the length of the distribution network lines, The length of the access line to be constructed; This is the power curve for a distributed power source. The distributed power source is providing power at that moment. and These represent the actual available power and the amount of abandoned power of distributed photovoltaic power at that moment, respectively. and These are the cost coefficients for photovoltaic power purchase and curtailment, respectively. Typical daily weighting; These correspond to the year, typical day, and hour, respectively.

[0008] A further improvement of this invention is that, in step two, the power output of the distributed power source satisfies the following constraints (5)-(6): (5) (6) In the formula: The lower bound of active power output of distributed power sources This indicates the upper limit of reactive power output, meaning that both the active and reactive power outputs of the distributed power source are within the limits. Distributed photovoltaic systems satisfy the following constraints (7)-(9): (7) (8) (9) In the formula: This represents the actual available power of distributed photovoltaic power at that moment. To contribute practically and effectively "Power output without reactive power" means that the output of distributed photovoltaic power is all within the boundary.

[0009] A further improvement of the present invention is that, in step three, the charging and discharging power meets the power constraint limit, and the amount of electricity stored in the battery meets the electricity constraint limit, as shown in equations (10)-(15) below: (10) (11) (12) (13) (14) (15) In the formula: Energy storage power stations ess The active and reactive power of charging and discharging. The amount of electricity stored at that moment; This indicates the minimum percentage of energy the battery needs to store. These represent the battery's charge and discharge efficiencies, respectively.

[0010] A further improvement of this invention is that, in step four, the deployment status variable of the access line is used. The locations for distributed photovoltaic power stations, energy storage power stations, and electric vehicle charging stations to connect to the distribution network are determined, while the connection lines must meet power flow constraints. A linear Dist-flow model is used for modeling, and the Big M method and other methods are employed. Determine whether power flow constraints need to be added, as shown in equations (16)-(17): (16) (17) In the formula: This indicates the node voltage at each station. Indicates the voltage at the distribution network node; Each station on the access line at that time The active and reactive power output; For transformer turns ratio, For the resistance and reactance of the connection line, For the voltage level of the access line, M For sufficiently large positive numbers; The node power of each station must be kept balanced, and the node voltage and transmission line capacity must meet the upper and lower limits, as shown in equations (18)-(22) below: (18) (19) (20) (twenty one) (twenty two) In the formula: It represents the active and reactive power output of distributed photovoltaic power stations, electric vehicle charging stations, and energy storage power stations; For charging stations m Voltage upper and lower limits; These are the maximum active and reactive power transmitted by the line, respectively. The output of each station to each node of the distribution network is expressed by the following formulas (23)-(25): (twenty three) (twenty four) (25) in These represent the node numbers of distributed photovoltaic power stations, electric vehicle charging stations, and energy storage power stations, respectively. These respectively represent the distributed photovoltaic, energy storage power station, and electric vehicle charging station injected into the distribution network node at that moment. The active power.

[0011] A further improvement of this invention is that, in step five, the distribution network branches satisfy the upper and lower limits of transmission power and power flow constraints, using state variables. Determine the required expansion lines for the distribution network, and ensure that the node voltage meets the upper and lower voltage limits. The active and reactive power of each node in the distribution network must be balanced, as shown in equations (26)-(32) below: (26) (27) (28) (29) (30) (31) (32) In the formula: These are the distribution network branches at that time. The active and reactive power flowing upstream; These represent the normal active and reactive loads on the nodes; the remaining variables and parameters are similar to the constraints of the access lines. In addition, each distribution network node substation must meet the capacity limit constraint: (33) In the formula: This represents the original upper limit of the substation's capacity. This indicates its power factor angle.

[0012] A distribution network expansion planning system considering the coordinated and optimized access of photovoltaic, energy storage, and charging infrastructure includes: Objective function construction unit: Constructs the objective function for distribution network planning, considering investment costs and operating costs; where investment costs include distributed generation costs, energy storage construction costs, substation expansion costs, distribution network line expansion costs, and access line construction costs, and all investment costs are calculated on an equal annual basis; operating costs include the cost of purchasing electricity from the upper-level grid, the generation costs of distributed generation sources, and the cost of purchasing and curtailing electricity from renewable energy sources. First constraint unit: Consider the constraints of power generation sources, including distributed power sources and power purchased from the upper-level grid. The power purchased from the upper-level grid is used as the output of each substation and is regarded as a distributed power source. At the same time, the upper and lower limits of active and reactive power are considered, and the power output can only be effective when the state variable of the construction is 1. Distributed photovoltaics also satisfy the requirement that the sum of actual output and abandoned power is the actual usable power. The second constraint unit considers energy storage configuration and operation constraints, including power constraints and energy constraints. The charging and discharging power meets the power constraint limit, and the energy stored in the battery meets the energy constraint limit. The third constraint unit considers the constraints of photovoltaic, energy storage, and charging network access to the distribution network; through the state variables of the access line construction. The locations for distributed photovoltaic power stations, energy storage power stations, and electric vehicle charging stations to connect to the distribution network are determined, while the connection lines must meet power flow constraints. A linear Dist-flow model is used for modeling, and the Big M method and other methods are employed. Determine whether a current flow constraint needs to be added; Fourth constraint unit: Considering distribution network operation constraints; distribution network branches satisfy upper and lower limits of transmission power and power flow constraints, using state variables. Determine the necessary expansion lines for the distribution network, and ensure that the node voltage meets the upper and lower voltage limits. Also, ensure that each node in the distribution network maintains a balance between active and reactive power. Distribution network expansion planning model establishment and solution unit: Based on the objective function of distribution network planning, power generation constraints, energy storage configuration and operation constraints, constraints of photovoltaic, energy storage and charging access to the distribution network, and distribution network operation constraints, a distribution network expansion planning model considering the coordinated and optimized access of photovoltaic, energy storage and charging is established. The model is solved by calling the Gurobi and CPLEX solvers in MATLAB to obtain the distribution network expansion planning scheme.

[0013] A further improvement of this invention is that, in the objective function construction unit, the objective function is as shown in equations (1)-(4): (1) (2) (3) (4) In the formula: For total cost, The respective y Annual investment and operating costs of power distribution network facilities; These are the investment costs for distributed power generation and the construction costs for energy storage, respectively. These are the costs of substation expansion and distribution network line expansion, respectively. Cost of access lines for electric vehicle charging stations, distributed photovoltaic and energy storage power stations; Indicates the construction status of the corresponding equipment; This represents the unit investment cost of the corresponding equipment, of which These are the construction costs per unit power and per unit capacity of energy storage power stations, respectively. To maximize the output of distributed power sources, Divided into energy storage power stations up to the [number] y The total power and electricity capacity invested and constructed in the year For the addition of transformer capacity to the substation; All represent distribution network node numbers. This indicates the node number of a distributed photovoltaic power station, an electric vehicle charging station, and an energy storage power station. To extend the length of the distribution network lines, The length of the access line to be constructed; This is the power curve for a distributed power source. The distributed power source is providing power at that moment. and These represent the actual available power and the amount of abandoned power of distributed photovoltaic power at that moment, respectively. and These are the cost coefficients for photovoltaic power purchase and curtailment, respectively. Typical daily weighting; These correspond to the year, typical day, and hour, respectively.

[0014] A further improvement of this invention is that, in the first constraint unit, the power output of the distributed power source satisfies the following constraints (5)-(6): (5) (6) In the formula: The lower bound of active power output of distributed power sources This indicates the upper limit of reactive power output, meaning that both the active and reactive power outputs of the distributed power source are within the limits. Distributed photovoltaic systems satisfy the following constraints (7)-(9): (7) (8) (9) In the formula: This represents the actual available power of distributed photovoltaic power at that moment. To contribute practically and effectively "Power output without reactive power" means that the output of distributed photovoltaic power is all within the boundary.

[0015] A further improvement of the present invention is that, in the second constraint unit, the charging and discharging power satisfies the power constraint, and the amount of electricity stored in the battery satisfies the amount of electricity constraint, as shown in equations (10)-(15) below: (10) (11) (12) (13) (14) (15) In the formula: Energy storage power stations ess The active and reactive power of charging and discharging. The amount of electricity stored at that moment; This indicates the minimum percentage of energy the battery needs to store. These represent the battery's charge and discharge efficiencies, respectively.

[0016] Compared with the prior art, the present invention has at least the following beneficial technical effects: This invention provides a distribution network expansion planning method and system considering the coordinated and optimized access of photovoltaic, energy storage, and charging stations. With distribution network expansion and coordinated and optimized access of photovoltaic, energy storage, and charging stations as the core, it optimizes distribution network planning schemes by constructing a model with the sum of distribution network investment costs and operating costs as the objective function. The model incorporates conditions such as node power balance constraints, distribution line power flow constraints, substation capacity limitations, and voltage limitations. It also coordinates and optimizes the access locations of photovoltaic, energy storage, and charging stations within the distribution network to achieve spatiotemporal matching of source and load, ensuring the safe operation of the distribution network and fully demonstrating the significant advantages of the proposed method in reducing distribution network costs. Attached Figure Description

[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is an overall flowchart of the method of the present invention.

[0019] Figure 2 This is a schematic diagram of a 56-node high-voltage distribution network in a certain city.

[0020] Figure 3 This is a comparison chart of expansion costs.

[0021] Figure 4 This is a comparison chart of access locations.

[0022] Figure 5 This is a structural block diagram of the system of the present invention. Detailed Implementation

[0023] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0024] In the description of this invention, it should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0025] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0026] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0027] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0028] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0029] Example 1 The present invention provides a distribution network expansion planning method that considers the coordinated and optimized access of photovoltaic, energy storage and charging infrastructure. The method models the distribution network and uses the investment cost and operating cost of the distribution network facilities, i.e., the total cost, as the objective function. The main constraints include the access constraints of photovoltaic, energy storage and charging infrastructure to the distribution network, the power flow constraints of distribution lines, the power balance constraints of nodes, and the capacity limitations of substations.

[0030] To fully demonstrate the advantages of this invention, the total cost of the distribution network planning model is analyzed by gradually adding different constraints. The analysis mainly consists of five steps, the specific implementation steps of which are as follows: Step 1: Constructing the objective function for distribution network planning requires considering investment costs and operating costs. Investment costs include distributed generation costs, energy storage construction costs, substation expansion costs, distribution network line expansion costs, and access line construction costs, all calculated on an annual basis. Operating costs include the cost of electricity purchased from the upper-level grid, the generation costs of distributed generation sources, and the cost of purchasing and curtailing renewable energy sources. The objective function is shown in equations (1)-(4): (1) (2) (3) (4) In the formula: For total cost, The respective y Annual investment and operating costs of power distribution network facilities; These are the investment costs for distributed power generation and the construction costs for energy storage, respectively. These are the costs of substation expansion and distribution network line expansion, respectively. Cost of access lines for electric vehicle charging stations, distributed photovoltaic and energy storage power stations; Indicates the construction status of the corresponding equipment; This represents the unit investment cost of the corresponding equipment, of which These are the construction costs per unit power and per unit capacity of energy storage power stations, respectively. To maximize the output of distributed power sources, Divided into energy storage power stations up to the [number] y The total power and electricity capacity invested and constructed in the year For the addition of transformer capacity to the substation; All represent distribution network node numbers. This indicates the node number of a distributed photovoltaic power station, an electric vehicle charging station, and an energy storage power station. To extend the length of the distribution network lines, The length of the access line to be constructed; This is the power curve for a distributed power source. The distributed power source is providing power at that moment. and These represent the actual available power and the amount of abandoned power of distributed photovoltaic power at that moment, respectively. and These are the cost coefficients for photovoltaic power purchase and curtailment, respectively. Typical daily weighting; These correspond to the year, typical day, and hour, respectively.

[0031] Step Two: Consider power generation constraints, including distributed generation and electricity purchased from the upstream grid. Electricity purchased from the upstream grid serves as the output of each substation, and its operational constraints are similar to those of distributed generation; for simplicity, it is treated as distributed generation. Both active and reactive power limits need to be considered simultaneously, and effective output is only possible when the deployment state variable is 1. Furthermore, distributed photovoltaic systems must satisfy the condition that the sum of actual output and wasted power equals the actual usable power.

[0032] The power output of distributed power sources should meet the following constraints (5)-(6): (5) (6) In the formula: The lower bound of active power output of distributed power sources This indicates the upper limit of reactive power output, meaning that both the active and reactive power outputs of the distributed power source are within the limits.

[0033] Distributed photovoltaic systems should meet the following constraints (7)-(9): (7) (8) (9) In the formula: This represents the actual available power of distributed photovoltaic power at that moment. To contribute practically and effectively "Power output without reactive power" means that the output of distributed photovoltaic power is all within the boundary.

[0034] Step 3: Consider energy storage configuration and operational constraints. The constraints of the energy storage system include power constraints and energy constraints. The charging and discharging power must meet the power constraint limit, and the energy stored in the battery must meet the energy constraint limit, as shown in equations (10)-(15) below: (10) (11) (12) (13) (14) (15) In the formula: Energy storage power stations ess The active and reactive power of charging and discharging. The amount of electricity stored at that moment; This indicates the minimum percentage of energy the battery needs to store. These represent the battery's charge and discharge efficiencies, respectively.

[0035] Step 4: Consider the constraints of photovoltaic, energy storage, and charging network access to the distribution network. This is done through the deployment and state variables of the access lines. The locations for distributed photovoltaic power stations, energy storage power stations, and electric vehicle charging stations to connect to the distribution network are determined, while the connection lines must meet power flow constraints. A linear Dist-flow model is used for modeling, and the Big M method and other methods are employed. Determine whether power flow constraints need to be added, as shown in equations (16)-(17): (16) (17) In the formula: This indicates the node voltage at each station. Indicates the voltage at the distribution network node; Each station on the access line at that time The active and reactive power output; For transformer turns ratio, For the resistance and reactance of the connection line, For the voltage level of the access line, M For sufficiently large positive numbers.

[0036] The node power of each station must be kept balanced, and the node voltage and transmission line capacity must meet the upper and lower limits, as shown in equations (18)-(22) below: (18) (19) (20) (twenty one) (twenty two) In the formula: It represents the active and reactive power output of distributed photovoltaic power stations, electric vehicle charging stations, and energy storage power stations; For charging stations m Voltage upper and lower limits; These represent the maximum active and reactive power transmitted by the line, respectively.

[0037] The output of each station to each node of the distribution network is expressed by the following formulas (23)-(25): (twenty three) (twenty four) (25) in These represent the node numbers of distributed photovoltaic power stations, electric vehicle charging stations, and energy storage power stations, respectively. These respectively represent the distributed photovoltaic, energy storage power station, and electric vehicle charging station injected into the distribution network node at that moment. The active power.

[0038] Step 5: Consider distribution network operation constraints. Similar to the constraints of photovoltaic, energy storage, and charging network integration into the distribution network, distribution network branches also need to meet upper and lower limits of transmission power and power flow constraints, expressed as state variables. Determine the required expansion lines for the distribution network, and ensure that the node voltage meets the upper and lower voltage limits. The active and reactive power of each node in the distribution network must be balanced, as shown in equations (26)-(32) below: (26) (27) (28) (29) (30) (31) (32) In the formula: These are the distribution network branches at that time. The active and reactive power flowing upstream; These represent the normal active and reactive loads at the nodes; the remaining variables and parameters are similar to the constraints of the access lines, so they will not be described in detail here.

[0039] In addition, each distribution network node substation must meet the capacity limit constraint: (33) In the formula: This represents the original upper limit of the substation's capacity. Indicates its power factor angle Step Six: Based on the objective function of the distribution network planning, the constraints of power generation, the constraints of energy storage configuration and operation, the constraints of photovoltaic, energy storage and charging access to the distribution network, and the constraints of distribution network operation, establish a distribution network extension planning model that considers the coordinated and optimized access of photovoltaic, energy storage and charging. Solve the model in MATLAB using the Gurobi and CPLEX solvers to obtain the distribution network extension planning scheme.

[0040] In summary, a distribution network expansion planning model considering the coordinated optimization of photovoltaic, energy storage and charging access was established in equation (34). It is a mixed integer linear programming (MINP) problem, which can be solved by calling commercial solvers such as Gurobi and CPLEX in MATLAB.

[0041] (34) Example 2 This embodiment analyzes a 56-node high-voltage power distribution system in a city in Northwest China. The power distribution network configuration is as follows: Figure 2 As shown. Due to the confidentiality of real urban power grid data, four modified IEEE-14 distribution networks simulate distribution networks representing the 110kV power supply areas in the north, south, east, and west of the city. These distribution networks operate relatively independently and are connected by a 330kV transmission network, and are not considered within the scope of this invention. The networks used are intended to simulate real urban areas.

[0042] In the aforementioned distribution network system, the distribution network planning model for coordinated access of photovoltaic, energy storage, and charging, built according to steps one through five, and the nearest access model (three stations accessing the nearest distribution network node) were simulated and run to compare the differences between the two planning schemes. To meet the charging load demand of EVs, 100MW of distributed power sources were invested in both the coordinated optimization access model and the nearest access model; therefore, their investment costs were not included in the expansion cost comparison. Investment and expansion costs were calculated based on their equivalent annual values, with a lifespan of 20 years and a discount rate of 0.08. The calculation results are shown in Table 1 and... Figure 3 As shown.

[0043] Table 1. Cost Comparison of the Two Options

[0044] Combination Figure 3 It can be seen that in the local access scheme, the access locations of distributed photovoltaic, energy storage and charging stations are fixed, lacking flexibility. This scheme makes it difficult to reasonably distribute the charging load in the distribution network, which in turn causes local node overload. It is necessary to expand the substations at multiple charging station access points, making the substation expansion cost as high as 12.222 million yuan. In addition, it is necessary to expand the distribution network lines, resulting in a high total expansion cost.

[0045] Compared to the nearest-access scheme, the photovoltaic-storage-charging collaborative access model proposed in this invention optimizes the access locations of the three components, allocating some charging load to upstream nodes with higher load margins, and enhancing load support capacity through ESS and DPV collaboration. Although this scheme increases investment in access lines, it effectively alleviates local overload problems, significantly reduces substation expansion investment to 5.378 million yuan, and eliminates the need for new distribution network lines, improving the economic efficiency of the planned scheme by 17.4%. Furthermore, because more ESSs can be configured under collaborative access, the utilization rate of gas turbine units is improved, thereby reducing electricity purchase costs and improving the economic efficiency of distribution network operation.

[0046] Comparison of the location of photovoltaic, energy storage and charging collaborative optimization access to the distribution network and the location of nearest access to the distribution network, for example Figure 4 As shown, the charging station has been optimized from initially connecting to downstream nodes with insufficient load capacity to upstream nodes with sufficient capacity, thereby ensuring the safe operation of the distribution network and improving the economic efficiency of the plan. At the same time, distributed photovoltaic and energy storage have changed from fixed access to flexible selection of access nodes, achieving the optimal trade-off between access cost and load support capacity, thereby reducing the operating cost of the distribution network.

[0047] The photovoltaic-storage-charging collaborative optimization access model changes the access location of distributed photovoltaic, energy storage and charging stations to achieve spatial matching of photovoltaic and charging, which increases access costs, but reduces substation expansion and distribution network line construction, thus reducing the total expansion cost; and reduces distribution network operation costs by reasonably configuring energy storage.

[0048] Example 3 like Figure 5 As shown, the distribution network expansion planning system considering the coordinated and optimized access of photovoltaic, energy storage, and charging provided by the present invention includes: Objective function construction unit: Constructs the objective function for distribution network planning, considering investment costs and operating costs; where investment costs include distributed generation costs, energy storage construction costs, substation expansion costs, distribution network line expansion costs, and access line construction costs, and all investment costs are calculated on an equal annual basis; operating costs include the cost of purchasing electricity from the upper-level grid, the generation costs of distributed generation sources, and the cost of purchasing and curtailing electricity from renewable energy sources. First constraint unit: Consider the constraints of power generation sources, including distributed power sources and power purchased from the upper-level grid. The power purchased from the upper-level grid is used as the output of each substation and is regarded as a distributed power source. At the same time, the upper and lower limits of active and reactive power are considered, and the power output can only be effective when the state variable of the construction is 1. Distributed photovoltaics also satisfy the requirement that the sum of actual output and abandoned power is the actual usable power. The second constraint unit considers energy storage configuration and operation constraints, including power constraints and energy constraints. The charging and discharging power meets the power constraint limit, and the energy stored in the battery meets the energy constraint limit. The third constraint unit considers the constraints of photovoltaic, energy storage, and charging network access to the distribution network; through the state variables of the access line construction. The locations for distributed photovoltaic power stations, energy storage power stations, and electric vehicle charging stations to connect to the distribution network are determined, while the connection lines must meet power flow constraints. A linear Dist-flow model is used for modeling, and the Big M method and other methods are employed. Determine whether a current flow constraint needs to be added; Fourth constraint unit: Considering distribution network operation constraints; distribution network branches satisfy upper and lower limits of transmission power and power flow constraints, using state variables. Determine the necessary expansion lines for the distribution network, and ensure that the node voltage meets the upper and lower voltage limits. Also, ensure that each node in the distribution network maintains a balance between active and reactive power. Distribution network expansion planning model establishment and solution unit: Based on the objective function of distribution network planning, power generation constraints, energy storage configuration and operation constraints, constraints of photovoltaic, energy storage and charging access to the distribution network, and distribution network operation constraints, a distribution network expansion planning model considering the coordinated and optimized access of photovoltaic, energy storage and charging is established. The model is solved by calling the Gurobi and CPLEX solvers in MATLAB to obtain the distribution network expansion planning scheme.

[0049] In the objective function construction unit of this embodiment, the objective function is as shown in equations (1)-(4): (1) (2) (3) (4) In the formula: For total cost, The respective y Annual investment and operating costs of power distribution network facilities; These are the investment costs for distributed power generation and the construction costs for energy storage, respectively. These are the costs of substation expansion and distribution network line expansion, respectively. Cost of access lines for electric vehicle charging stations, distributed photovoltaic and energy storage power stations; Indicates the construction status of the corresponding equipment; This represents the unit investment cost of the corresponding equipment, of which These are the construction costs per unit power and per unit capacity of energy storage power stations, respectively. To maximize the output of distributed power sources, Divided into energy storage power stations up to the [number] y The total power and electricity capacity invested and constructed in the year For the addition of transformer capacity to the substation; All represent distribution network node numbers. This indicates the node number of a distributed photovoltaic power station, an electric vehicle charging station, and an energy storage power station. To extend the length of the distribution network lines, The length of the access line to be constructed; This is the power curve for a distributed power source. The distributed power source is providing power at that moment. and These represent the actual available power and the amount of abandoned power of distributed photovoltaic power at that moment, respectively. and These are the cost coefficients for photovoltaic power purchase and curtailment, respectively. Typical daily weighting; These correspond to the year, typical day, and hour, respectively.

[0050] In the first constraint unit of this embodiment, the power output of the distributed power source satisfies the following constraints (5)-(6): (5) (6) In the formula: The lower bound of active power output of distributed power sources This indicates the upper limit of reactive power output, meaning that both the active and reactive power outputs of the distributed power source are within the limits. Distributed photovoltaic systems satisfy the following constraints (7)-(9): (7) (8) (9) In the formula: This represents the actual available power of distributed photovoltaic power at that moment. To contribute practically and effectively "Power output without reactive power" means that the output of distributed photovoltaic power is all within the boundary.

[0051] In the second constraint unit of this embodiment, the charging and discharging power meets the power constraint limit, and the amount of electricity stored in the battery meets the electricity constraint limit, as shown in the following equations (10)-(15): (10) (11) (12) (13) (14) (15) In the formula: Energy storage power stations ess The active and reactive power of charging and discharging. The amount of electricity stored at that moment; This indicates the minimum percentage of energy the battery needs to store. These represent the battery's charge and discharge efficiencies, respectively.

[0052] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0053] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that can be understood by those skilled in the art. The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A distribution network expansion planning method considering the coordinated and optimized access of photovoltaic, energy storage, and charging infrastructure, characterized in that: Includes the following steps: Step 1: Construct the objective function for distribution network planning, considering investment costs and operating costs; where investment costs include distributed generation costs, energy storage construction costs, substation expansion costs, distribution network line expansion costs, and access line construction costs, and all investment costs are calculated on an equal annual basis; operating costs include the cost of electricity purchased from the upper-level grid, the generation costs of distributed generation sources, and the cost of electricity purchased and curtailed from renewable energy sources. Step 2: Consider the constraints of power generation sources, including distributed generation and power purchased from the upper-level grid. The power purchased from the upper-level grid is used as the output of each substation and is regarded as a distributed generation source. At the same time, the upper and lower limits of active and reactive power are considered, and the power output can only be effective when the state variable of the construction is 1. Distributed photovoltaics also satisfy the requirement that the sum of actual output and abandoned power is the actual usable power. Step 3: Consider energy storage configuration and operation constraints, including power constraints and energy constraints. The charging and discharging power must meet the power constraint limit, and the energy stored in the battery must meet the energy constraint limit. Step 4: Consider the constraints of photovoltaic, energy storage, and charging network access to the distribution network; through the deployment and construction status variables of the access lines. The locations for distributed photovoltaic power stations, energy storage power stations, and electric vehicle charging stations to connect to the distribution network are determined, while the connection lines must meet power flow constraints. A linear Dist-flow model is used for modeling, and the Big M method and other methods are employed. Determine whether a current flow constraint needs to be added; Step 5: Consider distribution network operation constraints; distribution network branches must satisfy upper and lower limits of transmission power and power flow constraints, using state variables. Determine the necessary expansion lines for the distribution network, and ensure that the node voltage meets the upper and lower voltage limits. Also, ensure that each node in the distribution network maintains a balance between active and reactive power. Step Six: Based on the objective function of the distribution network planning, the constraints of power generation, the constraints of energy storage configuration and operation, the constraints of photovoltaic, energy storage and charging access to the distribution network, and the constraints of distribution network operation, establish a distribution network extension planning model that considers the coordinated and optimized access of photovoltaic, energy storage and charging. Solve the model in MATLAB using the Gurobi and CPLEX solvers to obtain the distribution network extension planning scheme.

2. The distribution network expansion planning method considering the coordinated and optimized access of photovoltaic, energy storage, and charging networks according to claim 1, characterized in that, In step one, the objective function is as shown in equations (1)-(4): (1) (2) (3) (4) In the formula: For total cost, The respective y Annual investment and operating costs of power distribution network facilities; These are the investment costs for distributed power generation and the construction costs for energy storage, respectively. These are the costs of substation expansion and distribution network line expansion, respectively. Cost of access lines for electric vehicle charging stations, distributed photovoltaic and energy storage power stations; Indicates the construction status of the corresponding equipment; This represents the unit investment cost of the corresponding equipment, of which These are the construction costs per unit power and per unit capacity of energy storage power stations, respectively. To maximize the output of distributed power sources, Divided into energy storage power stations up to the [number] y The total power and electricity capacity invested and constructed in the year For the addition of transformer capacity to the substation; All represent distribution network node numbers. This indicates the node number of a distributed photovoltaic power station, an electric vehicle charging station, and an energy storage power station. To extend the length of the distribution network lines, The length of the access line to be constructed; This is the power curve for a distributed power source. The distributed power source is providing power at that moment. and These represent the actual available power and the amount of abandoned power of distributed photovoltaic power at that moment, respectively. and These are the cost coefficients for photovoltaic power purchase and curtailment, respectively. Typical daily weighting; These correspond to the year, typical day, and hour, respectively.

3. The distribution network expansion planning method considering the coordinated and optimized access of photovoltaic, energy storage, and charging networks according to claim 2, characterized in that, In step two, the power output of the distributed power source satisfies the following constraints (5)-(6): (5) (6) In the formula: The lower bound of active power output of distributed power sources This indicates the upper limit of reactive power output, meaning that both the active and reactive power outputs of the distributed power source are within the limits. Distributed photovoltaic systems satisfy the following constraints (7)-(9): (7) (8) (9) In the formula: This represents the actual available power of distributed photovoltaic power at that moment. To contribute practically and effectively "Power output without reactive power" means that the output of distributed photovoltaic power is all within the boundary.

4. The distribution network expansion planning method considering the coordinated and optimized access of photovoltaic, energy storage, and charging networks according to claim 3, characterized in that, In step three, the charging and discharging power meets the power constraint, and the amount of electricity stored in the battery meets the energy constraint, as shown in equations (10)-(15) below: (10) (11) (12) (13) (14) (15) In the formula: Energy storage power stations ess The active and reactive power of charging and discharging. The amount of electricity stored at that moment; This indicates the minimum percentage of energy the battery needs to store. These represent the battery's charge and discharge efficiencies, respectively.

5. The distribution network expansion planning method considering the coordinated and optimized access of photovoltaic, energy storage, and charging systems according to claim 4, characterized in that, In step four, the deployment status variables of the access line are used. The locations for distributed photovoltaic power stations, energy storage power stations, and electric vehicle charging stations to connect to the distribution network are determined, while the connection lines must meet power flow constraints. A linear Dist-flow model is used for modeling, and the Big M method and other methods are employed. Determine whether power flow constraints need to be added, as shown in equations (16)-(17): (16) (17) In the formula: This indicates the node voltage at each station. Indicates the voltage at the distribution network node; Each station on the access line at that time The active and reactive power output; For transformer turns ratio, For the resistance and reactance of the connection line, For the voltage level of the access line, M For sufficiently large positive numbers; The node power of each station must be kept balanced, and the node voltage and transmission line capacity must meet the upper and lower limits, as shown in equations (18)-(22) below: (18) (19) (20) (21) (22) In the formula: It represents the active and reactive power output of distributed photovoltaic power stations, electric vehicle charging stations, and energy storage power stations; For charging stations m Voltage upper and lower limits; These are the maximum active and reactive power transmitted by the line, respectively. The output of each station to each node of the distribution network is expressed by the following formulas (23)-(25): (23) (24) (25) in These represent the node numbers of distributed photovoltaic power stations, electric vehicle charging stations, and energy storage power stations, respectively. These respectively represent the distributed photovoltaic, energy storage power station, and electric vehicle charging station injected into the distribution network node at that moment. The active power.

6. The distribution network expansion planning method considering the coordinated and optimized access of photovoltaic, energy storage, and charging networks according to claim 5, characterized in that, In step five, the distribution network branches satisfy the upper and lower limits of transmission power and power flow constraints, using state variables. Determine the required expansion lines for the distribution network, and ensure that the node voltage meets the upper and lower voltage limits. The active and reactive power of each node in the distribution network must be balanced, as shown in equations (26)-(32) below: (26) (27) (28) (29) (30) (31) (32) In the formula: These are the distribution network branches at that time. The active and reactive power flowing upstream; These represent the normal active and reactive loads on the nodes; the remaining variables and parameters are similar to the constraints of the access lines. In addition, each distribution network node substation must meet the capacity limit constraint: (33) In the formula: This represents the original upper limit of the substation's capacity. This indicates its power factor angle.

7. A distribution network expansion planning system considering the coordinated and optimized access of photovoltaic, energy storage, and charging infrastructure, characterized in that: include: Objective function construction unit: Constructs the objective function for distribution network planning, considering investment costs and operating costs; where investment costs include distributed generation costs, energy storage construction costs, substation expansion costs, distribution network line expansion costs, and access line construction costs, and all investment costs are calculated on an equal annual basis; operating costs include the cost of purchasing electricity from the upper-level grid, the generation costs of distributed generation sources, and the cost of purchasing and curtailing electricity from renewable energy sources. First constraint unit: Consider the constraints of power generation sources, including distributed power sources and power purchased from the upper-level grid. The power purchased from the upper-level grid is used as the output of each substation and is regarded as a distributed power source. At the same time, the upper and lower limits of active and reactive power are considered, and the power output can only be effective when the state variable of the construction is 1. Distributed photovoltaics also satisfy the requirement that the sum of actual output and abandoned power is the actual usable power. The second constraint unit considers energy storage configuration and operation constraints, including power constraints and energy constraints. The charging and discharging power meets the power constraint limit, and the energy stored in the battery meets the energy constraint limit. The third constraint unit considers the constraints of photovoltaic, energy storage, and charging network access to the distribution network; through the state variables of the access line construction. The locations for distributed photovoltaic power stations, energy storage power stations, and electric vehicle charging stations to connect to the distribution network are determined, while the connection lines must meet power flow constraints. A linear Dist-flow model is used for modeling, and the Big M method and other methods are employed. Determine whether a current flow constraint needs to be added; Fourth constraint unit: Considering distribution network operation constraints; distribution network branches satisfy upper and lower limits of transmission power and power flow constraints, using state variables. Determine the necessary expansion lines for the distribution network, and ensure that the node voltage meets the upper and lower voltage limits. Also, ensure that each node in the distribution network maintains a balance between active and reactive power. Distribution network expansion planning model establishment and solution unit: Based on the objective function of distribution network planning, power generation constraints, energy storage configuration and operation constraints, constraints of photovoltaic, energy storage and charging access to the distribution network, and distribution network operation constraints, a distribution network expansion planning model considering the coordinated and optimized access of photovoltaic, energy storage and charging is established. The model is solved by calling the Gurobi and CPLEX solvers in MATLAB to obtain the distribution network expansion planning scheme.

8. The distribution network expansion planning system considering the coordinated and optimized access of photovoltaic, energy storage, and charging as described in claim 7, is characterized in that, In the objective function construction unit, the objective function is as shown in equations (1)-(4): (1) (2) (3) (4) In the formula: For total cost, The respective y Annual investment and operating costs of power distribution network facilities; These are the investment costs for distributed power generation and the construction costs for energy storage, respectively. These are the costs of substation expansion and distribution network line expansion, respectively. Cost of access lines for electric vehicle charging stations, distributed photovoltaic and energy storage power stations; Indicates the construction status of the corresponding equipment; This represents the unit investment cost of the corresponding equipment, of which These are the construction costs per unit power and per unit capacity of energy storage power stations, respectively. To maximize the output of distributed power sources, Divided into energy storage power stations up to the [number] y The total power and electricity capacity invested and constructed in the year For the addition of transformer capacity to the substation; All represent distribution network node numbers. This indicates the node number of a distributed photovoltaic power station, an electric vehicle charging station, and an energy storage power station. To extend the length of the distribution network lines, The length of the access line to be constructed; This is the power curve for a distributed power source. The distributed power source is providing power at that moment. and These represent the actual available power and the amount of abandoned power of distributed photovoltaic power at that moment, respectively. and These are the cost coefficients for photovoltaic power purchase and curtailment, respectively. Typical daily weighting; These correspond to the year, typical day, and hour, respectively.

9. The distribution network expansion planning system considering the coordinated and optimized access of photovoltaic, energy storage, and charging as described in claim 8, is characterized in that, In the first constraint unit, the power output of the distributed power source satisfies the following constraints (5)-(6): (5) (6) In the formula: The lower bound of active power output of distributed power sources This indicates the upper limit of reactive power output, meaning that both the active and reactive power outputs of the distributed power source are within the limits. Distributed photovoltaic systems satisfy the following constraints (7)-(9): (7) (8) (9) In the formula: This represents the actual available power of distributed photovoltaic power at that moment. To contribute practically and effectively "Power output without reactive power" means that the output of distributed photovoltaic power is all within the boundary.

10. The distribution network expansion planning system considering the coordinated and optimized access of photovoltaic, energy storage, and charging as described in claim 9, is characterized in that, In the second constraint unit, the charging and discharging power meets the power constraint limit, and the energy stored in the battery meets the energy constraint limit, as shown in equations (10)-(15) below: (10) (11) (12) (13) (14) (15) In the formula: Energy storage power stations ess The active and reactive power of charging and discharging. The amount of electricity stored at that moment; This indicates the minimum percentage of energy the battery needs to store. These represent the battery's charge and discharge efficiencies, respectively.

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