A power distribution network power quality treatment method and device based on a flexible multi-state switch

Abstract

The present application relates to the technical field of power system, specifically relates to a kind of power distribution network power quality treatment method and device based on flexible multi-state switch, the method will flexible multi-state switch FMS according to actual demand be installed on the node in power system;According to the actual operation data of three-phase unbalanced power system, the mathematical model of the power distribution network accessed to FMS is established, the mathematical model of the power distribution network accessed to FMS includes objective function, the objective function is based on the minimum of network total network loss with line loss and FMS operation loss being taken into account, and the control strategy and operating mode of flexible multi-state switch FMS are determined;It is applied to the optimization control of the power distribution network based on FMS.Simulation experiment is carried out in IEEE 33 node power distribution network model, and the results show that FMS can effectively reduce system network loss, improve voltage level and improve three-phase unbalance degree.The method provides strong technical support for the application of flexible multi-state switch in actual power system.

Description

Technical Field

[0001] This invention relates to the field of power system technology, specifically to a method and device for power quality management in distribution networks based on flexible multi-state switches. Background Technology

[0002] With the growth of global energy demand and increasing pressure for environmental protection, distributed energy resources are being used more and more widely in power systems. Distributed energy sources, such as photovoltaic and wind power, are clean and sustainable; however, the randomness and volatility of their output power pose new challenges to the stability and reliability of traditional power systems. Especially in situations with high penetration rates, the power grid faces a series of problems, including voltage fluctuations, frequency deviations, and three-phase imbalances. These problems not only affect power quality but can also lead to equipment damage and system collapse.

[0003] Power quality issues mainly include voltage sags, voltage fluctuations, voltage imbalances, and harmonic pollution. These problems negatively impact the reliability and security of power supply for industrial and residential users. Traditional power quality management methods primarily rely on reactive power compensation equipment and filters, but these devices often fail to achieve the desired results when faced with complex power quality problems.

[0004] To address these challenges, flexible multi-state switches (FMS), as a novel type of power electronic device, have gradually attracted widespread attention. FMS features flexible control and efficient operation, and can improve voltage distribution, reduce power losses, and resolve power imbalances by regulating active and reactive power. The core component of an FMS is a back-to-back voltage source converter, whose bidirectional power flow and independent power control capabilities give it significant advantages in modern power systems.

[0005] In practical applications, FMS can not only supply power to loads but also feed the power from distributed generation sources back to the grid. Its advanced control strategies, such as vector control and DC voltage control, ensure independent regulation of active and reactive power, significantly enhancing the system's dynamic response and operational stability. By flexibly adjusting power flow, FMS effectively manages power quality.

[0006] Flexible multi-state switches (FMS) have been widely applied in distribution networks. For example, FMS has shown good results in reducing system network losses, improving voltage levels, and solving voltage fluctuations and three-phase imbalance problems. However, existing research mainly focuses on the application of FMS in single-phase multi-node systems, failing to fully consider the situation of three-phase unbalanced systems. To further explore the application of FMS in three-phase systems, based on the optimization model of distributed generator sets and FMS in three-phase unbalanced distribution networks, research has been conducted on the comprehensive management of power quality of the system using optimization algorithms such as second-order cone programming and multi-objective optimization models, achieving certain results. However, these traditional optimization algorithms often face problems such as high solution difficulty and long computation time when dealing with highly complex optimization problems, making it difficult to obtain ideal optimization results.

[0007] Furthermore, heuristic algorithms, a class of optimization algorithms based on empirical inspiration and natural phenomena, possess strong global search capabilities and flexibility, enabling them to find optimal solutions in complex high-dimensional search spaces. These algorithms have applications in power systems across numerous areas, such as optimizing power flow distribution, improving system stability, and optimizing resource allocation. Compared to traditional optimization methods, heuristic algorithms offer advantages such as shorter development time and stronger system robustness, particularly excelling when handling incomplete or noisy data. With the development of smart grids, heuristic algorithms are playing an increasingly important role in the optimal control of power systems. Achieving adaptive control and optimized operation of power systems through intelligent means will be a crucial direction for future power system development.

[0008] CN118300197A discloses a distribution network dispatching method, device, electronic equipment, and storage medium, which dispatches flexible multi-state switches based on an optimized dispatching strategy. However, the dispatching of distribution networks containing flexible multi-state switches has certain limitations. Its technology mainly focuses on voltage optimization and switch dispatching, without addressing more complex distribution network issues such as three-phase imbalance and comprehensive power quality management. In addition, although the patent proposes constraints on active and reactive power, it does not conduct in-depth research on the impact of the converter losses of the flexible multi-state switches themselves on the overall performance. Furthermore, the patent does not clearly provide practical verification of application scenarios, especially lacking sufficient adaptability analysis for dynamic operating environments such as load fluctuations and distributed energy access. Summary of the Invention

[0009] Purpose of the invention: To address the shortcomings of existing technologies in handling power quality issues when distributed energy sources are connected to the power grid, this invention provides a power quality management method for distribution networks based on flexible multi-state switches. This invention also discloses a power quality management device for distribution networks based on flexible multi-state switches.

[0010] Technical Solution: This invention relates to a power quality management method for distribution networks based on flexible multi-state switches. It employs back-to-back voltage source converters as one form of multi-state switch implementation, possessing bidirectional power flow and independent power control capabilities. Efficient power transmission is achieved through AC-DC and DC-AC conversion. During normal operation, the dual-terminal flexible multi-state switch uses a PQ-VdcQ control mode to regulate power transmission and maintain DC voltage. The multi-terminal flexible multi-state switch stabilizes AC voltage through a VdcQ mode, ensuring overall system stability. The method includes:

[0011] Flexible multi-state switches (FMS) are installed on nodes in a power system, which is a single-phase and / or three-phase unbalanced distribution network, according to actual needs.

[0012] Based on the actual operating data of the three-phase unbalanced power system, a mathematical model of the distribution network connected to the FMS is established. The mathematical model of the distribution network connected to the FMS includes an objective function. The objective function is based on minimizing the total network loss, taking into account line losses and FMS operating losses. The control strategy and operating mode of the flexible multi-state switch FMS are also determined.

[0013] Based on the mathematical model of the distribution network connected to the FMS and the control strategy and operation mode of the flexible multi-state switch FMS, the operation constraints of the FMS, the power flow balance constraints of the distribution network, the voltage and current amplitudes and the three-phase imbalance constraints of the system are determined in the distribution network containing the flexible multi-state switch.

[0014] The HOA-DE differential algorithm is adopted, based on the control strategy and operation mode of the flexible multi-state switch (FMS), and considering the constraints in the distribution network containing the FMS, to optimize the system network loss including line losses and FMS operation losses. The HOA-DE algorithm is used to perform a preliminary search using the HOA algorithm, and then to optimize using the mutation and crossover strategies of the DE differential evolution algorithm.

[0015] Verify the effectiveness of the HOA-DE (Hike Differential Algorithm) for optimizing network loss in the system.

[0016] Furthermore, including:

[0017] The objective function of the HOA-DE algorithm is to minimize the system network loss, taking into account line loss and FMS operation loss. The objective function is expressed as:

[0018]

[0019] Among them, Ω b Let be the set of all nodes in the power system. Inject into node i The active power of the phase, For a set of three phases, let the three phases be phase a, phase b, and phase c, Ω FMS A collection of FMS connected to the power system. For the k-th FMS on the j-th line Power loss inside the phase converter.

[0020] Furthermore, including:

[0021] The determination of the control strategy and operating mode of the flexible multi-state switch (FMS) includes:

[0022] Based on the balance between the active power injected into the associated feeder by the FMS and the internal losses of the converter composed of the flexible multi-state switch, an FMS operation balance constraint is established.

[0023] Based on the principle that the active and reactive power of each node in the power system remains balanced during stable operation, a power flow balance constraint is established.

[0024] Constrain the magnitudes of node voltage and current;

[0025] The voltage imbalance in the system is defined by the ratio of the deviation of the square of the three-phase voltage amplitude to the square of the average voltage amplitude, and the three-phase voltage imbalance is constrained.

[0026] The root node current imbalance is defined by the ratio of the negative sequence current amplitude to the positive sequence current amplitude, and constraints on the three-phase current imbalance at the root node are established.

[0027] Furthermore, including:

[0028] The FMS operational balance constraint is expressed as follows:

[0029]

[0030] in, Inject the active power of the j-th branch into the k-th FMS;

[0031] The active power injected into the j-th branch by the k-th FMS is... There are constraints, expressed as follows:

[0032]

[0033] in, Inject reactive power from the j-th branch into the k-th FMS. The converter loss coefficient;

[0034] Constrain FMS operation Upper and lower limit constraints are represented as follows:

[0035]

[0036] In the formula, The k-th FMS is located on the j-th branch. Phase converters allow for maximum and minimum reactive power values.

[0037] Furthermore, including:

[0038] The power flow balance constraint is expressed as:

[0039]

[0040] S ij =V i I ij (6)

[0041]

[0042] In the formula, I ij S represents the current flowing from node i to node j. ij Z represents the complex power flowing from node i to node j. ij S represents the impedance on the line. j The injected power at node j, Ω REF As the reference node, S ij S is calculated from the voltage at node i and the current at line (i,j). j It consists of distributed generation, multi-state switches, and line loads.

[0043] Furthermore, including:

[0044] The constraints on the node voltage and current amplitudes include:

[0045] The node voltages in the system are constrained, and the voltage amplitude of each phase at each node is expressed as follows:

[0046]

[0047] In the formula, These are the upper and lower limits of the voltage amplitude at node i, respectively. This constraint applies to the set of all nodes except the reference node.

[0048] The constraint on the branch current in the line is expressed as:

[0049]

[0050] In the formula, This represents the maximum current in line (i,j).

[0051] Furthermore, the constraint on the three-phase voltage imbalance includes:

[0052]

[0053] In the formula, For node i Phase voltage unbalance parameters It is the average of the squared magnitudes of the voltage amplitude at node i.

[0054] Furthermore, the establishment of constraints on the three-phase current imbalance at the root node includes:

[0055]

[0056] Among them, C I The root node three-phase current imbalance parameters are... This is the maximum value of the parameter. These are the positive and negative sequence current amplitudes at the root node in the system, calculated as follows:

[0057]

[0058] a = e j2π / 3 (15)

[0059] In the formula, These are the phase currents at the root node, a, b, and c, respectively.

[0060] Furthermore, this includes: optimizing the system network loss by employing the HOA-DE (Hike Differential Algorithm-DE) to account for line losses and FMS (Fulfilled System Management) operating losses, including: initializing the hiker, generating a set of initial candidate solutions, and considering the reactive power of the FMS. As a hiking population X i Write relevant internal loss parameters of the FMS converter, and write constraints such as node voltage amplitude, three-phase voltage imbalance, and root node current imbalance based on the operating characteristics of the FMS; calculate the fitness value F(x) with the system network loss f, which includes line loss and FMS operating loss, as the optimization objective.

[0061] Calculate the hiker's speed W using the Tobler hiking function. i t And based on the hiker Current speed W i t Update its location to obtain Evaluate the new fitness;

[0062] After the initial search, the mutation and crossover strategies of the DE algorithm are used for optimization. The quality of the solution after each mutation and crossover is evaluated. Solutions that do not meet the FMS operation constraints and voltage and current amplitude constraints are discarded, and solutions that do not meet the three-phase imbalance constraints are penalized.

[0063] Based on the evaluation results after crossover mutation, select the individual X with the highest fitness. best Extract its corresponding The fitness value of the objective function is updated as the final optimization result.

[0064] On the other hand, the present invention also provides a power quality management device for distribution networks based on a flexible multi-state switch, comprising:

[0065] A configuration module is used to install the flexible multi-state switch (FMS) on nodes in a power system according to actual needs, wherein the power system is a single-phase and / or three-phase unbalanced distribution network.

[0066] The model building module is used to establish a mathematical model of the distribution network connected to the FMS based on the actual operating data of the three-phase unbalanced power system. The mathematical model of the distribution network connected to the FMS includes an objective function, which is based on minimizing the total network loss including line losses and FMS operating losses, and determines the control strategy and operating mode of the flexible multi-state switch FMS.

[0067] The optimization module is used to optimize the system network loss, which takes into account line loss and FMS operation loss, using the hiking differential algorithm HOA-DE. The hiking differential algorithm is to perform an initial search using the hiking optimization algorithm HOA, and then optimize using the mutation and crossover strategies of the differential evolution algorithm DE.

[0068] The verification module is used to verify the effectiveness of the HOA-DE algorithm in optimizing network loss in the system.

[0069] Beneficial effects: Compared with the prior art, the present invention has the following advantages:

[0070] This invention proposes a power quality management method for distribution networks based on flexible multi-state switches (FMS). By combining the hiking optimization algorithm and the differential evolution algorithm, a hiking differential algorithm is proposed and successfully applied to the optimization control of a real power system. Simulation results verify the significant effects of this method in reducing system network losses, improving voltage levels, and mitigating three-phase imbalance. This method not only improves the optimization control performance of FMS in distribution networks but also provides strong support for the stable operation and efficient management of future power systems, demonstrating broad application prospects and practical value. Attached Figure Description

[0071] Figure 1 This is a schematic diagram of the multi-terminal flexible multi-state switch described in an embodiment of the present invention;

[0072] Figure 2The flowchart of the HOA-DE algorithm described in this embodiment of the invention is shown below.

[0073] Figure 3 This is a schematic diagram of the FMS access location in a single-phase 33-node distribution network according to an embodiment of the present invention;

[0074] Figure 4 This is a voltage curve diagram of the FMS connected at different locations according to an embodiment of the present invention;

[0075] Figure 5 This is a schematic diagram of the FMS access location in a three-phase 33-node distribution network according to an embodiment of the present invention;

[0076] Figure 6 This is a schematic diagram of voltage level curves under three scenarios described in the embodiments of the present invention. Detailed Implementation

[0077] 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, and 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.

[0078] This invention discloses a power quality management method for distribution networks based on flexible multi-state switches, the method comprising:

[0079] S1 installs the flexible multi-state switch (FMS) on nodes in the power system according to actual needs. The power system is a single-phase and / or three-phase unbalanced distribution network.

[0080] S2 establishes a mathematical model of the distribution network connected to the FMS based on the actual operating data of the three-phase unbalanced power system. The mathematical model of the distribution network connected to the FMS includes an objective function. The objective function is based on minimizing the total network loss, including line losses and FMS operating losses, and determines the control strategy and operating mode of the flexible multi-state switch FMS.

[0081] In this embodiment, the present invention analyzes the architecture of the FMS and establishes an optimization model based on the three-phase imbalance constraints of the system operation, including: establishing voltage, current and power distribution models of each node based on the actual operating data of the power system;

[0082] Consider the electrical connections and power flow between different nodes to determine the electrical parameters of the system.

[0083] The optimization objective function is set with the main objectives of reducing system network losses and improving voltage distribution, while also taking into account the improvement of three-phase imbalance.

[0084] Furthermore, in this embodiment, the control strategy and operating mode of the flexible multi-state switch are determined;

[0085] Based on the balance between the active power injected into the associated feeder by the FMS and the internal losses of its converter, an FMS operation balance constraint is established.

[0086] Power flow balance constraints are established based on maintaining a balance between active and reactive power among nodes in the power system during stable operation.

[0087] To ensure superior power quality of the system, the amplitude of node voltages is constrained;

[0088] To prevent excessively high circuit temperatures from causing material aging, circuit damage, or short circuits, the current amplitude is constrained.

[0089] The voltage imbalance in the system is defined by the ratio of the deviation of the square of the three-phase voltage amplitude to the square of the average voltage amplitude, and the three-phase voltage imbalance is constrained.

[0090] The root node current imbalance is defined by the ratio of the negative sequence current amplitude to the positive sequence current amplitude, and constraints on the three-phase current imbalance at the root node are established.

[0091] S3 uses the HOA-DE (Hike Differential Algorithm) to optimize the system network loss, taking into account line loss and FMS operation loss. The HOA-DE algorithm is used to perform an initial search using the HOA (Hike Optimization Algorithm) and then to optimize using the mutation and crossover strategies of the DE (Differential Evolutionary Algorithm).

[0092] The Hiking Optimization Algorithm (HOA) is a metaheuristic optimization algorithm inspired by the experience of hiking. As hikers attempt to summit mountains, hills, or rocks, they consciously or unconsciously consider the steepness of the terrain—a popular recreational activity—and the algorithm recognizes the similarity between the search landscape and the mountainous terrain traversed by the hiker. The mathematical model of HOA is based on the Tobler hiking function, which determines the hiker's (agent's) walking speed by considering the terrain's elevation and the distance traveled. During the solution of the optimization problem, the Tobler hiking function (THF) is used to determine the hiker's position.

[0093] The hiker is initialized, generating a set of initial candidate solutions based on the active and reactive power of the FMS. As a hiking population X iThe relevant internal loss parameters of the FMS converter are written into the data, and constraints such as node voltage amplitude, three-phase voltage imbalance, and root node current imbalance are written based on the operating characteristics of the FMS. The system network loss f, which includes line losses and FMS operating losses, is used as the optimization objective. The fitness value F(x) is calculated, and the hiker's speed W is calculated based on the Tobler hiking function. i t And based on the hiker Current speed W i t Update its location to obtain The new fitness level is evaluated.

[0094] After the initial search, the mutation and crossover strategies of the DE algorithm are used for optimization. The quality of the solutions after each mutation and crossover is evaluated, discarding solutions that do not meet the FMS operating constraints and voltage and current amplitude constraints, and penalizing solutions that do not meet the three-phase imbalance constraints. Based on the evaluation results after crossover and mutation, the individual X with the highest fitness is selected. best Extract its corresponding The fitness value of the objective function is updated as the final optimization result.

[0095] S4 verifies the effectiveness of the HOA-DE (Hike Differential Algorithm) for optimizing network loss in the system.

[0096] In this embodiment, the present invention optimizes the operation of a distribution network containing flexible multi-state switches by means of the proposed algorithm, with the main objectives of reducing system network losses and improving voltage distribution. The optimization includes:

[0097] A single-phase distribution network system with IEEE 33 nodes;

[0098] FMS is connected at different locations in a single-phase 33-node system, and the total network loss of the system is optimized using the proposed HOA-DE algorithm;

[0099] By comparing the optimized network loss results of distribution networks with flexible multi-state switches connected at different locations in a single-phase system, the differences in the network loss optimization effect of FMS of the same capacity are obtained.

[0100] By comparing the optimized voltage curves of distribution networks with flexible multi-state switches connected at different locations in a single-phase system, the differences in voltage drop mitigation capabilities of FMS of the same capacity can be obtained.

[0101] Furthermore, the single-phase system is extended to three-phase, and the FMS is connected in the three-phase 33-node distribution network;

[0102] Based on the mathematical model of flexible multi-state switch and the constraint on three-phase imbalance in the system, the proposed HOA-DE algorithm is used to optimize the network loss of the system.

[0103] The power quality management results before and after configuring FMS and before and after setting unbalance constraints are compared to verify the effect of FMS configuration on the comprehensive power quality management of three-phase unbalance.

[0104] Specifically, the multi-terminal flexible multi-state switch structure of the present invention is as follows: Figure 1 As shown, each end of the flexible multi-state switch (FMS) needs to have the function of transmitting active power flow and regulating power quality. It mainly consists of back-to-back voltage source converters connected to the power grid via feeders. This FMS achieves efficient power transmission through AC-DC and DC-AC conversion. The dual-terminal FMS uses PQ-VdcQ control mode during normal operation to regulate power transmission and maintain DC voltage; the multi-terminal FMS stabilizes AC voltage through VdcQ mode to ensure overall system stability.

[0105] Based on this, a mathematical model of the distribution network connected to the FMS is established, including:

[0106] Setting the objective function to minimize the total network loss, including line losses and FMS operating losses, can be expressed as:

[0107]

[0108] In the formula, Ω b It is the set of all nodes in the distribution network. Inject into node i The active power of the phase, Ω FMS A collection of FMS connected to the distribution network. For the k-th FMS on the j-th line Power loss inside the phase converter.

[0109] Constraining FMS operation to ensure that the active power injected into the associated feeders is balanced with the internal losses of its converter can be expressed as:

[0110]

[0111] In the formula, Inject the active power of the j-th branch into the k-th FMS.

[0112] Constraining the operation of the FMS, the active power injected into the j-th branch by the k-th FMS is... The existence of constraints can be represented as follows:

[0113]

[0114] In the formula, Inject reactive power from the j-th branch into the k-th FMS. This represents the converter loss factor.

[0115] Constrain FMS operation Upper and lower limit constraints can be expressed as:

[0116]

[0117] In the formula, The k-th FMS is located on the j-th branch. Phase converters allow for maximum and minimum reactive power values.

[0118] Constraining the operation of the FMS and limiting the apparent power of the converter can be expressed as:

[0119]

[0120] In the formula, For the k-th FMS on branch j The maximum apparent power that the phase converter is allowed to pass.

[0121] With constraints on the power flow balance of the system, the voltage drop equation for multiphase distribution lines can be expressed as:

[0122] ΔV i,j =Z·I

[0123] In the formula, ΔV i,j Let Z be the voltage drop matrix between nodes i and j, Z be the line impedance matrix, and I be the line current matrix. The expressions are as follows:

[0124]

[0125] In the formula, V i,a V i,b V i,c Z represents the three-phase complex voltage at node i, where a, b, and c are given. aa Z bb Z cc Z is the self-impedance in the line. ab Z bc Z ac For interphase mutual impedance, I a I b I c Let be the three-phase current vector between lines i and j.

[0126] With constraints on the power flow balance of the system, the power relationships in the lines can be expressed as:

[0127]

[0128] S ij =V i I ij (7)

[0129]

[0130] In the formula, S ij Z represents the complex power flowing from node i to node j. ij S represents the impedance on the line. j The injected power at node j, Ω REF As the reference node, where S ij S is calculated from the voltage at node i and the current at line (i,j). j It consists of distributed generation, multi-state switches, and line loads. Constraining the node voltages in the system, the voltage amplitude of each phase at each node can be expressed as:

[0131]

[0132] In the formula, These represent the upper and lower limits of the voltage amplitude at node i, respectively. This constraint applies to the set of all nodes except the reference node. The thermal limit constraint for branch currents in the line can be expressed as:

[0133]

[0134] In the formula, Let (i,j) be the maximum current in line (i,j). Constraints are applied to the three-phase imbalance of the power grid; the voltage imbalance constraint can be expressed as:

[0135]

[0136] In the formula, For node i Phase voltage unbalance parameters Let be the average of the squared values ​​of the voltage amplitude at node i. To constrain the three-phase imbalance of the power grid, the root node current imbalance constraint can be expressed as:

[0137]

[0138] In the formula, C I The root node three-phase current imbalance parameters are... This is the maximum value of the parameter. These are the positive and negative sequence current amplitudes at the root node in the system, calculated as follows:

[0139]

[0140] a = e j2π / 3 (16)

[0141] In the formula, These represent the phase currents of the root node (phases a, b, and c), respectively. The proposed differential algorithm for this invention optimizes distribution networks with flexible multi-state switches. The algorithm flow is as follows: Figure 2 As shown. Based on this, the main steps of the hiking difference algorithm include: generating a set of candidate solutions during the algorithm initialization phase, with the initial positions in the search space represented as follows:

[0142]

[0143] In the formula, Let be the initial position of the i-th candidate solution group. , , represent the upper and lower bounds of the decision variable, respectively, and μ is a random constant between [0,1].

[0144] In the HOA algorithm, terrain slope is represented as:

[0145]

[0146] In the formula, Let di be the terrain slope matrix for the i-th candidate solution in the t-th iteration, and let dh and dl represent the elevation difference and distance difference, respectively. The slope angle is the terrain inclination angle, which ranges from [0, 50°].

[0147] Walking speed based on Tobler's walking function Described as:

[0148]

[0149] In the HOA algorithm, the current speed of a hiker is represented as:

[0150]

[0151] In the formula, W i t W is the traveler's current speed. i t-1 The speed in the previous iteration, X is a constant uniformly distributed in the interval [0,1]. best To take the lead in position for hikers, This is the current location of the hiker. is the scan factor for hikers, and is a constant in the interval [1,3].

[0152] The particle position update in the algorithm is based on the population movement speed as follows:

[0153]

[0154] After initial searching using the HOA algorithm, further optimization is performed using the mutation and crossover strategies of the DE algorithm. The relevant formulas are as follows:

[0155] N i =X best +F·(X r1 -X r2 ); (twenty two)

[0156] In the formula, N i It is a mutation vector, X best It is the optimal solution vector, X r1 X r2 They are two random individuals in the population, and F is the variation factor used to control the magnitude of variation.

[0157] The crossover formula is used to combine the mutation vector with the current individual to generate new candidate solutions.

[0158]

[0159] In the formula, m i,j Let n be the j-th decision variable in the cross vector. i,j x is the j-th decision variable in the mutation vector. i,j R is the j-th decision variable in the current candidate solution. j It is a random number uniformly distributed in the interval [0,1], where c is the crossover probability and J is the crossover probability. R The dimension is randomly selected to ensure that at least one component is obtained from the mutation vector.

[0160] This invention uses the HOA-DE algorithm in MATLAB to verify the effect of FMS in reducing network losses in power systems. The FMS connection location is as follows: Figure 3 As shown.

[0161] Set up an IEEE 33-node system, with FMS connected to nodes 12-22, 18-33, and 9-15 respectively, each with a capacity of 500kW.

[0162] Based on this, the control effects of FMS at different nodes are compared.

[0163] Without FMS, the system network loss is 204kW. When FMS is connected to nodes 12-22, the network loss is 119.15kW. When connected to nodes 18-33, the network loss is 120.73kW. When connected to nodes 9-15, the network loss is 139.5kW. It can be seen that the effect of FMS on the management of system network loss varies depending on its location in the distribution network.

[0164] This invention uses the HOA-DE algorithm in MATLAB to verify the effect of FMS in reducing network losses in power systems. The voltage curves of FMS connected at different locations in the distribution network are shown below. Figure 4 As shown.

[0165] It can be seen that the proposed algorithm has a significant optimization effect in this example. The connection of FMS has a certain improvement on the voltage level in the distribution network. Compared with the case without FMS, the overall system voltage level is higher, and the voltage level improvement effect of FMS of the same capacity varies slightly.

[0166] This invention extends a single-phase 33-node distribution network into a three-phase model and verifies the effectiveness of FMS in managing three-phase imbalance in the power system. The FMS connection locations are as follows: Figure 5 As shown.

[0167] The 33-node distribution network was expanded into a three-phase model, with a three-phase load set at each node. To simulate the impact of distributed generation on the operation of the distribution network, single-phase photovoltaic systems were connected to nodes 4, 19, and 26, with a capacity of 150kW for each system, and an FMS capacity of 500kVA was set.

[0168] Based on this, this study sets up the following scenario:

[0169] Case 1: No FMS configured, no three-phase unbalance constraints set;

[0170] Case 2: Configure FMS without setting three-phase unbalance constraints;

[0171] Case 3: Configure FMS to constrain the three-phase voltage and current imbalance.

[0172] This invention addresses three scenarios and employs the HOA-DE algorithm to optimize the network by minimizing the total network loss, taking into account line losses and FMS operating losses. The optimization results are as follows: Figure 6 As shown.

[0173] Based on this, it can be seen that the HOA-DE algorithm has a significant effect on optimizing the three-phase unbalanced operation of power distribution networks with FMS configured. Compared with a three-phase unbalanced system without FMS, the three-phase voltage level of the system is significantly improved after configuring FMS; Figure 6 (b) and Figure 6 In (c), after the three-phase imbalance constraint is applied, the three-phase imbalance level of Case 3 is significantly reduced.

[0174] Under the three scenarios, the total system losses are 228.61kW, 214.93kW, and 224.87kW, respectively. This shows that in a three-phase network, the FMS still has a reducing effect on network losses. When considering the three-phase imbalance constraint, the optimization effect of the FMS on network losses is somewhat weakened, but the network loss is still lower than [previous scenario]. Figure 6 The loss under (a)Case 1 shows that in a distribution network connected to a distributed power source, the configuration of the FMS has a significant effect on the comprehensive power quality management of three-phase imbalance.

[0175] This invention proposes and verifies an optimization algorithm combining HOA (Hyper-Hyper-Availability) and DE (Digital-Equivalent) and applies it to the optimization control of Flexible Multi-State Switches (FMS) in distribution networks. First, the architecture of the FMS is analyzed, and an optimization model is established considering the three-phase imbalance constraints of the system operation. Then, the HOA-DE algorithm is proposed, and simulation experiments are conducted in a single-phase 33-node system to verify the optimization effect of connecting FMS at different locations in the distribution network on the system's power quality. Based on this, the single-phase model is extended to three-phase, verifying the effect of FMS connection in reducing system network losses, improving three-phase imbalance, and increasing voltage levels when considering three-phase imbalance constraints. This provides theoretical support for the application of flexible multi-state switches in practical power systems and demonstrates the significant value of FMS in improving the power quality and system reliability of distribution networks.

[0176] On the other hand, the present invention also provides a power quality management device for distribution networks based on a flexible multi-state switch, comprising:

[0177] A configuration module is used to install the flexible multi-state switch (FMS) on nodes in a power system according to actual needs, wherein the power system is a single-phase and / or three-phase unbalanced distribution network.

[0178] The model building module is used to establish a mathematical model of the distribution network connected to the FMS based on the actual operating data of the three-phase unbalanced power system. The mathematical model of the distribution network connected to the FMS includes an objective function, which is based on minimizing the total network loss including line losses and FMS operating losses, and determines the control strategy and operating mode of the flexible multi-state switch FMS.

[0179] The optimization module is used to optimize the system network loss, which takes into account line loss and FMS operation loss, using the hiking differential algorithm HOA-DE. The hiking differential algorithm is to perform an initial search using the hiking optimization algorithm HOA, and then optimize using the mutation and crossover strategies of the differential evolution algorithm DE.

[0180] The verification module is used to verify the effectiveness of the HOA-DE (Hike-Ahead Differential) algorithm in optimizing network loss in the system.

[0181] Other technical features of the power quality management device for distribution networks based on flexible multi-state switches of the present invention are similar to those of the corresponding power quality management method for distribution networks based on flexible multi-state switches, and will not be repeated here.

[0182] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0183] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0184] Obviously, those skilled in the art can make various modifications and variations to the embodiments of the present invention without departing from the spirit and scope of the embodiments of the present invention. Therefore, if these modifications and variations to the embodiments of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention also intends to include these modifications and variations.

Claims

1. A power quality management method for distribution networks based on flexible multi-state switches, characterized in that, The method includes: Flexible multi-state switch (FMS) is installed on nodes in a power system, which is a three-phase unbalanced distribution network, according to actual needs. Based on the actual operating data of the three-phase unbalanced distribution network, a mathematical model of the distribution network connected to the FMS is established. The mathematical model of the distribution network connected to the FMS includes an objective function. The objective function is based on minimizing the total network loss including line losses and FMS operating losses, and the control strategy and operation mode of the flexible multi-state switch FMS are determined. Based on the mathematical model of the distribution network connected to the FMS and the control strategy and operation mode of the flexible multi-state switch FMS, the operation balance constraints of the FMS, the power flow balance constraints of the distribution network, the voltage and current amplitude and the three-phase imbalance constraints of the system are determined in the distribution network containing the flexible multi-state switch. The HOA-DE differential algorithm is adopted, based on the control strategy and operation mode of the flexible multi-state switch (FMS), and considering the constraints in the distribution network containing the FMS, to optimize the system network loss including line losses and FMS operation losses. The HOA-DE algorithm is used to perform a preliminary search using the HOA algorithm, and then to optimize using the mutation and crossover strategies of the DE differential evolution algorithm. Verify the effectiveness of the HOA-DE (Hike Differential Algorithm-DE) for optimizing network loss in the system. The method of using the HOA-DE (Hike Differential Algorithm-DE) to optimize system network losses, taking into account line losses and FMS (Fulfilled Management System) operating losses, includes: The hiker is initialized, generating a set of initial candidate solutions based on the active and reactive power of the FMS. As a hiking population X i ;in, Inject the active power of the j-th branch into the k-th FMS. Inject reactive power from the j-th branch into the k-th FMS; Write relevant internal loss parameters of the FMS converter, and write constraints on node voltage amplitude, three-phase voltage imbalance, and root node current imbalance based on the operating characteristics of FMS. The fitness value F(x) is calculated with the system network loss f, which includes line loss and FMS operation loss, as the optimization objective. Calculate the hiker's speed W using the Tobler hiking function. i t And based on the hiker Current speed W i t Update its location to obtain And evaluate the new fitness; After the initial search, the mutation and crossover strategies of the DE algorithm are used for optimization, and the quality of the solution after each mutation and crossover is evaluated. Solutions that do not meet the FMS running balance constraints and voltage and current amplitude constraints are discarded, and solutions that do not meet the three-phase imbalance constraints are penalized. Based on the evaluation results after crossover mutation, select the individual X with the highest fitness. best Extract its corresponding The fitness value of the objective function is updated as the final optimization result.

2. The power quality management method for distribution networks based on flexible multi-state switches according to claim 1, characterized in that, The objective function of the HOA-DE algorithm is to minimize the system network loss, taking into account line loss and FMS operation loss. The objective function is expressed as: Among them, Ω b Let be the set of all nodes in the power system. Inject into node i The active power of the phase, It is a set of three phases, namely phase a, phase b, and phase c, Ω FMS A collection of FMS connected to the power system. For the k-th FMS on the j-th line Power loss inside the phase converter.

3. The power quality management method for distribution networks based on flexible multi-state switches according to claim 2, characterized in that, The determination of the control strategy and operating mode of the flexible multi-state switch (FMS) includes: Based on the balance between the active power injected into the associated feeder by the FMS and the internal losses of the converter composed of the flexible multi-state switch, an operational balance constraint for the FMS is established. Based on the principle that the active and reactive power of each node in the power system remains balanced during stable operation, a power flow balance constraint is established. Constrain the magnitudes of node voltage and current; The voltage imbalance in the system is defined by the ratio of the deviation of the square of the three-phase voltage amplitude to the square of the average voltage amplitude, and the three-phase voltage imbalance is constrained. The root node current imbalance is defined by the ratio of the negative sequence current amplitude to the positive sequence current amplitude, and constraints on the three-phase current imbalance at the root node are established.

4. The power quality management method for distribution networks based on flexible multi-state switches according to claim 3, characterized in that, The operational balance constraints of the FMS are expressed as follows: in, Inject the active power of the j-th branch into the k-th FMS; The active power injected into the j-th branch by the k-th FMS is... There are constraints, expressed as follows: in, Inject reactive power from the j-th branch into the k-th FMS. The converter loss coefficient; Constrain FMS operation Upper and lower limit constraints are represented as follows: In the formula, The k-th FMS is on the j-th branch. Phase converters allow for the maximum and minimum values ​​of reactive power.

5. The power quality management method for distribution networks based on flexible multi-state switches according to claim 2, characterized in that, The power flow balance constraint of the distribution network is expressed as follows: S ij =V i I ij ; (6) In the formula, I ij V represents the current flowing from node i to node j. i Let S be the voltage at node i. ij Z represents the complex power flowing from node i to node j. ij S represents the impedance on the line. j The injected power at node j, Ω REF As the reference node, S ij S is calculated from the voltage at node i and the current in line ij. j The distributed generation power S of node j j,DG The multi-state switching power S of node j j,FMS and the line load power S at node j j,L composition.

6. The power quality management method for distribution networks based on flexible multi-state switches according to claim 5, characterized in that, The constraints on the node voltage and current amplitudes include: The node voltages in the system are constrained, and the voltage amplitude of each phase at each node is expressed as follows: In the formula, These are the upper and lower limits of the voltage amplitude at node i, respectively. This constraint applies to the set of all nodes except the reference node. The constraint on the branch current in the line is expressed as: In the formula, This represents the maximum current value of line ij.

7. The power quality management method for distribution networks based on flexible multi-state switches according to claim 6, characterized in that, The constraint on the three-phase voltage imbalance includes: In the formula, For node i in Phase voltage unbalance parameters It is the average of the squared voltage magnitude of node i.

8. The power quality management method for distribution networks based on flexible multi-state switches according to claim 7, characterized in that, The establishment of constraints on the three-phase current imbalance at the root node includes: Among them, C I The root node three-phase current unbalance parameter. This is the maximum value of the parameter. These are the positive and negative sequence current amplitudes at the root node in the system, calculated as follows: a=e j2π / 3 ; (15) In the formula, These are the phase currents at the root node, a, b, and c, respectively.

9. A power quality management device for distribution networks based on a flexible multi-state switch, characterized in that, include: A configuration module is used to install the flexible multi-state switch (FMS) on nodes in a power system, which is a three-phase unbalanced distribution network, according to actual needs. The model building module is used to establish a mathematical model of the distribution network connected to the FMS based on the actual operating data of the three-phase unbalanced distribution network. The mathematical model of the distribution network connected to the FMS includes an objective function. The objective function takes the minimum total network loss, including line loss and FMS operating loss, as the benchmark, and determines the control strategy and operation mode of the flexible multi-state switch FMS. The optimization module is used to optimize the system network loss, which takes into account line loss and FMS operation loss, using the hiking differential algorithm HOA-DE. The hiking differential algorithm is to perform an initial search using the hiking optimization algorithm HOA, and then optimize using the mutation and crossover strategies of the differential evolution algorithm DE. The verification module is used to verify the effectiveness of the HOA-DE algorithm in optimizing network loss in the system. The method of using the HOA-DE (Hike Differential Algorithm-DE) to optimize system network losses, taking into account line losses and FMS (Fulfilled Management System) operating losses, includes: The hiker is initialized, generating a set of initial candidate solutions based on the active and reactive power of the FMS. As a hiking population X i ;in, Inject the active power of the j-th branch into the k-th FMS. Inject reactive power from the j-th branch into the k-th FMS; Write relevant internal loss parameters of the FMS converter, and write constraints on node voltage amplitude, three-phase voltage imbalance, and root node current imbalance based on the operating characteristics of FMS. The fitness value F(x) is calculated with the system network loss f, which includes line loss and FMS operation loss, as the optimization objective. Calculate the hiker's speed W using the Tobler hiking function. i t And based on the hiker Current speed W i t Update its location to obtain And evaluate the new fitness; After the initial search, the mutation and crossover strategies of the DE algorithm are used for optimization, and the quality of the solution after each mutation and crossover is evaluated. Solutions that do not meet the FMS running balance constraints and voltage and current amplitude constraints are discarded, and solutions that do not meet the three-phase imbalance constraints are penalized. Based on the evaluation results after crossover mutation, select the individual X with the highest fitness. best Extract its corresponding The fitness value of the objective function is updated as the final optimization result.

Images