Coordinated optimization method for soft open points, photovoltaic and industrial loads in active power distribution network

Abstract

The application relates to a soft open point, photovoltaic and industrial load collaborative optimization method in an active power distribution network. A soft open point is arranged in the power distribution network, a photovoltaic node on a main line is connected with a feeder end node, and surplus power is transferred to a weaker voltage end area in a high photovoltaic period. The method comprises the following steps: constructing an active power distribution network model based on linear flow; establishing a photovoltaic and industrial load constraint model; establishing a soft open point model; based on the linear flow model, the photovoltaic and industrial load constraint model and the soft open point model, taking the sum of the active network loss of the power distribution network and the photovoltaic power abandonment amount as the optimization target, and solving to obtain optimal setting values of the photovoltaic power abandonment amount of each node, the photovoltaic reactive power output of each node, the industrial load adjustment amount and the power at the two ends of the soft open point in a dispatching period, so that power system optimization is efficiently performed.

Description

Technical Field

[0001] This invention relates to the field of power system optimization technology, and in particular to a method for the coordinated optimization of soft switching points, photovoltaics, and industrial loads in an active distribution network. Background Technology

[0002] The statements in this section are merely background information relating to this disclosure and do not necessarily constitute prior art.

[0003] To achieve the goals of "carbon peaking and carbon neutrality" and build a clean and efficient new power system, the penetration rate of distributed power sources such as photovoltaics in distribution networks continues to rise. The large-scale centralized connection of photovoltaic systems to medium-voltage distribution networks, especially during peak output periods such as midday on sunny days, can easily cause voltage rises at connection nodes, increased voltage fluctuations at feeder ends, and reverse power flow, increasing line losses and triggering operational risks such as voltage exceeding limits and protection malfunctions. Simultaneously, photovoltaic output is volatile and random, and the load side also exhibits time-varying characteristics. The increased penetration rate of distributed power sources exacerbates the source-load imbalance. In recent years, power electronic devices such as soft-open points have emerged, enabling bidirectional continuous regulation of active and reactive power at previously "normally open / normally closed" tie-line locations. These are considered important means to improve the flexibility of distribution networks and the capacity for renewable energy absorption. On the other hand, some industrial loads possess a certain degree of adjustability and response speed, and have the potential to locally absorb excess electricity and reduce curtailment during periods of photovoltaic surplus.

[0004] In existing technologies, most studies on high-proportion photovoltaic (PV) active distribution network operation are still limited to: either suppressing voltage exceedances through local reactive power regulation or direct curtailment, relying solely on soft switching points for power flow reconfiguration and voltage support, or independently optimizing industrial load curves from a demand response perspective. There is a lack of a systematic approach that integrates PV, soft switching points, and industrial loads into a unified optimization framework for coordinated control. On the one hand, the ability of SOPs (Start of Power Points) to transfer surplus PV power across feeders is not fully utilized, resulting in significant curtailment at some PV connection points to avoid voltage exceedances. On the other hand, industrial load regulation is not coupled with network power flow and node voltage modeling, making it difficult to achieve overall optimization of network losses and curtailment while meeting distribution network security constraints. In summary, existing active distribution network operation methods struggle to simultaneously consider voltage safety, network loss levels, and PV absorption levels in high PV penetration scenarios. There is an urgent need for an active distribution network operation method that coordinates and optimizes PV, soft switching points, and industrial loads, exploring the potential for coordinated control of multiple resources from an integrated source, grid, and load perspective. Summary of the Invention

[0005] To solve the above-mentioned technical problems, or at least partially solve them, this invention provides a method for the coordinated optimization of soft switching points, photovoltaics, and industrial loads in an active distribution network.

[0006] This invention provides a method for the coordinated optimization of soft switches, photovoltaic (PV) power, and industrial loads in an active distribution network. The method involves setting up soft switches in the distribution network to connect PV nodes on the main line to feeder terminal nodes, thereby transferring surplus power to weaker voltage areas during peak PV periods. The method includes: S100, construct an active distribution network model based on linear power flow; S200, establish photovoltaic and industrial load constraint models; S300, establish a soft opening point model; Based on the above linear power flow model, photovoltaic and industrial load constraint model, and soft-start model, S400 aims to minimize the sum of active power loss in the distribution network and photovoltaic curtailment, and solves the operation plan.

[0007] Furthermore, constructing an active distribution network model based on linear power flow includes: using a linear power flow model of a distributed distribution network to describe the relationship between node voltage and branch power. Ignoring the quadratic effect of the square of the branch current on the voltage, the linear power flow model is written as: ; in, Branch roads Resistance and reactance, Branch roads The active and reactive power at time t, from node Flow to Node , and They are nodes and nodes The square of the voltage at time t For the directed branch collection of the active distribution network, , It is the set of nodes in an active distribution network.

[0008] Furthermore, in the active distribution network model, the active and reactive power injected into any node of the active distribution network is composed of photovoltaic output, industrial load, ordinary load, and soft-start injection, satisfying the active and reactive power balance relationship: ; ; in, This indicates that for all nodes that satisfy the condition "branch from node", Pointing to node "downstream node Perform summation; This represents the active power flowing from parent node j to child node m at time t; This represents the active power flowing from parent node i to child node j at time t; branch road The resistance; branch road The squared change in current at time t; This represents the predicted photovoltaic active power output of node j at time t; Indicates that node j at time... The curtailment of solar power has contributed to the cause; Represents a node At any moment The active power load demand; Indicates that node j at time... The soft-start point active power injection; This represents the reactive power flowing from parent node j to child node m at time t; This represents the reactive power flowing from parent node i to child node j at time t; branch road The reactance; This represents the photovoltaic reactive power output of node j at time t; Represents a node At any moment The reactive load demand; Indicates that node j at time... The soft-start point reactive power injection.

[0009] Furthermore, the active distribution network model includes setting capacity constraints for the apparent power of each branch: ,in, branch road Maximum apparent power; The node voltage is constrained within the rated allowable operating range, i.e.:

[0010] in, , They are nodes The lower and upper limits of the square of the voltage. It is the square of the voltage at node j at time t.

[0011] Furthermore, when it is necessary to limit the power purchases from the upstream power grid, the active distribution network model has a control over the active power purchases of the saturation point. No merit Apply boundary constraints: ,in, The maximum active / reactive power that the upstream power grid allows for power purchase. This is the minimum reactive power purchase allowed by the upper-level power grid.

[0012] Furthermore, establishing photovoltaic and industrial load control models includes: For any photovoltaic node Predict photovoltaic active power at a given time t Under the premise that its light discard power at time t satisfy: Photovoltaic moment t reactive power output Limited by the inverter's reactive power regulation capability, the following must be satisfied: , The upper limit of the inverter's reactive power regulation capability; at the same time, the apparent power of the photovoltaic inverter at any moment does not exceed the rated capacity. : ; For the node where the industrial load is located, its active power is expressed as the sum of the baseline value and the adjustment amount: , Let i be the active power of the industrial load at time t. Let i be the industrial load baseline active power at time t. Let be the industrial load adjustment at node i at time t; the active power of the industrial load satisfies the operating range constraints: ,in These represent the upper limit of the active power of the industrial load at time t, respectively.

[0013] Furthermore, establishing a soft-start point model includes: To ensure energy conservation, the active power balance is maintained at the soft-start point: ; in, This represents the amount of active power injected at node i at time t; This represents the amount of active power injected / exchange at node j at time t; This represents the active power loss at node i at time t; This represents the active power loss at node j at time t; This represents the nodes connected at both ends of the soft opening point, and models the coupling relationship between the active power injection and internal losses at both ends of the soft opening point. Furthermore, the apparent power of the soft-start point must be limited by the rated capacity: ; in, This represents the amount of active power injected at node i at time t; This represents the amount of reactive power injected at node i at time t; This represents the upper limit of the apparent power capacity of the soft opening at node i.

[0014] Furthermore, the combined amount of active and reactive power transmitted at both ends is considered. Let the independent variable represent the soft-start loss: ; in, Indicates the soft-start loss coefficient; The above equation represents a nonlinear constraint. To improve the solvability of the model, auxiliary variables are introduced and a second-order cone relaxation method is used to approximate the above equation, which is then written as: ; This transforms the original non-convex quadratic constraint into a second-order cone constraint that can be directly processed by the standard solver.

[0015] Furthermore, the optimization objective is to minimize the sum of active power losses in the active distribution network and the amount of curtailed photovoltaic power, expressed as: ; The first item is the active power loss of the line, the second item is the active power loss of the soft switch, and the third item is the amount of curtailed photovoltaic power. By solving this optimization problem, the amount of solar power curtailment at each node can be obtained within the scheduling cycle. Photovoltaic reactive power output at each node Industrial load regulation and the power at both ends of the soft switch The optimal setting value.

[0016] Secondly, the present invention provides a device for the coordinated optimization of soft switching points, photovoltaics, and industrial loads in an active distribution network, comprising: at least one processing unit, wherein the processing unit is connected to a storage unit via a bus unit, the storage unit stores a computer program that can run on a processor, and the processing unit implements the method for the coordinated optimization of soft switching points, photovoltaics, and industrial loads in the active distribution network by running the computer program stored in the storage unit.

[0017] The technical solutions provided in the embodiments of the present invention have the following advantages compared with the prior art: This invention sets up a soft switch in the distribution network to connect the photovoltaic nodes on the main line to the feeder end nodes. Through the coordination and optimization method of this invention, the surplus power can be transferred from the main line nodes to the end nodes through the soft switch during the high output period of photovoltaic power. On the one hand, it suppresses the voltage over-limit of the photovoltaic access point, and on the other hand, it improves the voltage level at the feeder end. At the same time, it significantly reduces the photovoltaic curtailment and the total equivalent loss of the system, thereby achieving the technical effect of improving the safety and economy of the active distribution network. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart illustrating a method for coordinated optimization of soft switching points, photovoltaic systems, and industrial loads in an active distribution network, provided by an embodiment of the present invention; Figure 2 Topology diagram of the IEEE 33-node power distribution system with improved soft switching provided in this embodiment of the invention; Figure 3 This is a schematic diagram of a comparison table of loss results between cooperative soft-open point optimization and non-cooperative soft-open point optimization provided in an embodiment of the present invention. Figure 4 This is a schematic diagram of a comparison table of per-unit voltage results for cooperative soft-switching optimization and non-cooperative soft-switching optimization provided in an embodiment of the present invention. Figure 5 This is a schematic diagram showing the distribution of camera positions of the inspection equipment provided in an embodiment of the present invention relative to the power transmission lines. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0023] Example 1 like Figure 2 As shown, a soft switch is installed in the distribution network to connect the photovoltaic nodes on the main line to the feeder end nodes, so as to transfer surplus power to the weaker voltage end areas during peak photovoltaic periods. Figure 1As shown, a coordinated optimization method for soft-switching points, photovoltaics, and industrial loads in an active distribution network, which adjusts the transfer of surplus power to weaker voltage end areas during peak photovoltaic periods, includes: S100, construct an active distribution network model based on linear power flow.

[0024] Obtain the topology of the active distribution network and count the nodes and branches involved in the active distribution network. Let... For an active distribution network, When constructing an active distribution network model based on linear power flow for the directed branch set of an active distribution network, the line resistance, reactance, and reference voltage are considered. The parameters are standardized. Considering the small voltage deviation and phase angle difference in the distribution network, a linear power flow model of the distributed distribution network (such as the linearized form of DistFlow) is used to describe the relationship between node voltage and branch power. Ignoring the quadratic effect of the square of the branch current on the voltage, the linear power flow model can be written as: ; in, Branch roads Resistance and reactance, Branch roads The active and reactive power at time t, from node Flow to Node , and They are nodes and nodes The square of the voltage at time t For the directed branch collection of the active distribution network, , It is the set of nodes in an active distribution network. The linear voltage drop relationship between node voltage and branch power is given.

[0025] Furthermore, the active and reactive power injected into any node of an active distribution network consists of photovoltaic output, industrial loads, general loads, and soft-switching injection. For any node... The active and reactive power balance constraints are: ; ; in, This indicates that for all nodes that satisfy the condition "branch from node", Pointing to node "downstream node Perform summation; This represents the active power flowing from parent node j to child node m at time t; This represents the active power flowing from parent node i to child node j at time t; branch road The resistance; branch road The squared change in current at time t; This represents the predicted photovoltaic active power output of node j at time t; Indicates that node j at time... The curtailment of solar power has contributed to the cause; Represents a node At any moment The active power load demand; Indicates that node j at time... The soft-start point active power injection; This represents the reactive power flowing from parent node j to child node m at time t; This represents the reactive power flowing from parent node i to child node j at time t; branch road The reactance; This represents the photovoltaic reactive power output of node j at time t; Represents a node At any moment The reactive load demand; Indicates that node i at time... The soft-start point reactive power injection.

[0026] Furthermore, to ensure the safe operation of the lines, the active distribution network model of this invention sets capacity constraints on the apparent power of each branch: ,in, branch road The maximum apparent power. In implementation, the apparent power capacity constraint for each branch can be written as a second-order cone constraint as needed for direct processing by the solver.

[0027] The active distribution network model limits node voltage to within the rated allowable operating range, i.e.: ; in, , They are nodes The lower and upper limits of the square of the voltage (corresponding to the upper and lower limits of the per-unit voltage). It is the square of the voltage at node j at time t.

[0028] To limit the power purchased by the upstream power grid, the active distribution network model of this invention also considers the active power purchased at time t of the saturation node. No merit Apply boundary constraints: ,in, The maximum active / reactive power that the upstream power grid allows for power purchase. This is the minimum reactive power purchase allowed by the upper-level power grid.

[0029] Through the above relationships, this invention, while maintaining the linearity of the power flow equations, fully characterizes the voltage constraints, power balance constraints, branch capacity constraints, and power exchange boundaries with the upper-level grid of the active distribution network, providing a basic network model for subsequent coordinated optimization.

[0030] S200, establish photovoltaic and industrial load constraint models.

[0031] This invention considers photovoltaic power plants connected to the distribution network as distributed power sources that can reduce output and provide reactive power support.

[0032] For any photovoltaic node Predict photovoltaic active power at a given time t Under the premise that its light discard power at time t satisfy: Discarded light power It cannot be negative or exceed the predicted photovoltaic active power. .

[0033] Photovoltaic moment t reactive power output Limited by the inverter's reactive power regulation capability, the following must be satisfied: , The upper limit of the inverter's reactive power regulation capability; at the same time, the apparent power of the photovoltaic inverter at any moment does not exceed the rated capacity. : ; The combined active and reactive power output cannot exceed the inverter capacity.

[0034] The above constraints collectively constitute the operational constraints of photovoltaic power plant nodes. This is achieved by analyzing the predicted active power output of the photovoltaic system. Reduce power consumption and utilize photovoltaic reactive power. Providing reactive power support can alleviate overvoltage problems at the connection point during peak photovoltaic periods.

[0035] In terms of industrial load modeling, this invention targets the nodes where industrial loads are located (e.g., Figure 2 In the IEEE 33-bus system, Bus 17 expresses its active power as the sum of a baseline value and a regulation value: , Let i be the active power of the industrial load at time t. Let i be the industrial load baseline active power at time t. Let be the industrial load adjustment at node i at time t; the active power of the industrial load satisfies the operating range constraints: ,in These represent the upper limit of the active power of the industrial load at time t, respectively.

[0036] In this invention, As an optimization variable, when the photovoltaic output is high, the industrial load power can be appropriately increased to absorb surplus electricity; when the photovoltaic output is low, the regulation amount should be reduced to avoid introducing unnecessary losses. If necessary, the reactive power of the industrial load can also be expressed as a function of active power according to the power factor relationship or a similar method.

[0037] By using photovoltaic and industrial load constraint models, this invention integrates controllable photovoltaic injection and flexible industrial load regulation into the same optimization framework, enabling the regulation capabilities on both the "source-load" sides to work synergistically.

[0038] S300, establish a soft opening point model; A soft switch, as a flexible power electronic device connecting two feeder sections, enables bidirectional controllable exchange of active and reactive power between the two busbars. This invention sets up a soft switch in the distribution network to connect photovoltaic-rich nodes on the main line (such as the upper busbar near Bus 20–21) to feeder end nodes (such as the feeder where Bus 17 is located), in order to transfer surplus power to the weaker voltage end area during periods of high photovoltaic activity.

[0039] Let the nodes at both ends of the soft opening point be respectively and ( Figure 2 In the example, ab are 17 and 21 respectively, and the corresponding injection powers are respectively To ensure energy conservation, the active power balance constraint at the soft-opening point is as follows:

[0040] in, This represents the amount of active power injected at node i at time t; This represents the amount of active power injected / exchange at node j at time t; This represents the active power loss at node i at time t; This represents the active power loss at node j at time t; This represents the nodes connected at both ends of the soft opening point, and models the coupling relationship between the active power injection and internal losses at both ends of the soft opening point. Considering that the losses of power electronic devices are typically related to the square of the current or power passing through them, this invention uses a quadratic approximation to characterize the soft-switching point losses. This is achieved by considering the combined active and reactive power transmitted at both ends. Let the independent variable represent the soft-start loss: ; in, Indicates the soft-start loss coefficient; In its original form, this is a nonlinear constraint. To improve the solvability of the overall optimization model, this invention introduces auxiliary variables and employs a second-order cone relaxation method to adjust the equation. By performing an approximate transformation, it can be written as: ; This transforms the original non-convex quadratic constraint into a second-order cone constraint that can be directly processed by the standard solver.

[0041] Meanwhile, the apparent power of the soft-start point must be limited by the rated capacity: ; in, This represents the amount of active power injected at node i at time t; This represents the amount of reactive power injected at node i at time t; This represents the upper limit of the apparent power capacity of the soft opening at node i.

[0042] By using the soft-connection model, this invention not only ensures the physical feasibility and capacity safety of the soft-connection, but also maintains the convexity or quasi-convexity of the overall optimization problem by utilizing the second-order cone transformation, so that the power flow routing capability of the soft-connection can be fully utilized in the distribution network.

[0043] Based on the above linear power flow model, photovoltaic and industrial load constraint model, and soft-start model, S400 aims to minimize the sum of active power loss in the distribution network and photovoltaic curtailment, and solves the operation plan.

[0044] Based on the aforementioned linear power flow model, photovoltaic and industrial load model, and soft-start point model, this invention constructs a coordinated optimization model for photovoltaic, soft-start point, and industrial loads to generate an active distribution network operation plan under given load and photovoltaic forecast conditions. The optimization objective is to minimize the sum of active power losses in the distribution network and photovoltaic curtailment, and the objective function is: ; The first term represents the active power loss of the transmission line (which can be approximated by branch current or power), the second term represents the active power loss at the soft-start point, and the third term represents the amount of curtailed photovoltaic power. The objective function can be implemented in either a linear or second-order conical equivalent form as needed.

[0045] During the optimization process, the objective function needs to simultaneously satisfy the constraints of linear power flow and operating boundary conditions of the distribution network, the constraints of photovoltaic and industrial loads, and the constraints of soft-start power and loss. By solving this optimization problem, the amount of photovoltaic curtailment at each node can be obtained within the scheduling cycle. Photovoltaic reactive power output at each node Industrial load regulation and the power at both ends of the soft switch The optimal setting value.

[0046] In the improved IEEE 33-node system shown in Figure 2, a soft-connect point is set up to connect the upstream photovoltaic access point with the end industrial load. Through the coordination optimization method of this invention, surplus power can be transferred from the mainline node (e.g., Bus 21) to the end node (e.g., Bus 17) via the soft-connect point during periods of high photovoltaic output. Figure 3 and Figure 4 As shown, this approach suppresses voltage overshoot at photovoltaic access points and improves the voltage level at the feeder end, while significantly reducing photovoltaic curtailment and total equivalent system losses, thereby achieving the technical effect of improving the safety and economy of the active distribution network.

[0047] Example 2 like Figure 5 As shown in the figure, this invention provides a device for the coordinated optimization of soft-connectors, photovoltaic (PV) loads, and industrial loads in an active distribution network. The device includes at least one processing unit connected to a storage unit via a bus unit. The storage unit, as a computer-readable storage medium, can store software programs, computer-executable programs, and modules, such as the software program, computer-executable program, and module corresponding to the coordinated optimization method for soft-connectors, PV loads, and industrial loads in an active distribution network according to this invention. The processing unit implements the aforementioned coordinated optimization method for soft-connectors, PV loads, and industrial loads in an active distribution network by running the software program, computer-executable program, and module stored in the storage unit.

[0048] Of course, the computer program stored in the memory of the active distribution network soft switch, photovoltaic and industrial load co-optimization device provided in the embodiments of the present invention is not limited to the method operation described above, and can also execute related operations in the active distribution network soft switch, photovoltaic and industrial load co-optimization method provided in any embodiment of the present invention.

[0049] In the embodiments provided by this invention, it should be understood that the disclosed structures and methods can be implemented in other ways. For example, the structural embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, structures, or units, and may be electrical, mechanical, or other forms.

[0050] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0051] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0052] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for coordinated optimization of soft switches, photovoltaics, and industrial loads in an active distribution network, characterized in that, In the distribution network, soft switches are installed to connect photovoltaic nodes on the main line to the end nodes of the feeder, so as to transfer surplus power to the end areas with weaker voltage during peak photovoltaic periods. Methods include: S100, construct an active distribution network model based on linear power flow; S200, establish photovoltaic and industrial load constraint models; S300, establish a soft opening point model; Based on the above linear power flow model, photovoltaic and industrial load constraint model, and soft-start model, S400 aims to minimize the sum of active power loss in the distribution network and photovoltaic curtailment, and solves the operation plan.

2. The method for coordinated optimization of soft switches, photovoltaics, and industrial loads in an active distribution network according to claim 1, characterized in that, Constructing an active distribution network model based on linear power flow includes: using a linear power flow model of a distributed distribution network to describe the relationship between node voltage and branch power. Ignoring the quadratic effect of the square of the branch current on the voltage, the linear power flow model is written as: ； in, Branch roads Resistance and reactance, Branch roads The active and reactive power at time t, from node Flow to Node , and They are nodes and nodes The square of the voltage at time t For the directed branch collection of the active distribution network, , It is the set of nodes in an active distribution network.

3. The method for coordinated optimization of soft switches, photovoltaics, and industrial loads in an active distribution network according to claim 1, characterized in that, In the active distribution network model, the active and reactive power injected into any node of the active distribution network consists of photovoltaic output, industrial load, ordinary load, and soft-connector injection, satisfying the active and reactive power balance constraints as follows: ； ； in, This indicates that for all nodes satisfying "branch from node" Pointing to node "downstream node Perform summation; This represents the active power flowing from parent node j to child node m at time t; This represents the active power flowing from parent node i to child node j at time t; branch road The resistance; branch road The squared change in current at time t; This represents the predicted photovoltaic active power output of node j at time t; Indicates that node j at time... The curtailment of solar power has contributed to the cause; Represents a node At any moment The active power load demand; Indicates that node j at time... The soft-start point active power injection; This represents the reactive power flowing from parent node j to child node m at time t; This represents the reactive power flowing from parent node i to child node j at time t; branch road The reactance; This represents the photovoltaic reactive power output of node j at time t; Represents a node At any moment The reactive load demand; Indicates that node j at time... The soft-start point reactive power injection.

4. The method for coordinated optimization of soft switches, photovoltaics, and industrial loads in an active distribution network according to claim 2, characterized in that, The active distribution network model includes setting capacity constraints for the apparent power of each branch: ,in, branch road Maximum apparent power; The node voltage is constrained within the rated allowable operating range, i.e.: in, , They are nodes The lower and upper limits of the square of the voltage. It is the square of the voltage at node j at time t.

5. The method for coordinated optimization of soft switches, photovoltaics, and industrial loads in an active distribution network according to claim 2, characterized in that, When it is necessary to limit the power purchase capacity of the upstream power grid, the active distribution network model should consider the active power purchase capacity at time t of the saturation node. No merit Apply boundary constraints: ,in, The maximum active / reactive power that the upstream power grid allows for power purchase. This is the minimum reactive power purchase allowed by the upper-level power grid.

6. The method for coordinated optimization of soft switches, photovoltaics, and industrial loads in an active distribution network according to claim 1, characterized in that, The establishment of photovoltaic and industrial load control models includes: For any photovoltaic node Predict photovoltaic active power at a given time t Under the premise that its light discard power at time t satisfy: Photovoltaic moment t reactive power output Limited by the inverter's reactive power regulation capability, the following must be satisfied: , The upper limit of the inverter's reactive power regulation capability; at the same time, the apparent power of the photovoltaic inverter at any moment does not exceed the rated capacity. : ; For the node where the industrial load is located, its active power is expressed as the sum of the baseline value and the adjustment amount: , Let i be the active power of the industrial load at time t. Let i be the industrial load baseline active power at time t. Let be the industrial load adjustment at node i at time t; the active power of the industrial load satisfies the operating range constraints: ,in These represent the upper limit of the active power of the industrial load at time t, respectively.

7. The method for coordinated optimization of soft switches, photovoltaics, and industrial loads in an active distribution network according to claim 1, characterized in that, Establishing a soft-start point model includes: Soft-open-point active power balance constraints that ensure energy conservation: ; in, This represents the amount of active power injected at node i at time t; This represents the amount of active power injected / exchange at node j at time t; This represents the active power loss at node i at time t; This represents the active power loss at node j at time t; This represents the nodes connected at both ends of the soft opening point, and models the coupling relationship between the active power injection and internal losses at both ends of the soft opening point. Furthermore, the apparent power of the soft-start point must be limited by the rated capacity: ； in, This represents the amount of active power injected at node i at time t; This represents the amount of reactive power injected at node i at time t; This represents the upper limit of the apparent power capacity of the soft opening at node i.

8. The method for coordinated optimization of soft switches, photovoltaics, and industrial loads in an active distribution network according to claim 7, characterized in that, The combined amount of active and reactive power transmitted at both ends Let the independent variable represent the soft-start loss: ； in, Indicates the soft-start loss coefficient; The above equation represents a nonlinear constraint. To improve the solvability of the model, auxiliary variables are introduced and a second-order cone relaxation method is used to approximate the above equation, which is then written as: ； This transforms the original non-convex quadratic constraint into a second-order cone constraint that can be directly processed by the standard solver.

9. The method for coordinated optimization of soft switches, photovoltaics, and industrial loads in an active distribution network according to claim 1, characterized in that, The optimization objective is to minimize the sum of active power losses in the active distribution network and solar power curtailment, expressed as: ； The first item is the active power loss of the line, the second item is the active power loss of the soft switch, and the third item is the amount of curtailed photovoltaic power. By solving this optimization problem, the amount of solar power curtailment at each node can be obtained within the scheduling cycle. Photovoltaic reactive power output at each node Industrial load regulation and the power at both ends of the soft switch The optimal setting value.

10. A collaborative optimization device for soft switches, photovoltaics, and industrial loads in an active distribution network, comprising: At least one processing unit, the processing unit being connected to a storage unit via a bus unit, the storage unit storing a computer program that can run on a processor, characterized in that the processing unit implements the coordinated optimization method for soft switching points, photovoltaics, and industrial loads in an active distribution network as described in any one of claims 1-9 by running the computer program stored in the storage unit.

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