Three-phase imbalance treatment method, device, system, equipment, medium and product

Abstract

The invention provides a three-phase imbalance treatment method, device, system, equipment, medium and product, an operation optimization model is adopted, the operation optimization model relates to commutation soft switching constraints and reactive compensation constraints, and a solution for indicating actions of a reactive compensation device and a commutation soft switching is calculated by minimizing an objective function of the operation optimization model. Therefore, three-phase imbalance treatment is carried out through cooperation of the reactive power compensation device and the phase-change soft switch. Due to the addition of the commutation soft switch, the three-phase imbalance treatment response speed is greatly increased; based on the algorithm processing, the topology and commutation soft switch replaces a traditional interconnection switch to be connected between the two transformer areas of the power distribution network, so that interconnection and mutual assistance between the transformer areas can be considered in three-phase imbalance treatment; moreover, the key voltage treatment target of voltage deviation is considered in the operation optimization model, so that the voltage of the power distribution network does not exceed the allowable range of the national standard in a high-permeability distributed power supply scene.

Description

Technical Field

[0001] The present application relates to the field of electric power technology, and in particular to a three-phase imbalance control method, device, system, equipment, medium and product. Background Art

[0002] The distribution network will be connected to a large number of distributed photovoltaics (DPV) to improve the utilization rate of new energy and reduce carbon emissions. However, with the access of massive single-phase DPV, the distribution network will face increasingly serious three-phase imbalance problems, resulting in frequent problems such as power loss and neutral point potential shift. Therefore, the management of three-phase imbalance in the distribution network has become one of the important research topics at this stage.

[0003] At present, the three-phase unbalance control has achieved certain results. The use of passive / active reactive compensation devices for three-phase unbalance control has the advantages of dynamically balancing the three-phase load current and long service life. However, the reactive compensation device has problems such as single function and slow response speed due to the limitation of the reactive compensation device itself (for example, the group switching capacitor bank is limited by the mechanical switch, and the static reactive generator is limited by the characteristics of the semi-controlled device), and it cannot take into account the interconnection between stations. Summary of the invention

[0004] The present application proposes a three-phase imbalance control method, device, system, equipment, medium and product, which can solve one of the above-mentioned technical problems.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, a three-phase unbalance control method is provided, the control method is for a distribution network equipped with a reactive power compensation device and a phase-changing soft switch, the control method is based on an operation optimization model, the objective function of the operation optimization model is constructed based on the distribution network loss, the overall voltage deviation and the three-phase unbalance, the constraints of the operation optimization model include: system flow constraints, safety constraints, distributed photovoltaic active output constraints, power balance constraints, phase-changing soft switch constraints and reactive power compensation device constraints, the control method includes:

[0007] Obtaining monitoring data related to the operation optimization model;

[0008] With the goal of minimizing the objective function, a solution for indicating the actions of the reactive power compensation device and the commutation soft switch is calculated; and

[0009] According to the solution, the reactive power compensation device and the phase-changing soft switch are controlled to operate.

[0010] Based on the above technical solution, an operation optimization model is adopted. The operation optimization model involves phase-changing soft switch constraints and reactive compensation constraints. By minimizing its objective function, the solution for indicating the action of the reactive compensation device and the phase-changing soft switch is calculated. In this way, the reactive compensation device and the phase-changing soft switch are used to coordinate the three-phase unbalance control. The addition of the phase-changing soft switch greatly improves the response speed of the three-phase unbalance control. Based on this algorithm processing and topology, the phase-changing soft switch replaces the traditional connecting switch and is connected between the two substations of the distribution network, so that the three-phase unbalance control can take into account the interconnection between the substations. Moreover, the voltage deviation, a key voltage control target, is taken into account in the operation optimization model, so that in the high-penetration distributed power supply scenario, the distribution network voltage will not exceed the allowable range of the national standard.

[0011] In a possible design of the first aspect, the governance method further includes:

[0012] The strong non-convex nonlinear problem in the operation optimization model is transformed into a mixed integer problem by using second-order cone programming for solving.

[0013] In a possible design manner of the first aspect, the CPLEX commercial solver is used for solving.

[0014] In a possible design manner of the first aspect, the commutation soft switch constraints include: commutation soft switch operation constraints, commutation soft switch power loss constraints and commutation soft switch capacity constraints; the reactive power compensation constraints include: group switching capacitor group constraints and static reactive power generator constraints.

[0015] In a second aspect, a three-phase unbalance control device is provided, the control device is for a distribution network equipped with a reactive power compensation device and a phase-changing soft switch, the control device is based on an operation optimization model, the objective function of the operation optimization model is constructed based on the distribution network loss, the overall voltage deviation and the three-phase unbalance, the constraints of the operation optimization model include: system flow constraints, safety constraints, distributed photovoltaic active output constraints, power balance constraints, phase-changing soft switch constraints and reactive power compensation device constraints, the control device includes:

[0016] An acquisition unit, used for acquiring monitoring data related to the operation optimization model;

[0017] A solution unit, used for calculating and obtaining a solution for indicating the actions of the reactive power compensation device and the phase-changing soft switch with the goal of minimizing the objective function; and

[0018] A control unit is used to control the reactive power compensation device and the phase-changing soft switch according to the solution.

[0019] In a third aspect, a three-phase unbalance control system is provided, the control system comprising: a distribution network equipped with a reactive compensation device and a phase-changing soft switch, and a data processing center, the data processing center being based on an operation optimization model, the objective function of the operation optimization model being constructed based on distribution network losses, overall voltage deviation and three-phase imbalance, the constraints of the operation optimization model comprising: system flow constraints, safety constraints, distributed photovoltaic active output constraints, power balance constraints, phase-changing soft switch constraints and reactive compensation device constraints, the data processing center being used to obtain monitoring data related to the operation optimization model; with the goal of minimizing the objective function, calculating a solution for indicating the action of the reactive compensation device and the phase-changing soft switch; and controlling the action of the reactive compensation device and the phase-changing soft switch according to the solution.

[0020] In a possible design of the third aspect, the phase-changing soft switch is arranged between two contact points of the AC feeder of the distribution network; the phase-changing soft switch includes two three-phase four-wire VSCs.

[0021] In a fourth aspect, an electronic device is provided, comprising: a processor, and a memory coupled to the processor, the memory being used to store a computer program; the processor being used to execute the computer program stored in the memory, so that the electronic device performs the governance method as any possible implementation method in the first aspect.

[0022] In the present application, the electronic device described in the third aspect may be a terminal device or a network device, or a chip (system) or other parts or components arranged in the terminal device or the network device.

[0023] In a fifth aspect, a computer-readable storage medium is provided, comprising a computer program or instructions, which, when executed on a computer, enables the computer to execute the governance method of any possible implementation in the first aspect.

[0024] In a sixth aspect, a computer program product is provided, comprising: a computer program or instructions, which, when executed on a computer, causes the computer to execute the governance method of any possible implementation in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0026] Figure 1 Schematic diagram of the PC-SOP topology and installation position of an embodiment of the present application;

[0027] Figure 2 It is the IEEE33-node distribution network topology of an embodiment of the present application;

[0028] Figure 3 is the load prediction data of each phase in the embodiment of the present application;

[0029] Figure 4 is the DPV output prediction data of the embodiment of the present application;

[0030] Figure 5 is the optimized reactive power compensation result of each phase of CB in the embodiment of the present application;

[0031] Figure 6 is the reactive power compensation result of each phase of SVG after optimization in the embodiment of the present application;

[0032] Figure 7 is the total active power of each phase of the PC-SOP of the embodiment of the present application;

[0033] Figure 8 is the PC-SOP output power during the cycle of the embodiment of the present application;

[0034] Fig. 9 is the optimized voltage distribution of the embodiment of the present application;

[0035] Fig.10 This is the result of three-phase voltage imbalance after optimization in the embodiment of the present application. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0037] It should be noted that, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0038] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0039] In the following, in conjunction with the accompanying drawings, the three-phase imbalance control method, device, system, equipment, medium and product of the embodiments of the present application are exemplarily described.

[0040] (I) This embodiment clarifies the working principle of the phase-changing soft switch:

[0041] First, determine the phase-commutation soft switching structure.

[0042] Smart soft switches (Soft Open Point, SOP) are often installed between adjacent feeders to replace traditional interconnecting switches in distribution networks. They can accurately control three-phase power flows at a lower operating cost, significantly balance load differences and reduce network losses. SOP usually controls back-to-back voltage source converters (VSC) to achieve its basic functions. On this basis, PC-SOP has derived two devices: commutator series SOP and three-phase four-bridge arm SOP. This embodiment is based on the three-phase four-bridge arm SOP to study the coordinated optimization scheduling method of the distribution network based on PC-SOP and reactive power compensation device. The schematic diagram of the PC-SOP topology and installation position is shown in the figure. Figure 1 As shown, its node distribution network topology is as follows Figure 2 The reactive power compensation device is set at Figure 2 At nodes 13, 21 and 30.

[0043] In the reactive power compensation device, the group switching capacitor banks (CB) are controlled by manual switching. The static VAR generator (SVG) quickly adjusts its output reactive power by controlling the on and off of its internal power electronic devices (such as IGBT, etc.).

[0044] The phase-commutation soft-switching PC-SOP consists of a proportional resonant controller, a voltage control loop that controls the output voltage, and a current control loop that provides a reference signal to the pulse width modulator (PWM), thereby independently controlling the current and power of each phase of the VSC.

[0045] The structure of PC-SOP mainly includes two three-phase four-wire VSCs, whose AC side is connected to the AC grid through an LC filter, and the DC side is connected to the two VSCs through a common DC capacitor. In the three-phase four-bridge SOP, the midpoint of the fourth bridge arm of the VSC is connected to the neutral line of the AC grid, that is, Figure 1 Therefore, the VSC is able to perform three-phase decoupling internally, thereby achieving autonomous control of the three-phase power supply and neutral line current, which helps to absorb or release three-phase power on the AC side of the PC-SOP.

[0046] Secondly, determine the mathematical model of phase-changing soft switching.

[0047] In the three-phase four-bridge-arm PC-SOP, each VSC can independently realize three-phase power control. Therefore, the controllable variables of PC-SOP are the active and reactive power of each phase. At the same time, PC-SOP has a DC link that can isolate the influence of the reactive output of the VSCs on both sides, and its mathematical modeling only needs to meet the VSC capacity.

[0048] 1) PC-SOP operation constraints

[0049] The sum of the input power and output power of all phases in PC-SOP needs to be zero, and its operating constraints are:

[0050]

[0051] Where: is the active power transmitted by the VSC of the PC-SOP access node i in phase ω at time t; is the active power loss generated by the VSC of the PC-SOP connected to the node i in the ω phase at time t; is the active power transmitted by the VSC of the PC-SOP access node j in phase ω at time t; is the active power loss generated by the VSC of the PC-SOP access node j in phase ω at time t, and the value space Ω of ω is three phases A, B, and C. Figure 7 As shown in Figure 1, the total active power of each phase of PC-SOP is approximately 0, which satisfies the constraint condition of formula (1).

[0052] 2) PC-SOP power loss constraints

[0053]

[0054] Where: η PC-SOP is the PC-SOP power loss coefficient; is the active power transmitted by the VSC of the PC-SOP access node i in phase ω at time t; is the reactive power transmitted by the VSC of the PC-SOP access node i in phase ω at time t; is the active power transmitted by the VSC of the PC-SOP access node j in phase ω at time t; is the reactive power transmitted by the VSC of the PC-SOP access node j in phase ω at time t. Figure 8 As shown, the active power result of VSC in the ω phase is shown in sub-figure (a), and the reactive power result of VSC in the ω phase is shown in sub-figure (b)

[0055] 3) PC-SOP capacity constraints

[0056]

[0057] Where: is the VSC capacity of PC-SOP access node i; is the VSC capacity of PC-SOP access node j.

[0058] (II) This embodiment clarifies a three-phase unbalance management model for a distribution network considering the coordination of PC-SOP and reactive power compensation device, including the following steps:

[0059] Determine the three-phase unbalance control model of the distribution network considering the coordination of PC-SOP and reactive power compensation device;

[0060] The distribution network collaborative optimization model considering PC-SOP and reactive compensation devices includes objective function, distribution network flow constraints, safe operation constraints and traditional regulation resource constraints, and the quadratic cone programming SOCP is used to linearize the model and then solve it.

[0061] 1) Objective function

[0062] In the proposed model, the objective function consists of the following parts: distribution network loss, overall voltage deviation, and three-phase imbalance.

[0063] minf=λ LIN f LIN +λ SYN f SYN +λ UNB f UNB (6)

[0064]

[0065] μ LIN +μ SYN +μ UNB =1(10)

[0066] Where: LIN , SYN , UNB are the weight factors of network loss target, overall voltage deviation target and three-phase unbalance target respectively; f LIN 、f SYN 、f UNB They are respectively the measured distribution network loss, overall voltage deviation and three-phase imbalance; μ LIN , μ SYN , μ UNB are the weights of the network loss target, the overall voltage deviation target and the voltage imbalance target respectively; They are the initial values ​​of the network loss target, the overall voltage deviation target and the three-phase unbalance target before optimization.

[0067] 1) Distribution network loss

[0068]

[0069] Where: N bus is the number of distribution network nodes; I ij,ω 、r ij,ω are the branch current and resistance of phase ω between node i and node j respectively; Δt is the duration of a single time period, that is, the present invention takes 1 day as an optimization cycle, which is divided into 24 time periods, and a single time period is 1 hour.

[0070] 2) Overall voltage deviation

[0071]

[0072] Where: N bus is the number of distribution network nodes; V j,ω is the node voltage of the ω phase at node j, that is Fig. 9 Results: N is the reference voltage of the distribution network;.

[0073] 3) Three-phase imbalance

[0074]

[0075] Where: N bus is the number of distribution network nodes; d j is the voltage three-phase unbalance degree at node j, that is Fig.10 According to IEEE Std112-2017, the definition of the three-phase unbalance degree of node j voltage is shown in equations (14) to (15).

[0076]

[0077] Where: L j is the average value of the three-phase voltage amplitude at node j; V j,A is the node voltage of phase A at node j; V j,B is the node voltage of phase B at node j; V j,C is the node voltage of phase C at node j;.

[0078] 2) Constraints

[0079] ① System power flow constraints

[0080]

[0081] Where: p j,ω ,q j,ω are the active and reactive injected powers of node j in phase ω respectively; P jk,ω , Q jk,ωis the active and reactive power flowing from node j to the next node k in phase ω; P ij,ω , Q ij,ω I is the active and reactive power of the previous node i flowing into node j in phase ω; ij,ω is the branch current of phase ω between node i and node j; V i,ω is the node voltage of the ω phase of node i; V j,ω is the node voltage of the ω phase at node j; r ij,ω 、x ij,ω are the resistance and reactance of phase ω between node i and node j respectively; g j,ω 、b j,ω are the conductance and susceptance of node j in phase ω respectively.

[0082] ② Security constraints

[0083]

[0084] Where: V j,ω is the node voltage of the ω phase at node j; V max 、V min is the upper and lower limits of the node voltage; I ij,ω is the branch current of phase ω between node i and node j; I max ,I min is the upper and lower limits of branch current; P GRI,ω,t , Q GRI,ω,t are the active power and reactive power of the distribution network interacting with the upper power grid in phase ω; P GRI,max , Q GRI,max , P GRI,min , Q GRI,min are the maximum and minimum interaction power values ​​respectively.

[0085] ③ Distributed photovoltaic (DPV) active output constraints (other power sources can be used)

[0086] In actual power grids, most DPVs are uncontrollable active power and controllable reactive power resources, and the active output is the predicted output of DPV.

[0087]

[0088] Where: are the actual output of the photovoltaic power station installed at node j at time t in phase ω; They are the predicted output of the photovoltaic power station installed at node j at time t in phase ω, namely Figure 4 Predict data.

[0089] ④ Constraints on group switching capacitor banks CB

[0090]

[0091] Where: is the reactive compensation power of the CB connected to node j at time t in phase ω, that is, Figure 5 result; is the number of operational groups of CB connected to node j in phase ω at time t, which is a discrete variable value; is the number of operational groups of CB connected to node j-1 in phase ω at time t, which is a discrete variable value; is the compensation power of each group of CB, which is a constant; The upper limit of the number of CB groups connected to node j; This is the upper limit of the number of CB operations.

[0092] In addition, the absolute value constraint in the above formula can be processed as follows: by adding an auxiliary variable that represents the change in CB compensation capacity between adjacent time periods: Then we can get:

[0093]

[0094] Where: is the action identifier of the CB connected to node j at time t in phase ω, which is a discrete variable value; is the number of operational groups of CB connected to node j in phase ω at time t, which is a discrete variable value; The upper limit of the number of CB groups connected to node j; This is the upper limit of the number of CB operations.

[0095] ⑤ Static VAR generator SVG constraints

[0096]

[0097] Where: is the compensation power of each group of SVG, that is Figure 6 result; are the lower and upper limits of SVG compensation power respectively. Considering that in the operation of active distribution network, as the penetration rate of DPV continues to increase, it may cause system power flow to reverse and overvoltage problems to occur, so the compensation lower limit of SVG in this paper is

[0098] ⑥PC-SOP constraints

[0099] PC-SOP constraints include operation constraints (Equation (1)), power loss constraints (Equation (2), Equation (2)), and capacity constraints (Equation (4), Equation (5)).

[0100] ⑦Power balance constraints

[0101]

[0102] Where: PIN , Q IN are the sum of active and reactive power injected into each phase of each node in the distribution network; P load , Q load are the sum of active and reactive loads of each phase of each node in the distribution network, that is, Figure 3 The sum of each phase load data; P GRI , Q GRI are the sum of active power and reactive power of each phase of the distribution network interacting with the upper power grid; P DPV The sum of the outputs of distributed power sources connected to each phase; Q CB is the sum of the reactive outputs of each CB; Q SVG is the sum of the reactive power outputs of each SVG; PC-SOP is the sum of active power transmitted by PC-SOP, Q PC-SOP is the sum of reactive power transmitted by PC-SOP.

[0103] Determine the solution method of the three-phase unbalance control model of the distribution network

[0104] The above distribution network optimization model can be expressed as formula (23).

[0105]

[0106] The objective function, constraint formula (2), formula (3), and formula (16) in this model are all strongly non-convex forms, belonging to the mixed integer nonlinear programming problem and difficult to solve. SOCP has obvious advantages in convergence speed and optimization ability due to its characteristics such as smoothness and symmetry of search space, and can ensure the optimal solution. Therefore, SOCP is introduced to transform the model of formula (23) into a mixed integer model to achieve efficient solution of the original model.

[0107] The power flow constraint SOCP is divided into two steps: ① define new optimization variables - the square of the node voltage amplitude and the square of the current amplitude, so as to eliminate the influence of the phase angle on the power flow calculation; ② use the second-order cone relaxation technology to transform the original non-convex constraint into a convex constraint, so that it can be linearized and solved. The power flow constraint of the transformed system is shown in formula (24).

[0108]

[0109] Where: It is the square of the branch current between the ω phase node i and the node j, and the square of the node voltage at the node i.

[0110] At the same time, convert equations (2) and (3) into second-order cone form, that is:

[0111]

[0112] The transformed mixed integer model can be expressed as formula (27).

[0113]

[0114] The transformed model is formula (27), which is a mixed integer second-order cone programming problem and can be directly solved using the CPLEX commercial solver.

[0115] By solving the model, the following formula can be obtained to indicate the reactive power compensation device (in formula (2) and formula (3)): ) and the solution of the phase-changing soft switching action; and the distribution network power flow calculation result, that is, the node voltage (V in formula (16) j,ω ), branch current (I in equation (16) ij,ω ), active injection power (p in equation (16) j,ω ) and reactive injection power (q in equation (16) j,ω ). Then, according to the solution, the reactive power compensation device and the phase-changing soft switch are controlled.

[0116] The hardware platform is Intel(R) Xeon(R) CPU E3-1231 v3 @ 3.4 GHz and 16 GB RAM. The software platform is Matlab R2023b, integrated optimization toolbox YALMIP (version 20210331) and solver IBM ILOGCPLEX (version 12.10.0).

[0117] The embodiment of the present application further provides a three-phase unbalance control device, the control device is for a distribution network equipped with a reactive power compensation device and a phase-changing soft switch, the control device is based on an operation optimization model, the objective function of the operation optimization model is constructed based on the distribution network loss, the overall voltage deviation and the three-phase unbalance, the constraint conditions of the operation optimization model include: system flow constraint, phase-changing soft switch constraint and reactive power compensation constraint, the control device includes:

[0118] An acquisition unit, used for acquiring monitoring data related to the operation optimization model;

[0119] A solution unit, used for calculating and obtaining a solution for indicating the actions of the reactive power compensation device and the phase-changing soft switch with the goal of minimizing the objective function; and

[0120] A control unit is used to control the reactive power compensation device and the phase-changing soft switch according to the solution.

[0121] An embodiment of the present application also provides a three-phase unbalance management system, which includes: a distribution network equipped with a reactive compensation device and a phase-changing soft switch, and a data processing center, wherein the data processing center is based on an operation optimization model, wherein the objective function of the operation optimization model is constructed based on distribution network losses, overall voltage deviation, and three-phase imbalance, and the constraints of the operation optimization model include: system flow constraints, safety constraints, distributed photovoltaic active output constraints, phase-changing soft switch constraints, and reactive compensation device constraints, and the data processing center is used to obtain monitoring data related to the operation optimization model; with the goal of minimizing the objective function, calculate and obtain a solution for indicating the action of the reactive compensation device and the phase-changing soft switch; and control the action of the reactive compensation device and the phase-changing soft switch based on the solution.

[0122] Optionally, the phase-changing soft switch is arranged between two contact points of the AC feeder of the distribution network; the phase-changing soft switch includes two three-phase four-wire VSCs.

[0123] An embodiment of the present application also provides an electronic device, comprising: a processor, and a memory coupled to the processor, wherein the memory is used to store a computer program; the processor is used to execute the computer program stored in the memory, so that the electronic device executes a method as described in any one of the above embodiments.

[0124] The electronic device may be a computing device such as a desktop computer, a notebook, a palmtop computer, a cloud server, etc. The electronic device may include, but is not limited to, a processor and a memory.

[0125] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the electronic device, and various interfaces and lines are used to connect various parts of the entire device.

[0126] The memory may be used to store the computer program, and the processor implements various functions of the electronic device by running or executing the computer program stored in the memory and calling the data stored in the memory.

[0127] The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function, etc.; the data storage area may store data created according to the use of the mobile phone, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0128] The embodiment of the present application also provides a storage medium, the storage medium is a computer-readable storage medium, the computer program is stored in the computer-readable storage medium, and the computer program, when executed by the processor, can implement the steps of each of the above-mentioned method embodiments. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0129] An embodiment of the present application further provides a computer program product, including: a computer program or instructions, which, when executed on a computer, enables the computer to execute any of the above-mentioned possible implementation methods.

[0130] The above is a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications are also considered to be within the scope of protection of the present application.

Claims

1. A three-phase imbalance control method, characterized in that: The control method is aimed at a distribution network equipped with a reactive power compensation device and a phase-changing soft switch. The control method is based on an operation optimization model. The objective function of the operation optimization model is constructed based on the distribution network loss, the overall voltage deviation and the three-phase imbalance. The constraints of the operation optimization model include: system flow constraints, safety constraints, distributed photovoltaic active output constraints, power balance constraints, phase-changing soft switch constraints and reactive power compensation device constraints. The control method includes: Obtaining monitoring data related to the operation optimization model; With the goal of minimizing the objective function, a solution for indicating the actions of the reactive power compensation device and the commutation soft switch is calculated; and According to the solution, the reactive power compensation device and the phase-changing soft switch are controlled to operate.

2. The treatment method according to claim 1, characterized in that: The governance method also includes: The strong non-convex nonlinear problem in the operation optimization model is transformed into a mixed integer problem by using second-order cone programming for solving.

3. The treatment method according to claim 2, characterized in that: The CPLEX commercial solver is used for solving.

4. The treatment method according to claim 1, characterized in that: The commutation soft switch constraints include: commutation soft switch operation constraints, commutation soft switch power loss constraints and commutation soft switch capacity constraints; the reactive power compensation device constraints include: group switching capacitor bank constraints and static reactive power generator constraints.

5. A three-phase unbalanced treatment device, characterized in that: The control device is for a distribution network equipped with a reactive power compensation device and a phase-changing soft switch. The control device is based on an operation optimization model. The objective function of the operation optimization model is constructed based on the distribution network loss, the overall voltage deviation and the three-phase imbalance. The constraints of the operation optimization model include: system flow constraints, safety constraints, distributed photovoltaic active output constraints, power balance constraints, phase-changing soft switch constraints and reactive power compensation device constraints. The control device includes: An acquisition unit, used for acquiring monitoring data related to the operation optimization model; A solution unit, used for calculating and obtaining a solution for indicating the actions of the reactive power compensation device and the phase-changing soft switch with the goal of minimizing the objective function; and A control unit is used to control the reactive power compensation device and the phase-changing soft switch according to the solution.

6. A three-phase unbalanced treatment system, characterized in that: The governance system includes: a distribution network equipped with a reactive power compensation device and a phase-changing soft switch, and a data processing center. The data processing center is based on an operation optimization model. The objective function of the operation optimization model is constructed based on the distribution network loss, the overall voltage deviation and the three-phase imbalance. The constraints of the operation optimization model include: system flow constraints, safety constraints, distributed photovoltaic active output constraints, power balance constraints, phase-changing soft switch constraints and reactive power compensation device constraints. The data processing center is used to obtain monitoring data related to the operation optimization model; with the goal of minimizing the objective function, calculate and obtain a solution for indicating the action of the reactive power compensation device and the phase-changing soft switch; and control the action of the reactive power compensation device and the phase-changing soft switch based on the solution.

7. The governance system according to claim 6, characterized in that: The phase-changing soft switch is arranged between two contact points of the AC feeder of the distribution network; the phase-changing soft switch includes two three-phase four-wire VSCs.

8. An electronic device, characterized in that: The electronic device comprises: a processor, and a memory coupled to the processor, The memory is used to store computer programs; The processor is used to execute the computer program stored in the memory, so that the electronic device executes the method for measuring the core quality index according to any one of claims 1 to 4.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a computer program or an instruction. When the computer program or the instruction is executed on a computer, the computer executes the method for calculating the core quality index according to any one of claims 1 to 4.

10. A computer program product, characterized in that The computer program product comprises: a computer program or instructions, which, when executed on a computer, enables the computer to execute the method for calculating the core quality index according to any one of claims 1 to 8.

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