Topology design method and system for multi-port flexible interconnection system

Abstract

The invention discloses a topological design method and system for a multi-port flexible interconnection system, and relates to the technical field of power systems, and the method comprises the steps: designing a topological structure based on a power distribution network demand objective function and constraint conditions; based on the topological structure, a model is constructed for simulation verification, and a simulation verification result is obtained; and optimizing the topological structure based on a simulation verification result. According to the topology design method of the multi-port flexible interconnection system, the multi-port flexible interconnection system technology is introduced, the particle swarm optimization algorithm and the analytic hierarchy process are combined, and systematic optimization design of equipment layout and a topology connection mode is achieved. Compared with a traditional method, the dynamic adaptive capacity and the system stability of the power distribution network are improved, different load changes and fault conditions can be effectively handled, and the recovery time after system faults is shortened. Meanwhile, the optimized scheme has better performance in the aspects of cost effectiveness, flexibility and the like, and the reliability and effectiveness of the design scheme in actual operation are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a topology design method and system for a multi-port flexible interconnection system. Background Art

[0002] In modern power systems, the stability and reliability of distribution networks are crucial to ensuring power supply. With the access of new energy sources, the continuous changes in loads, and the increasing requirements of power users for power supply reliability, the traditional distribution network topology faces many challenges. Traditional distribution network designs usually adopt fixed topologies such as star, ring or mesh structures, but these topologies have limitations in dealing with dynamic load changes, fault recovery, and grid expansion.

[0003] Existing distribution network design methods often ignore the multi-port flexible interconnection capabilities within the power grid, making it difficult to achieve flexible power dispatching and management without sacrificing system stability. In addition, traditional design methods usually rely on engineering experience in equipment layout and connection methods, lacking systematic optimization and decision analysis, resulting in poor performance in complex power grid environments and difficulty in effectively responding to the diverse needs and extreme operating conditions of the power system. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problems solved by the present invention are: the existing distribution network topology design methods have the problems of insufficient flexibility and poor system stability, and how to optimize the equipment layout and topology connection in a dynamic power system.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a topology design method for a multi-port flexible interconnection system, comprising:

[0007] Design the topology structure based on the distribution network demand objective function and constraints;

[0008] Based on the topological structure, a model is constructed for simulation verification to obtain simulation verification results;

[0009] The topology structure is optimized based on the simulation verification results.

[0010] As a preferred solution of the topology design method of the multi-port flexible interconnection system described in the present invention, wherein: the objective function is expressed as,

[0011] R eff (t) = R01 + αT(t) - T ref

[0012]

[0013] P ls (t) = I adj (t) 2 ·R eff (t)

[0014]

[0015] Q ls (t) = I adj (t) 2 ·X eff (t)

[0016]

[0017] S stab (t) = γ V V stab (t)+γ F F stab (t)

[0018]

[0019] Where R0 is the reference resistance, which refers to the resistance value of the circuit under standard conditions, α is the temperature coefficient, which indicates how the resistance changes with temperature, T(t) is the actual temperature at time t, and T ref It represents the reference temperature, which is usually the reference ambient temperature for resistance measurement. I(t) represents the measured current at time t. κ represents the adjustment coefficient, which characterizes the sensitivity of the load change to the current. ΔP load (t) represents the load power change at time t, P base represents the reference power, which is used to normalize the power change. X0 represents the reference inductive reactance, which refers to the inductive reactance value of the line under standard conditions. μ represents the frequency change coefficient, which indicates how the inductive reactance responds to the change of the system frequency. Δf(t) represents the frequency change at time t. nom represents the nominal frequency, i.e., the standard operating frequency of the system design, V(t) represents the voltage value at time t, V nom Indicates the nominal voltage, that is, the standard voltage designed for the system, V range Indicates the fluctuation range allowed for voltage stability, f range Indicates the fluctuation range allowed for frequency stability, γ V and γ F denote the weight factors of voltage and frequency stability, respectively; γ1, γ2, and γ3 denote the weight factors of active power loss, reactive power loss, and system stability in the objective function, respectively.

[0020] As a preferred solution of the topology design method of the multi-port flexible interconnection system described in the present invention, the constraint condition is expressed as:

[0021]

[0022] Where V(t) represents the voltage of the node at time t, V min (t),V max (t) represents the minimum and maximum voltage allowed at time t, I(t) represents the current of the line at time t, and I max represents the maximum carrying current of the line, f(t) represents the frequency of the system at time t, and f min (t),f max (t) represents the minimum and maximum frequencies allowed at time t, P k (t) represents the power output of device k at time t, Denotes the minimum and maximum safe operating power of device k.

[0023] As a preferred solution of the topology design method of the multi-port flexible interconnection system described in the present invention, wherein: the design of the topology structure includes selecting devices according to the objective function and the constraint conditions, and determining the device layout and the topological connection mode;

[0024] The devices include intelligent soft switches, transformers, reactors, capacitors and FACTS devices.

[0025] As a preferred scheme of the topology design method of the multi-port flexible interconnection system described in the present invention, wherein: the determination of the equipment layout and the topological connection method includes using a power system simulation tool, initializing the project and setting the basic parameters of the power grid, and importing data to establish a power grid model; the data includes load data, power generation capacity data and equipment performance parameters; when the data import is completed, the key nodes of the power grid are defined in the simulation software, the key nodes include power generation source nodes, load centers and regulation nodes, and the equipment is arranged on the key nodes to form a preliminary topological structure.

[0026] As a preferred solution of the topology design method of the multi-port flexible interconnection system described in the present invention, the objective function and the constraint conditions are input into the simulation software, a group of particle groups are initialized by the particle swarm optimization algorithm, each particle represents a possible device layout scheme, the particle moves in the search space, and continuously adjusts its position according to its own and the group's best position to find the optimal device configuration, the simulation software iteratively evaluates the performance of the layout scheme corresponding to each particle, gradually optimizes the value of the objective function, and when the algorithm converges, outputs the optimal position and quantity configuration scheme of the device to determine the optimal layout scheme;

[0027] When the equipment layout optimization is completed, the analytic hierarchy process (AHP) is used to perform multi-criteria decision analysis to determine the optimal power grid topology and set evaluation criteria, which include system reliability, cost-effectiveness, flexibility and stability, and assign weights to each criterion; the performance indicators of the ring network, star network and mesh structure are input into the AHP model, and the relative importance of the indicators is analyzed layer by layer by constructing a judgment matrix; AHP calculates the priority score of each topology relative to each evaluation criterion, and combines the performance data provided by the simulation software. The AHP method finally obtains the comprehensive priority of each topology, and selects the topology with the highest priority based on the comprehensive score.

[0028] As a preferred scheme of the topology design method of the multi-port flexible interconnection system described in the present invention, wherein: after completing the equipment layout and topology design, simulation verification is performed, and different operation scenarios are set, including normal operation, fault conditions, load peaks and valleys. After running the simulation, key performance indicators of the system are collected, and the key performance indicators include voltage, current and power loss; the simulation results are compared with the design goals to evaluate whether the expected effect has been achieved. If the simulation results show that some performance indicators are not up to standard, the equipment configuration, layout location or connection method is adjusted, and simulation verification is performed again until the performance indicators of the system meet the design goal requirements.

[0029] Another object of the present invention is to provide a topology design system for a multi-port flexible interconnection system, which can solve the problems of unreasonable equipment configuration, rigid topology structure and difficulty in dynamic adjustment in the existing distribution network design by constructing a multi-port flexible interconnection system.

[0030] To solve the above technical problems, the present invention provides the following technical solutions: A topology design system for a multi-port flexible interconnection system, comprising: a demand analysis model, a topology design module, a simulation test model, and an optimization feedback model;

[0031] The demand analysis model is used to determine the distribution network demand objective function and constraint conditions;

[0032] The topology design module is used to design a topology structure;

[0033] The simulation test model is used to construct a model for simulation verification;

[0034] The optimization feedback model is used to optimize the topology structure based on the simulation verification results.

[0035] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned topology design method for a multi-port flexible interconnection system when executing the computer program.

[0036] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the topology design method for a multi-port flexible interconnection system as described above.

[0037] Beneficial effects of the present invention: The topology design method of the multi-port flexible interconnection system provided by the present invention realizes the systematic optimization design of equipment layout and topological connection mode by introducing the multi-port flexible interconnection system technology, combining the particle swarm optimization algorithm and the hierarchical analysis method. Compared with the traditional method, it improves the dynamic adaptability and system stability of the distribution network, can effectively cope with different load changes and fault conditions, and reduce the recovery time after system failure. At the same time, the optimized scheme performs better in terms of cost-effectiveness, flexibility, etc., ensuring the reliability and effectiveness of the design scheme in actual operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0039] Figure 1 An overall flow chart of a topology design method for a multi-port flexible interconnection system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0041] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0042] Example 1, reference Figure 1 , as an embodiment of the present invention, provides a topology design method for a multi-port flexible interconnection system, comprising:

[0043] Design the topology structure based on the distribution network demand objective function and constraints;

[0044] Based on the topological structure, a model is constructed for simulation verification to obtain simulation verification results;

[0045] The topology structure is optimized based on the simulation verification results.

[0046] The objective function is expressed as,

[0047] R eff (t) = R01 + αT(t) - T ref

[0048]

[0049] P ls (t) = I adj (t) 2 ·R eff (t)

[0050]

[0051] Q ls (t) = I adj (t) 2 ·X eff (t)

[0052]

[0053] S stab (t) = γ V V stab (t)+γ F F stab (t)

[0054]

[0055] Where R0 is the reference resistance, which refers to the resistance value of the circuit under standard conditions, α is the temperature coefficient, which indicates how the resistance changes with temperature, T(t) is the actual temperature at time t, and T ref It represents the reference temperature, which is usually the reference ambient temperature for resistance measurement. I(t) represents the measured current at time t. κ represents the adjustment coefficient, which characterizes the sensitivity of the load change to the current. ΔP load (t) represents the load power change at time t, P base represents the reference power, which is used to normalize the power change. X0 represents the reference inductive reactance, which refers to the inductive reactance value of the line under standard conditions. μ represents the frequency change coefficient, which indicates how the inductive reactance responds to the change of the system frequency. Δf(t) represents the frequency change at time t. nom represents the nominal frequency, i.e., the standard operating frequency of the system design, V(t) represents the voltage value at time t, V nom Indicates the nominal voltage, that is, the standard voltage designed for the system, V rangeIndicates the fluctuation range allowed for voltage stability, f range Indicates the fluctuation range allowed for frequency stability, γ V and γ F denote the weight factors of voltage and frequency stability, respectively; γ1, γ2, and γ3 denote the weight factors of active power loss, reactive power loss, and system stability in the objective function, respectively.

[0056] The constraint condition is expressed as,

[0057]

[0058] Where V(t) represents the voltage of the node at time t, V min (t),V max (t) represents the minimum and maximum voltage allowed at time t, I(t) represents the current of the line at time t, and I max represents the maximum carrying current of the line, f(t) represents the frequency of the system at time t, and f min (t),f max (t) represents the minimum and maximum frequencies allowed at time t, P k (t) represents the power output of device k at time t, Denotes the minimum and maximum safe operating power of device k.

[0059] The design of the topological structure includes selecting equipment according to the objective function and the constraint conditions, and determining the equipment layout and the topological connection mode;

[0060] The devices include intelligent soft switches, transformers, reactors, capacitors and FACTS devices.

[0061] The method of determining the equipment layout and topological connection method includes using a power system simulation tool to initialize the project and set the basic parameters of the power grid, and importing data to establish a power grid model; the data includes load data, power generation capacity data and equipment performance parameters; when the data is imported, the key nodes of the power grid are defined in the simulation software, and the key nodes include power generation source nodes, load centers and regulation nodes, and equipment is arranged on the key nodes to form a preliminary topological structure.

[0062] Input the objective function and constraints into the simulation software, and initialize a group of particle swarms through the particle swarm optimization algorithm. Each particle represents a possible device layout solution. The particle moves in the search space and continuously adjusts its position according to its own and the group's best position to find the optimal device configuration. The simulation software iteratively evaluates the performance of the layout solution corresponding to each particle and gradually optimizes the value of the objective function. When the algorithm converges, it outputs the optimal location and quantity configuration solution of the device and determines the optimal layout solution.

[0063] Initialize the particle population:

[0064] Particle representation: Each particle x i (t) represents a device layout scheme. The dimension of the particle corresponds to the layout parameters of various types of equipment (intelligent soft switches, transformers, reactors, capacitors, FACTS devices) in the power grid, including the location and quantity of each device.

[0065] Initialization of particle swarm: Assume that there are N particles, each of which represents a possible device layout. During initialization, the position and velocity of the particles are set according to the search space, and preliminary screening is performed based on the constraints. Initial position x i (0) and initial velocity v i (0) Randomly generated by the system or obtained through heuristic methods.

[0066] Objective function Fx i Calculation of (t):

[0067] The position x of each particle i (t) determines the configuration of the equipment in the power grid. Based on these configurations, the simulation software calculates the following:

[0068] Active power loss P ls (t): Based on the current I of the device adj (t) and resistance R eff (t) is calculated as follows:

[0069] P ls (t) = I adj (t) 2 ·R eff (t)

[0070] Reactive power loss Q ls (t): The current I adj (t) and inductive reactance X eff (t) is calculated as follows:

[0071] Q ls (t) = I adj (t) 2 ·X eff (t)

[0072] System stability stab (t): through voltage stability V stab (t) and frequency stability F stab The calculation of (t) yields:

[0073] S stab (t) = γ V V stab (t)+γ F Fstab (t)

[0074] Comprehensive objective function: objective function Fx i (t) Combining the above indicators to reflect the overall performance of the equipment layout plan:

[0075]

[0076] After each calculation of the objective function, check whether the layout solution satisfies all constraints:

[0077] V min (t)≤V(t)≤V max (t)

[0078] I(t)≤I max

[0079] f min (t)≤f(t)≤f max (t)

[0080]

[0081] If it is not satisfied, the objective function will be penalized, which will reduce the score of the layout solution or directly mark it as an infeasible solution.

[0082] The speed update formula is expressed as:

[0083]

[0084] Among them, v i (t+1) represents the velocity of particle i at time t+1, v i (t) represents the current speed of particle i at time t, ω represents the inertia weight, which controls the updating degree of particle speed and balances the ability of particle exploration and development. c1 represents the self-cognition factor, which is the attraction of the particle to its own optimal solution, and represents the individual's preference for its historical optimal position. c2 represents the social cognition factor, which is the attraction of the particle to the group's optimal solution, and represents the individual's preference for the group's optimal position. r1 and r2 represent random factors with values ​​between 0 and 1, which are used to increase the randomness of particle search and prevent falling into local optimality. The best historical position of particle i that has been searched so far, g best represents the global optimal position found by all particles in the group so far, λ represents the adjustment coefficient, which is used to balance the influence of the objective function gradient on the speed update. Denotes the objective function Fx i (t) for the particle position x i The gradient of (t) represents the sensitivity of the objective function to the change of the current particle position.

[0085] The position update formula is expressed as:

[0086] x i (t+1)=x i (t)+v i (t+1)

[0087] Among them, x i (t+1) represents the position of particle i at time t+1, indicating the new equipment layout plan.

[0088] In each iteration, according to the updated particle velocity v i (t+1) and position x i At (t+1), the simulation software re-evaluates the objective function and checks whether the constraints are met.

[0089] The global optimal position of the particle g best and the individual best position Continuously update to ensure that the algorithm converges towards the global optimal solution.

[0090] When the global optimal position of the particle g best When there is no significant change in multiple iterations, or the change in the objective function value is less than the set threshold, the algorithm is considered to have converged.

[0091] After convergence, the global optimal position g is output best The corresponding equipment layout plan includes the optimal location and quantity configuration of intelligent soft switches, transformers, reactors, capacitors and FACTS equipment.

[0092] The gradient of the objective function to the particle position is introduced into the velocity update formula of the particle swarm optimization algorithm (PSO). In the traditional PSO algorithm, the particle position update mainly depends on the inertia weight, the individual historical best position and the global optimal position (g best ). This method relies on the particle's history and group information to guide the search direction, thereby achieving global optimization. However, this method may fall into local optimality in some cases, or converge slowly in complex search spaces.

[0093] Introducing the gradient information of the objective function can provide particles with immediate feedback on the direction of the steepest descent of the objective function, making the movement of particles more targeted rather than relying solely on historical information.

[0094] The gradient represents the rate of change of the objective function at the current position, and it indicates in which direction the objective function value can be reduced most quickly. Introducing gradient information into the velocity update formula allows particles to move more accurately towards the optimal solution of the objective function when approaching local extreme points, thereby avoiding excessive ineffective exploration.

[0095] Traditional PSO algorithms may sometimes require more iterations to converge to the optimal solution, but the introduction of gradient information can accelerate this process. Because the gradient directly reflects the optimal direction of the current point, particles can move faster to the valley area of ​​the objective function, thereby shortening the optimization time.

[0096] Despite the introduction of gradient information, PSO still retains the inertia weight and information based on the historical optimal position of the group. This means that even in the early stages of global search, the algorithm still has the ability to explore the entire search space without falling into local optimality due to local gradient information.

[0097] When the equipment layout optimization is completed, the analytic hierarchy process (AHP) is used to perform multi-criteria decision analysis to determine the optimal power grid topology and set evaluation criteria, which include system reliability, cost-effectiveness, flexibility and stability, and assign weights to each criterion; the performance indicators of the ring network, star network and mesh structure are input into the AHP model, and the relative importance of the indicators is analyzed layer by layer by constructing a judgment matrix; AHP calculates the priority score of each topology relative to each evaluation criterion, and combines the performance data provided by the simulation software. The AHP method finally obtains the comprehensive priority of each topology, and selects the topology with the highest priority based on the comprehensive score.

[0098] System reliability sys Quantify the ability of the power grid to maintain power supply under fault conditions. Calculated by the mean time between failures (MTBF) and the mean time to repair failures (MTTR), expressed as:

[0099]

[0100] Cost-effectiveness eff Quantify the relationship between the total cost of grid construction and operation and its life cycle. total and system life cycle L sys Calculation, expressed as:

[0101]

[0102] Flexibility flex Quantify the ability of the power grid to cope with load changes and expansion requirements. Based on the ability to cope with load changes load and the scalability index E index Calculation, expressed as:

[0103]

[0104] Stability (S stab ) quantifies the ability of the power grid to maintain voltage and frequency stability under different operating conditions. The voltage fluctuation rate (V var ) and frequency volatility f var Calculation, expressed as:

[0105]

[0106] Weight calculation w i Using historical data and simulation results, the weight of each evaluation criterion is automatically calculated through regression analysis. The specific calculation formula is as follows:

[0107] w rel =α1·R sys +β1

[0108] w cost =α2·C eff +β2

[0109] w flex =α3·F flex +β3

[0110] w stab =α4·S stab +β4

[0111] Among them, α i and β i It is the coefficient obtained through regression analysis, which reflects the impact of each evaluation criterion on the overall performance of the system.

[0112] Construct an automated judgment matrix and input simulation data:

[0113] The simulation results of different topologies (ring, star, mesh) are input into the system. These simulation data contain the R sys , C eff 、F flex and S stab value.

[0114] Generate a standardized score P i Normalize the input simulation data and generate a standardized score P i The standardized scoring formula is:

[0115]

[0116] Among them, P i,kis the standardized score of topology i under evaluation criterion k, index i,k represents the original score of topology i under evaluation criterion k, and max index k It is the maximum value of all topological structures under evaluation criterion k.

[0117] Construct judgment matrix A k For each evaluation criterion k, construct the judgment matrix A k , where the matrix element a ij,k Calculated by the following formula:

[0118]

[0119] Among them, a ij,k is the relative importance of topology i relative to topology j under evaluation criterion k.

[0120] Eigenvector calculation w k By judging the matrix A k Perform eigenvalue decomposition and calculate the eigenvector w k , represents the weight under the evaluation criterion k:

[0121]

[0122] Eigenvector w k Represents the relative weight of each topological structure under the evaluation criterion k.

[0123] Layer-by-layer analysis and priority score calculation

[0124] Layer-by-layer analysis and scoring i Under each evaluation criterion k, the priority score p of each topology is calculated based on the standardized score and feature vector. i :

[0125]

[0126] Among them, p i represents the comprehensive score of topology i under all evaluation criteria, w k is the weight of each evaluation criterion.

[0127] Calculate the comprehensive priority score P tot Calculate the comprehensive priority score P of all evaluation criteria tot , the formula is as follows:

[0128]

[0129] w i =γ1·w rel +γ2·w cost +γ3·w flex +γ4·wstab

[0130] Among them, w i is the weight of the comprehensive evaluation criteria, based on the regression analysis results, p i is the comprehensive score of topology i.

[0131] After calculating the comprehensive priority score, the system automatically performs a consistency check to ensure the consistency of the judgment matrix. The formula for calculating the consistency ratio CR is:

[0132]

[0133] Among them, CI is the consistency index, which indicates the degree of deviation of the judgment matrix, and RI is the random consistency index related to the matrix order.

[0134] According to the comprehensive priority score P tot Automatically select the topology with the highest priority. Verify the performance of the selected topology through simulation software.

[0135] After completing the equipment layout and topology design, simulation verification is carried out, and different operating scenarios are set, including normal operation, fault conditions, load peaks and valleys. After running the simulation, the key performance indicators of the system are collected, and the key performance indicators include voltage, current and power loss; the simulation results are compared with the design goals to evaluate whether the expected effect has been achieved. If the simulation results show that some performance indicators are not up to standard, the equipment configuration, layout location or connection method is adjusted, and simulation verification is carried out again until the system performance indicators meet the design target requirements.

[0136] Embodiment 2 is an embodiment of the present invention, which provides a topology design system for a multi-port flexible interconnection system, including:

[0137] Demand analysis model, topology design module, simulation test model and optimization feedback model;

[0138] The demand analysis model is used to determine the distribution network demand objective function and constraint conditions;

[0139] The topology design module is used to design a topology structure;

[0140] The simulation test model is used to construct a model for simulation verification;

[0141] The optimization feedback model is used to optimize the topology structure based on the simulation verification results.

[0142] Embodiment 3, an embodiment of the present invention, is different from the first two embodiments in that:

[0143] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0144] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0145] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0146] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0147] Embodiment 4 is an embodiment of the present invention, which provides a topology design method for a multi-port flexible interconnection system. In order to verify the beneficial effects of the present invention, a scientific demonstration is carried out through simulation experiments.

[0148] The experiment adopts a distribution network model consisting of 10 load nodes, 2 generation nodes and 3 regulation nodes. The load nodes represent different user groups, the generation nodes simulate the access of renewable energy, and the regulation nodes are equipped with different types of power equipment.

[0149] The traditional method uses a fixed topology (star topology is used in the experiment) for equipment layout, which includes conventional transformers, switchgear and compensation capacitors.

[0150] The method of the present invention uses multi-port flexible interconnection system technology, and the equipment includes intelligent soft switches, adjustable reactors, capacitors and FACTS equipment. The equipment layout and topology are determined by optimization algorithm and multi-standard decision analysis.

[0151] Operation scenarios include normal operation, where the system runs under normal load conditions, to evaluate system stability and voltage regulation capabilities. Load fluctuations simulate changes in peak load and valley load to test the system's dynamic response capabilities. Fault conditions randomly set nodes or lines in the system to fail, to test the system's fault recovery capabilities and reliability.

[0152] Use power system simulation tools (such as PSS / E or DIgSILENT) to establish a distribution network model and configure various parameters in the experimental conditions.

[0153] Traditional approaches use fixed topologies to lay out equipment based on load and generation locations.

[0154] The method of the present invention uses a particle swarm optimization algorithm to determine the optimal layout and quantity configuration scheme of the equipment, adopts AHP to perform decision analysis of the topological structure, and finally determines the optimal topological structure.

[0155] Run simulation tools under normal operation, load fluctuations, and fault conditions to collect data on various performance indicators, including voltage stability, system losses, operating costs, and fault recovery time.

[0156] The simulation data of the traditional method and the method of the present invention under the same conditions are compared, and the difference in system performance between the two is analyzed through data analysis. The experimental results are shown in Table 1.

[0157] Table 1 Comparison of experimental results

[0158] Scenario index Traditional methods Method of the present invention Normal operation Voltage stability 0.85 0.95 Load fluctuation System loss 120kW 90kW Fault conditions Recovery time 3min 1min Life cycle cost Cost-effectiveness 1.5 million yuan 1.3 million yuan

[0159] The method of the present invention adopts intelligent soft switches and FACTS devices, which can quickly adjust the voltage of the system when load fluctuations or faults occur, and maintain a high voltage stability. Compared with the traditional method, the fixed topology structure cannot flexibly respond to voltage fluctuations, resulting in low voltage stability. Since the method of the present invention adopts the particle swarm optimization algorithm, the equipment layout and power flow distribution are more reasonable, reducing unnecessary power loss. However, the fixed equipment layout in the traditional method leads to insufficient optimization of power flow, which increases system losses. The multi-port flexible interconnection system of the method of the present invention can respond to faults quickly, reconfigure power flow through intelligent control devices, and significantly shorten the fault recovery time. The traditional method requires manual or preset rules to perform fault recovery, which is slow. Although the initial investment of the method of the present invention is high, the operation and maintenance costs of the system are significantly reduced by optimizing the equipment layout and reducing system losses. The traditional method has high long-term costs due to its fixedness and lack of optimization.

[0160] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A topology design method for a multi-port flexible interconnection system, characterized in that: include: Design the topology structure based on the distribution network demand objective function and constraints; Based on the topological structure, a model is constructed for simulation verification to obtain simulation verification results; The topology structure is optimized based on the simulation verification results.

2. The topology design method of a multi-port flexible interconnection system according to claim 1, characterized in that: The objective function is expressed as, R eff (t)=R0(1+α(T(t)-T ref )) P ls (t)=I adj (t) 2 ·R eff (t) Q ls (t)=I adj (t) 2 ·X eff (t) S stab (t)=γ V V stab (t)+γ F F stab (t) Where R0 is the reference resistance, which refers to the resistance value of the circuit under standard conditions, α is the temperature coefficient, which indicates how the resistance changes with temperature, T(t) is the actual temperature at time t, and T ref It represents the reference temperature, which is usually the reference ambient temperature for resistance measurement. I(t) represents the measured current at time t. κ represents the adjustment coefficient, which characterizes the sensitivity of the load change to the current. ΔP load (t) represents the load power change at time t, P base represents the reference power, which is used to normalize the power change. X0 represents the reference inductive reactance, which refers to the inductive reactance value of the line under standard conditions. μ represents the frequency change coefficient, which indicates how the inductive reactance responds to the change of the system frequency. Δf(t) represents the frequency change at time t. nom represents the nominal frequency, i.e., the standard operating frequency of the system design, V(t) represents the voltage value at time t, V nom Indicates the nominal voltage, that is, the standard voltage designed for the system, V range Indicates the fluctuation range allowed for voltage stability, f range Indicates the fluctuation range allowed for frequency stability, γ V and γ F denote the weight factors of voltage and frequency stability, respectively; γ1, γ2, and γ3 denote the weight factors of active power loss, reactive power loss, and system stability in the objective function, respectively.

3. The topology design method of a multi-port flexible interconnection system according to claim 2, characterized in that: The constraint condition is expressed as, V min (t)≤V(t)≤V max (t), I(t)≤I max , f min (t)≤f(t)≤f max (t), Where V(t) represents the voltage of the node at time t, V min (t),V max (t) represents the minimum and maximum voltage allowed at time t, I(t) represents the current of the line at time t, and I max represents the maximum carrying current of the line, f(t) represents the frequency of the system at time t, and f min (t),f max (t) represents the minimum and maximum frequencies allowed at time t, P k (t) represents the power output of device k at time t, Denotes the minimum and maximum safe operating power of device k.

4. The topology design method of a multi-port flexible interconnection system according to claim 3, characterized in that: The design of the topological structure includes selecting equipment according to the objective function and the constraint conditions, and determining the equipment layout and the topological connection mode; The devices include intelligent soft switches, transformers, reactors, capacitors and FACTS devices.

5. The topology design method of a multi-port flexible interconnection system according to claim 4, characterized in that: The method of determining the equipment layout and topological connection method includes using a power system simulation tool to initialize the project and set the basic parameters of the power grid, and importing data to establish a power grid model; the data includes load data, power generation capacity data and equipment performance parameters; when the data is imported, the key nodes of the power grid are defined in the simulation software, and the key nodes include power generation source nodes, load centers and regulation nodes, and equipment is arranged on the key nodes to form a preliminary topological structure.

6. The topology design method of a multi-port flexible interconnection system according to claim 5, characterized in that: Input the objective function and constraints into the simulation software, and initialize a group of particle swarms through the particle swarm optimization algorithm. Each particle represents a possible device layout solution. The particle moves in the search space and continuously adjusts its position according to its own and the group's best position to find the optimal device configuration. The simulation software iteratively evaluates the performance of the layout solution corresponding to each particle and gradually optimizes the value of the objective function. When the algorithm converges, it outputs the optimal location and quantity configuration solution of the device and determines the optimal layout solution. When the equipment layout optimization is completed, the analytic hierarchy process (AHP) is used to perform multi-criteria decision analysis to determine the optimal power grid topology, set evaluation criteria, including system reliability, cost-effectiveness, flexibility and stability, and assign weights to each criterion; input the performance indicators of the ring network, star network and mesh structure into the AHP model, and analyze the relative importance of the indicators layer by layer by constructing a judgment matrix; AHP calculates the priority score of each topology relative to each evaluation criterion. Combined with the performance data provided by the simulation software, the AHP method finally obtains the comprehensive priority of each topology. Based on the comprehensive score, the topology with the highest priority is selected.

7. The topology design method of a multi-port flexible interconnection system according to claim 6, characterized in that: After completing the equipment layout and topology design, simulation verification is carried out, and different operating scenarios are set, including normal operation, fault conditions, load peaks and valleys. After running the simulation, the key performance indicators of the system are collected, and the key performance indicators include voltage, current and power loss; the simulation results are compared with the design goals to evaluate whether the expected effect has been achieved. If the simulation results show that some performance indicators are not up to standard, the equipment configuration, layout location or connection method is adjusted, and simulation verification is carried out again until the system performance indicators meet the design target requirements.

8. A system using the topology design method of a multi-port flexible interconnection system as claimed in any one of claims 1 to 7, characterized in that: include: Demand analysis model, topology design module, simulation test model and optimization feedback model; The demand analysis model is used to determine the distribution network demand objective function and constraint conditions; The topology design module is used to design a topology structure; The simulation test model is used to construct a model for simulation verification; The optimization feedback model is used to optimize the topology structure based on the simulation verification results.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for topology design of a multi-port flexible interconnection system according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for topology design of a multi-port flexible interconnection system according to any one of claims 1 to 7 are implemented.

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