A power distribution network coordination optimization method and device based on source network load storage

Abstract

The application discloses a power distribution network coordination optimization method and device based on source network load storage. According to the pre-defined minimum value optimization problem, the application constructs a power distribution network reconstruction optimization problem, applies the power distribution network reconstruction optimization problem to reconstruct the power distribution network, obtains a line switching state, establishes a power distribution network equivalent model in combination with the operating parameters of the elements in the power distribution network and the line switching state, constructs an objective function based on the power distribution network equivalent model and taking the minimization of the operating cost of the power distribution network as a target, constructs a constraint condition, establishes a source network load storage coordination optimization linear model, solves the source network load storage coordination optimization linear model, obtains an optimal power distribution network planning strategy, and controls the operating state of the elements in the power distribution network according to the optimal power distribution network planning strategy, so that the establishment of the source network load storage coordination optimization linear model for the power distribution network coordination optimization is realized, and the operating state of the distributed power supply and other elements in the power distribution network is controlled according to the actual optimal power distribution network planning strategy.

Description

Technical Field

[0001] This invention relates to the field of distribution network operation control technology, and in particular to a method and apparatus for coordinated optimization of distribution networks based on source, grid, load and storage. Background Technology

[0002] Against the backdrop of the gradual depletion of traditional fossil fuels and their severe pollution, distributed generation (DG) has received significant attention due to its clean and renewable characteristics. However, while DG integration into the distribution network brings opportunities, it also presents numerous challenges, including absorption issues caused by supply-demand imbalances and safety concerns arising from sudden grid disconnection. Active distribution networks enable proactive control of DG, leveraging source-grid-load-storage coordination and optimization technologies to fully utilize the regulatory functions of various controllable resources. This can improve the economic efficiency, safety, and reliability of the power system, as well as increase the penetration rate of DG.

[0003] Traditional source-grid-load-storage coordination optimization models are mostly nonlinear models, which are difficult to converge and prone to getting trapped in local optima for source-grid coordination. Therefore, it is necessary to establish a linear source-grid-load-storage coordination optimization model for distribution network coordination optimization, so as to ensure that the distribution network controls the operation status of distributed power sources according to the actual optimal distribution network planning strategy. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies, this invention provides a distribution network coordination optimization method and apparatus based on source-grid-load-storage, which can establish a linear model for source-grid-load-storage coordination optimization to optimize the distribution network and ensure that the distribution network controls the operating status of distributed power sources and other components in the distribution network according to the actual optimal distribution network planning strategy.

[0005] To address the aforementioned technical problems, in a first aspect, an embodiment of the present invention provides a distribution network coordination optimization method based on source-grid-load-storage, comprising:

[0006] Based on a predefined minimum value optimization problem, a distribution network reconfiguration optimization problem is constructed. The distribution network is then reconfigured using the aforementioned distribution network reconfiguration optimization problem to obtain the line switching status.

[0007] The operating parameters of the components in the distribution network are obtained as component operating parameters. Based on the component operating parameters and the line switching status, an equivalent model of the distribution network is established.

[0008] Based on the equivalent model of the distribution network, an objective function is constructed with the goal of minimizing the operating cost of the distribution network, constraints are constructed, and a linear model for coordinated optimization of source, grid, load and storage is established.

[0009] Solve the source-grid-load-storage coordinated optimization linear model to obtain the optimal distribution network planning strategy, so that the distribution network controls the operating status of the components in the distribution network according to the optimal distribution network planning strategy.

[0010] Furthermore, the construction of the distribution network reconfiguration optimization problem based on the predefined minimum value optimization problem specifically includes:

[0011] Select the objective term corresponding to the linear switching number calculation algorithm from the minimum value optimization problem, and construct the distribution network reconfiguration optimization problem based on the objective term; wherein, the minimum value optimization problem is obtained by defining the sum of the absolute values ​​of any random free variables as the minimum.

[0012] Furthermore, the step of obtaining the operating parameters of the components in the distribution network as component operating parameters specifically involves:

[0013] Based on the load equivalent model and the power source equivalent method, equivalent calculations of the injected current source of the active load and the energy storage system in the distribution network are performed respectively to obtain the operating parameters of the active load and the energy storage system.

[0014] Furthermore, the objective function is:

[0015] Costobj=min{Cofepr+Cofswi+Cofrl};

[0016] Cofepr, Cofswi, and Cofrl represent the electricity purchase cost, switching operation cost, and active load subsidy cost, respectively.

[0017] Furthermore, the constraints include at least one of the following: line switch operation constraints, active load element constraints, distribution network power flow constraints, distribution network radiation constraints, node voltage constraints, and branch current constraints.

[0018] Secondly, an embodiment of the present invention provides a distribution network coordination optimization device based on source-grid-load-storage, comprising:

[0019] The distribution network reconfiguration module is used to construct a distribution network reconfiguration optimization problem based on a predefined minimum value optimization problem, and apply the distribution network reconfiguration optimization problem to reconfigure the distribution network to obtain the line switching status.

[0020] The distribution network equivalent model establishment module is used to obtain the operating parameters of the components in the distribution network as component operating parameters, and to establish the distribution network equivalent model by combining the component operating parameters and the line switching status.

[0021] The source-grid-load-storage coordinated optimization linear model establishment module is used to construct an objective function and construct constraints based on the equivalent model of the distribution network, with the goal of minimizing the operating cost of the distribution network, and to establish a source-grid-load-storage coordinated optimization linear model.

[0022] The distribution network coordination and optimization module is used to solve the linear model of source-grid-load-storage coordination and optimization to obtain the optimal distribution network planning strategy, so that the distribution network controls the operating status of the components in the distribution network according to the optimal distribution network planning strategy.

[0023] Furthermore, the distribution network reconfiguration module is specifically used to: select an objective term corresponding to the linear switching number calculation algorithm from the minimum value optimization problem, and construct the distribution network reconfiguration optimization problem based on the objective term; wherein, the minimum value optimization problem is obtained by defining the sum of the absolute values ​​of any random free variables as the minimum.

[0024] Furthermore, the distribution network equivalent model establishment module is specifically used to perform equivalent calculations of the active load and the injected current source of the energy storage system in the distribution network based on the load equivalent model and the power source equivalent method, so as to obtain the operating parameters of the active load and the energy storage system.

[0025] Furthermore, the objective function is:

[0026] Costobj=min{Cofepr+Cofswi+Cofrl};

[0027] Cofepr, Cofswi, and Cofrl represent the electricity purchase cost, switching operation cost, and active load subsidy cost, respectively.

[0028] Furthermore, the constraints include at least one of the following: line switch operation constraints, active load element constraints, distribution network power flow constraints, distribution network radiation constraints, node voltage constraints, and branch current constraints.

[0029] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0030] By constructing a distribution network reconfiguration optimization problem based on a predefined minimum value optimization problem, and applying this problem to reconfigure the distribution network to obtain line switching states, an equivalent model of the distribution network is established by combining the operating parameters of the components in the distribution network and the line switching states. Based on this equivalent model, an objective function is constructed with the goal of minimizing the operating cost of the distribution network, constraints are established, and a linear model for source-grid-load-storage coordination optimization is established. By solving this linear model, the optimal distribution network planning strategy is obtained, enabling the distribution network to control the operating states of its components according to this strategy. This achieves the goal of establishing a linear model for source-grid-load-storage coordination optimization to optimize the distribution network, ensuring that the distribution network controls the operating states of distributed power sources and other components according to the actual optimal distribution network planning strategy. Attached Figure Description

[0031] Figure 1 This is a flowchart illustrating the distribution network coordination optimization method based on source-grid-load-storage in the first embodiment of the present invention.

[0032] Figure 2 This is a schematic diagram of the distribution network coordination and optimization device based on source-grid-load-storage in the second embodiment of the present invention. Detailed Implementation

[0033] The technical solutions of this invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0034] It should be noted that the step numbers in this document are only for the convenience of explaining the specific embodiments and are not intended to limit the order in which the steps are executed. The method provided in this embodiment can be executed by relevant terminal devices, and the following description uses a processor as the execution subject.

[0035] like Figure 1 As shown, the first embodiment provides a distribution network coordination optimization method based on source-grid-load-storage, including steps S1 to S4:

[0036] S1. Based on the predefined minimum value optimization problem, construct the distribution network reconfiguration optimization problem, apply the distribution network reconfiguration optimization problem to reconfigure the distribution network, and obtain the line switching status.

[0037] S2. Obtain the operating parameters of the components in the distribution network as component operating parameters, and establish an equivalent model of the distribution network by combining the component operating parameters and line switching status.

[0038] S3. Based on the equivalent model of the distribution network, construct the objective function and constraints with the goal of minimizing the operating cost of the distribution network, and establish a linear model for coordinated optimization of source, grid, load and storage.

[0039] S4. Solve the linear model of source-grid-load-storage coordination optimization to obtain the optimal distribution network planning strategy, so that the distribution network can control the operating status of the components in the distribution network according to the optimal distribution network planning strategy.

[0040] As an example, in step S1, an absolute value linear programming method is applied to the distribution network reconfiguration. A minimum value optimization problem is predefined, which minimizes the sum of the absolute values ​​of any random free variables. Based on the minimum value optimization problem, a distribution network reconfiguration optimization problem is constructed. The distribution network is reconfigured using the distribution network reconfiguration optimization problem to obtain the line switching state.

[0041] In step S2, the injection current and other operating parameters of active loads and energy storage systems in the distribution network are obtained as component operating parameters. Combined with the component operating parameters and line switching status, an equivalent model of the distribution network is established.

[0042] In step S3, based on the equivalent model of the distribution network, an objective function is constructed with the goal of minimizing the operating cost of the distribution network. Constraints are constructed by considering constraints such as line switch operation constraints, active load element constraints, distribution network power flow constraints, distribution network radiation constraints, node voltage constraints, and branch current constraints, and a linear model for source-grid-load-storage coordinated optimization is established.

[0043] In step S4, the linear model for source-grid-load-storage coordination optimization is solved to obtain the optimal distribution network planning strategy, so that the distribution network can control the operating status of active loads, energy storage systems, distributed power sources and other components in the distribution network according to the optimal distribution network planning strategy.

[0044] This embodiment can establish a linear model for coordinated optimization of power generation, grid, load and storage to optimize the distribution network and ensure that the distribution network controls the operating status of distributed power sources and other components in the distribution network according to the actual optimal distribution network planning strategy.

[0045] In a preferred embodiment, the step of constructing a distribution network reconfiguration optimization problem based on a predefined minimum value optimization problem specifically involves: selecting an objective term from the minimum value optimization problem that corresponds to the linear switching number calculation algorithm, and constructing a distribution network reconfiguration optimization problem based on the objective term; wherein, the minimum value optimization problem is defined as minimizing the sum of the absolute values ​​of any random free variables.

[0046] As an example, an absolute value linear programming method is applied to distribution network reconfiguration. By transforming two binary variables, the absolute value term is converted into a linear term, and the applicable scenarios can be extended and expanded. The specific process is as follows:

[0047] Define a minimum optimization problem that minimizes the sum of the absolute values ​​of any random free variables. To simplify the problem description, select the objective term from the minimum optimization problem that corresponds to the Prolongable Linear Switching Operations Calculation (PLSOC) algorithm. Other terms and other linear constraints in the minimum optimization problem are temporarily ignored. The goal is to construct a distribution network reconfiguration optimization problem such that the sum of the first constant multiple and the second constant multiple of the absolute value of any random free variable is less than the sum of its third constant.

[0048] After constructing the distribution network reconfiguration optimization problem, the constructed distribution network reconfiguration optimization problem is applied to the distribution network reconfiguration to reconfigure the distribution network and obtain the line switching state represented by binary variables.

[0049] In this process, for each random free variable, after determining whether the random free variable is positive or negative, a similar minimum value optimization problem is established, thereby eliminating absolute values, reducing the difficulty of solving the problem, and improving the solvability of the linear model for source-grid-load-storage coordinated optimization.

[0050] There are eight ways to represent the line switching state using binary variables. Lijpos equals 1 and Lijneg equals 0 only when the original line ij is disconnected and then reconnected and closed. Conversely, Lijneg equals 1 and Lijpos equals 0 only when the original line ij is closed and then reconnected and disconnected. When no line switching occurs, both are 0. In the distribution network reconfiguration model, Lijpos represents the newly closed line, and Lijneg represents the newly disconnected line.

[0051] In a preferred embodiment, obtaining the operating parameters of components in the distribution network as component operating parameters specifically involves: performing equivalent calculations of the active load and the injected current source of the energy storage system in the distribution network based on the load equivalent model and the power supply equivalent method, respectively, to obtain the operating parameters of the active load and the energy storage system.

[0052] As an example, the active load RL can be regarded as the superposition of the node's inherent load and the local small controllable power source. RL is regarded as another current source. The equivalent model of the injected current source is obtained by using a similar processing method to distributed power sources. The model includes the real part and imaginary part of the equivalent injected current source of the i-th active load node at time t, the active and reactive power of the i-th active load node in response at time t, and the substation voltage.

[0053] Among them, RL is constrained by the maximum response value, which is usually taken as a certain proportion of the inherent load demand of the node, that is, the maximum response value. The reactive response value and the active response value of RL maintain a certain functional relationship, that is, the active response value of RL is between [0, the product of the reactive response value of RL and the response coefficient of RL], and the response coefficient of RL takes a value in the range of [0, 1]. The effective value of the active response value of RL is the product between the active response value of RL and the tangent of the power factor of RL. The power factor of RL takes a fixed value. RL is regarded as a controllable current source. For traditional non-response loads, according to Norton's theorem, the load equivalent model is still used to transform it into admittance and current source in parallel.

[0054] In a preferred embodiment, the objective function is:

[0055] Costobj=min{Cofepr+Cofswi+Cofrl} (1);

[0056] Cofepr, Cofswi, and Cofrl represent the electricity purchase cost, switching operation cost, and active load subsidy cost, respectively.

[0057] As an example, the operating cost of a distribution network includes three parts: the cost of purchasing electricity from the upper-level power supply, the cost of reconfiguration switch switching operations, and the cost of active load subsidies. The corresponding objective function is:

[0058] Costobj=Cofepr+Cofswi+Cofrl (1);

[0059] In equation (1), Cofepr, Cofswi and Cofrl represent the cost of electricity purchase, the cost of switching action and the cost of active load subsidy, respectively, with units of $ / MW, $ / time and $ / MW.

[0060] The objective function takes grid operation into account, but does not include the investment costs of distributed generation (DG) and energy storage system (BES) components. The cost of electricity changes caused by BES charging and discharging is effectively reflected in the electricity purchase cost. The degradation cost of BES throughout its entire life cycle is not considered, and the electricity purchased by the distribution network from the upper main grid is regarded as consistent with the active power output of traditional generator power.

[0061] In a preferred embodiment, the constraints include at least one of line switch operation constraints, active load element constraints, distribution network power flow constraints, distribution network radiation constraints, node voltage constraints, and branch current constraints.

[0062] As an example, when establishing a linear model for source-grid-load-storage coordinated optimization, constraints are constructed by considering line switch action constraints, active load element constraints, distribution network power flow constraints, distribution network radiation constraints, node voltage constraints, and branch current constraints.

[0063] Among them, the circuit breaker action constraint is a time period, such as a day, the number of circuit breaker actions is limited to [minimum number of circuit breaker actions, maximum number of circuit breaker actions].

[0064] Active load element constraints limit the load capacity of active load elements to within [minimum load capacity, maximum load capacity].

[0065] Distribution network power flow constraints are constraints on the power flow equations. According to I = YV, the power flow equations are determined as follows: The real part of the equivalent injected current source is the sum of the real parts of the equivalent injected current source of the distributed generation, the traditional generator power source, and the load equivalent current source at the i-th node at time t; the imaginary part of the equivalent injected current source is the sum of the imaginary parts of the equivalent injected current source of the distributed generation, the traditional generator power source, and the load equivalent current source at the i-th node at time t. The power flow equations are expressed as:

[0066]

[0067]

[0068] In equations (2) to (3), B ij,t This represents the susceptance value of line ij in the admittance matrix; and Let represent the real and imaginary parts of the total injected current at node i at time t.

[0069] When considering that the load equivalent increases the node admittance and injected current source, the power supply equivalent increases the node injected current source, and that distribution network reconfiguration may change the network structure, the power flow equation is expressed as:

[0070]

[0071]

[0072]

[0073]

[0074] For the complex numbers of node voltages, branch currents, and branch admittances in the distribution network, division is performed from the perspective of the real and imaginary parts. Through a series of approximation methods and equivalent transformations, the nonlinear power flow equations containing sine functions are transformed into linear power flow equations, thereby improving the linearization of the model and reducing the difficulty of solving the problem.

[0075] Distribution network radial constraints include constraints that maintain the radial shape of the reconfigured distribution network, expressed as:

[0076] τ ij +τ ji =μij (8);

[0077] ∑ j∈Ni τ ij =1, i>2 (9);

[0078] τ ij =0, j∈Ni (10);

[0079] τ ij ∈{0,1} (11);

[0080] In equations (8) to (11), τ ij and τ ji These are two different binary variables, when τ ij When τ equals 1, it means that node i is the parent node of node j. ji When μ equals 1, it means that node j is the parent node of node i. When the line is broken, that is, μ ij When μ equals 0, both variables are 0; when the circuit is closed, i.e., μ... ij When N equals 1, only one variable is equal to 1, and the other variable must be equal to 0, because there is only one mother node for the same line; N represents a node; the first node is at the beginning of the line and has no mother node; except for the first node, all other nodes must contain a mother node.

[0081] Node voltage constraints include upper and lower limits on the real part of the node voltage.

[0082] Branch current constraints are:

[0083]

[0084] In equation (12), This represents the square of the maximum power of the branch.

[0085] Understandably, the source-grid-load-storage coordinated optimization linear model is obtained through a series of linearization processes. Based on the objective function and constraints, it can be jointly simulated using Matlab and GAMS software to obtain the running results under multiple calculation scenarios. Data analysis and chart processing can then be performed on the objective function, purchased electricity, reconfiguration actions, active load response, and the operation of the energy storage system.

[0086] To more clearly illustrate the distribution network coordination optimization method based on source-grid-load-storage provided in the first embodiment, the specific operation process is as follows:

[0087] 1. A linear switching operations calculation algorithm (PLSOC) with good scalability is proposed to extend and expand the scope of application of PLSOC.

[0088] 2. Based on the load equivalent model and power supply equivalent method, perform equivalent calculations of the injected current source for active loads and energy storage systems;

[0089] 3. Establish a linear model for source-grid-load-storage coordination optimization with the objective function of minimizing the operating cost of the distribution network, satisfying the constraints of each component in the distribution network and the operational safety constraints of the distribution network;

[0090] 4. Predict the load and wind turbine output for 24 hours a day, and preprocess the prediction results, distribution network tie line status, node admittance matrix and time-of-use electricity price data, and export the results from MATLAB to GAMS software;

[0091] 5. Define various variables and build and modify mixed integer linear programming (MILP) optimization models in GAMS team building;

[0092] 6. Call the Cplex solver to solve the GAMS optimization model. If an error message is displayed, return to step 5 to make corrections. If no feasible solution is found, return to step 4 to check the relevant parameters. If no error occurs and a feasible solution is found, output the results.

[0093] 7. Import the results back into MATLAB software, calculate and analyze the relevant results, and further visualize the results using charts.

[0094] Based on the same inventive concept as the first embodiment, the second embodiment provides as follows: Figure 2 The device shown is a distribution network coordination optimization device based on source-grid-load-storage, comprising: a distribution network reconfiguration module 21, used to construct a distribution network reconfiguration optimization problem according to a predefined minimum value optimization problem, and apply the distribution network reconfiguration optimization problem to reconfigure the distribution network to obtain the line switching state; a distribution network equivalent model establishment module 22, used to obtain the operating parameters of the components in the distribution network as component operating parameters, and establish a distribution network equivalent model by combining the component operating parameters and the line switching state; a source-grid-load-storage coordination optimization linear model establishment module 23, used to construct an objective function and construct constraints based on the distribution network equivalent model, with the goal of minimizing the operating cost of the distribution network, and establish a source-grid-load-storage coordination optimization linear model; and a distribution network coordination optimization module 24, used to solve the source-grid-load-storage coordination optimization linear model to obtain the optimal distribution network planning strategy, so that the distribution network controls the operating state of the components in the distribution network according to the optimal distribution network planning strategy.

[0095] In a preferred embodiment, the distribution network reconfiguration module 21 is specifically used to: select the target item corresponding to the linear switching number calculation algorithm from the minimum value optimization problem, and construct the distribution network reconfiguration optimization problem based on the target item; wherein, the minimum value optimization problem is defined as the minimum sum of the absolute values ​​of any random free variables.

[0096] In a preferred embodiment, the distribution network equivalent model establishment module 22 is specifically used to perform equivalent calculations of the active load and the injected current source of the energy storage system in the distribution network based on the load equivalent model and the power supply equivalent method, so as to obtain the operating parameters of the active load and the energy storage system.

[0097] In a preferred embodiment, the objective function is:

[0098] Costobj=min{Cofepr+Cofswi+Cofrl};

[0099] Cofepr, Cofswi, and Cofrl represent the electricity purchase cost, switching operation cost, and active load subsidy cost, respectively.

[0100] In a preferred embodiment, the constraints include at least one of line switch operation constraints, active load element constraints, distribution network power flow constraints, distribution network radiation constraints, node voltage constraints, and branch current constraints.

[0101] In summary, implementing the embodiments of the present invention has the following beneficial effects:

[0102] By constructing a distribution network reconfiguration optimization problem based on a predefined minimum value optimization problem, and applying this problem to reconfigure the distribution network to obtain line switching states, an equivalent model of the distribution network is established by combining the operating parameters of the components in the distribution network and the line switching states. Based on this equivalent model, an objective function is constructed with the goal of minimizing the operating cost of the distribution network, constraints are established, and a linear model for source-grid-load-storage coordination optimization is established. By solving this linear model, the optimal distribution network planning strategy is obtained, enabling the distribution network to control the operating states of its components according to this strategy. This achieves the goal of establishing a linear model for source-grid-load-storage coordination optimization to optimize the distribution network, ensuring that the distribution network controls the operating states of distributed power sources and other components according to the actual optimal distribution network planning strategy.

[0103] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

[0104] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

Claims

1. A method for coordinated optimization of distribution networks based on source-grid-load-storage, characterized in that, include: Based on a predefined minimum value optimization problem, a distribution network reconfiguration optimization problem is constructed. The distribution network is then reconfigured using the aforementioned distribution network reconfiguration optimization problem to obtain the line switching status. The operating parameters of the components in the distribution network are obtained as component operating parameters. Based on the component operating parameters and the line switching status, an equivalent model of the distribution network is established. Based on the equivalent model of the distribution network, an objective function is constructed with the goal of minimizing the operating cost of the distribution network, constraints are constructed, and a linear model for coordinated optimization of source, grid, load and storage is established. Solve the source-grid-load-storage coordinated optimization linear model to obtain the optimal distribution network planning strategy, so that the distribution network controls the operating status of the components in the distribution network according to the optimal distribution network planning strategy; The process of constructing a distribution network reconfiguration optimization problem based on a predefined minimum value optimization problem is as follows: Selecting an objective term corresponding to the linear switching count calculation algorithm from the minimum value optimization problem, and constructing the distribution network reconfiguration optimization problem based on the objective term; wherein, the minimum value optimization problem is defined as minimizing the sum of the absolute values ​​of any random free variables; selecting an objective term corresponding to the linear switching count calculation algorithm from the minimum value optimization problem, and constructing the distribution network reconfiguration optimization problem based on the objective term includes: converting the absolute value term into a linear term through the conversion relationship of binary variables, so that the sum of the first constant multiple and the second constant multiple of the absolute value of any random free variable is less than the sum of its third constant, and constructing the distribution network reconfiguration optimization problem.

2. The distribution network coordination optimization method based on source-grid-load-storage as described in claim 1, characterized in that, The specific steps for obtaining the operating parameters of the components in the distribution network as component operating parameters are as follows: Based on the load equivalent model and the power source equivalent method, equivalent calculations of the injected current source of the active load and the energy storage system in the distribution network are performed respectively to obtain the operating parameters of the active load and the energy storage system.

3. The distribution network coordination optimization method based on source-grid-load-storage as described in claim 1, characterized in that, The objective function is: Costobj=min{Cofepr+Cofswi+Cofrl}; Cofepr, Cofswi, and Cofrl represent the electricity purchase cost, switching operation cost, and active load subsidy cost, respectively.

4. The distribution network coordination optimization method based on source-grid-load-storage as described in claim 1, characterized in that, The constraints include at least one of the following: line switch operation constraints, active load element constraints, distribution network power flow constraints, distribution network radiation constraints, node voltage constraints, and branch current constraints.

5. A distribution network coordination optimization device based on source-grid-load-storage, characterized in that, include: The distribution network reconfiguration module is used to construct a distribution network reconfiguration optimization problem based on a predefined minimum value optimization problem, and apply the distribution network reconfiguration optimization problem to reconfigure the distribution network to obtain the line switching status. The distribution network equivalent model establishment module is used to obtain the operating parameters of the components in the distribution network as component operating parameters, and to establish the distribution network equivalent model by combining the component operating parameters and the line switching status. The source-grid-load-storage coordinated optimization linear model establishment module is used to construct an objective function and construct constraints based on the equivalent model of the distribution network, with the goal of minimizing the operating cost of the distribution network, and to establish a source-grid-load-storage coordinated optimization linear model. The distribution network coordination and optimization module is used to solve the source-grid-load-storage coordination and optimization linear model to obtain the optimal distribution network planning strategy, so that the distribution network controls the operating status of the components in the distribution network according to the optimal distribution network planning strategy. The distribution network reconfiguration module is specifically used for: selecting an objective term corresponding to the linear switching number calculation algorithm from the minimum value optimization problem, and constructing the distribution network reconfiguration optimization problem based on the objective term; wherein, the minimum value optimization problem is obtained by defining the sum of the absolute values ​​of any random free variables as minimal; selecting an objective term corresponding to the linear switching number calculation algorithm from the minimum value optimization problem and constructing the distribution network reconfiguration optimization problem based on the objective term includes: converting the absolute value term into a linear term through the conversion relationship of binary variables, so that the sum of the first constant multiple and the second constant multiple of the absolute value of any random free variable is less than the sum of its third constant, and constructing the distribution network reconfiguration optimization problem.

6. The distribution network coordination optimization device based on source-grid-load-storage as described in claim 5, characterized in that, The distribution network equivalent model establishment module is specifically used to perform equivalent calculations of the injected current sources of the active load and the energy storage system in the distribution network based on the load equivalent model and the power source equivalent method, so as to obtain the operating parameters of the active load and the energy storage system.

7. The distribution network coordination optimization device based on source-grid-load-storage as described in claim 5, characterized in that, The objective function is: Costobj=min{Cofepr+Cofswi+Cofrl}; Cofepr, Cofswi, and Cofrl represent the electricity purchase cost, switching operation cost, and active load subsidy cost, respectively.

8. The distribution network coordination optimization device based on source-grid-load-storage as described in claim 5, characterized in that, The constraints include at least one of the following: line switch operation constraints, active load element constraints, distribution network power flow constraints, distribution network radiation constraints, node voltage constraints, and branch current constraints.

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