UPFC configuration optimization method and system

Abstract

The application discloses a UPFC configuration optimization method and system, wherein the method comprises the following steps: analyzing the obtained topological structure information and operation parameters of a target power system to construct a key channel line set; simulating the power grid power flow distribution of the target power system after a UPFC is configured to access different key channel lines, and calculating the load rate of the key channel lines based on the simulation result of the power grid power flow distribution; taking the key channel line with the minimum weighted power flow entropy as the optimal access line of the UPFC to be configured according to the calculation of the load rate; performing power flow calculation on the power grid operation state of the target power system under a preset fault scenario, and calculating the power transfer support strength of the key channel lines according to the result of the power flow calculation; and establishing a UPFC grid-connected capacity optimization model, performing calculation on the UPFC grid-connected capacity optimization model, and obtaining the optimal capacity of the UPFC to be configured. The method provided by the application can be widely used for optimizing the power flow distribution of a regional power grid.

Description

Technical Field

[0001] This application relates to the field of power transmission technology, and in particular to a UPFC configuration optimization method and system. Background Technology

[0002] With the increasing development of power system loads and grid structures, uneven power supply in transmission lines can easily lead to transmission congestion on some lines while the transmission capacity of other lines remains underutilized, resulting in wasted investment. The Unified Power Flow Controller (UFPC), as a representative of advanced third-generation Flexible AC Transmission Systems (FACTS), plays a crucial role in system power flow control and voltage stability by controlling factors such as bus voltage, line impedance, and active and reactive power within the system.

[0003] However, existing methods for the location and capacity determination of UPFCs often lack a systematic approach and fail to comprehensively consider the overall structure and operating characteristics of the power system. This may lead to unreasonable UPFC configuration locations and capacity mismatches, thus failing to fully realize their control effects. Summary of the Invention

[0004] This application provides a UPFC configuration optimization method and system to solve the technical problem of how to optimize the power flow distribution of a regional power grid.

[0005] To address the aforementioned technical problems, embodiments of this application provide a UPFC configuration optimization method, including:

[0006] The topology information and operating parameters of the target power system are analyzed, and a set of key channel lines is constructed based on the analysis results.

[0007] Initialize the capacity of the UPFC to be configured, simulate the power flow distribution of the power grid after the UPFC to be configured is connected to different key channel lines in the key channel line set, and calculate the load rate of the key channel line based on the simulation results of the power flow distribution.

[0008] Calculate the weighted power flow entropy based on the load rate, and select the critical channel line with the smallest weighted power flow entropy as the optimal access line for the UPFC to be configured.

[0009] Power flow calculation is performed on the power grid operation status of the target power system under a preset fault scenario, and the power transfer support strength of the key channel line is calculated based on the result of the power flow calculation.

[0010] Based on the optimal access line and the power transfer support strength, a UPFC grid-connected capacity optimization model is established. The UPFC grid-connected capacity optimization model is calculated according to the improved particle swarm optimization algorithm to obtain the optimal capacity of the UPFC to be configured, so as to optimize the configuration of the UPFC to be configured.

[0011] As one preferred embodiment, the step of simulating the power flow distribution of the grid after the UPFC is connected to different critical channel lines in the critical channel line set, using the capacity of the UPFC to be configured as the compensation value, and calculating the load rate of the critical channel lines based on the simulation results of the power flow distribution, includes:

[0012] Establish a power grid model for the target power system;

[0013] Using the capacity of the UPFC to be configured as the compensation value, determine the compensation strategy of the UPFC to be configured in different critical channel lines;

[0014] According to the compensation strategy, the UPFC to be configured is connected to the power grid model, and the power flow distribution of the power grid model after the UPFC to be configured is connected to the power grid model is simulated based on the power flow calculation method.

[0015] The load rate of the critical channel line is calculated based on the power flow distribution.

[0016] As one preferred embodiment, the calculation of the weighted power flow entropy based on the load rate includes:

[0017] according to The load factor is differentiated, with each interval having a length of [length missing]. The load rate is expressed as:

[0018] ,

[0019] in, For load rate, For the line Maximum conveying capacity For the actual running current, This represents the total number of transmission lines in the power system.

[0020] interval The proportion of line load rate within Defined as:

[0021] ,

[0022] in, For interval The total number of lines within;

[0023] The weighted power flow entropy is calculated and expressed as:

[0024] ,

[0025] in, For weighted power flow entropy, For interval The average line load rate within the area.

[0026] As one preferred embodiment, the power transfer support strength is expressed as:

[0027] ,

[0028] in, For the transmission power of the critical channel after a failure, The initial power for the critical channel; To provide emergency power support for the regional power grid.

[0029] As one preferred embodiment, the step of calculating the optimal configuration capacity of the UPFC based on the improved particle swarm optimization algorithm to obtain the grid-connected capacity optimization model of the UPFC to be configured includes:

[0030] The capacity value of the UPFC to be configured is randomly initialized as a particle, and the particle represents a UPFC configuration scheme;

[0031] Calculate the fitness value of each particle, and iteratively update the particles based on the fitness value and a nonlinear decreasing inertia weight.

[0032] When the result of the iterative update meets the preset convergence condition, the current result is output as the optimal configuration capacity of the UPFC to be configured.

[0033] Another embodiment of this application provides a park energy consumption decision optimization system, including:

[0034] The analysis module is used to analyze the topology information and operating parameters of the target power system and construct a set of key channel lines based on the analysis results.

[0035] The simulation module is used to initialize the capacity of the UPFC to be configured, simulate the power flow distribution of the power grid after the UPFC to be configured is connected to different key channel lines in the key channel line set, and calculate the load rate of the key channel line based on the simulation results of the power flow distribution.

[0036] The configuration module is used to calculate the weighted power flow entropy based on the load rate, and to select the key channel line with the smallest weighted power flow entropy as the optimal access line of the UPFC to be configured.

[0037] The calculation module is used to perform power flow calculation on the power grid operation status of the target power system under a preset fault scenario, and to calculate the power transfer support strength of the key channel line based on the result of the power flow calculation.

[0038] The optimization module is used to establish a UPFC grid-connected capacity optimization model based on the optimal access line and the power transfer support strength, and to calculate the optimal capacity of the UPFC to be configured by calculating the UPFC grid-connected capacity optimization model according to the improved particle swarm optimization algorithm, so as to optimize the configuration of the UPFC to be configured.

[0039] As one preferred embodiment, the simulation module is specifically used for:

[0040] Establish a power grid model for the target power system;

[0041] Using the capacity of the UPFC to be configured as the compensation value, determine the compensation strategy of the UPFC to be configured in different critical channel lines;

[0042] According to the compensation strategy, the UPFC to be configured is connected to the power grid model, and the power flow distribution of the power grid model after the UPFC to be configured is connected to the power grid model is simulated based on the power flow calculation method.

[0043] The load rate of the critical channel line is calculated based on the power flow distribution.

[0044] As one preferred embodiment, the configuration module is further configured to:

[0045] according to The load factor is differentiated, with each interval having a length of [length missing]. The load rate is expressed as:

[0046] ,

[0047] in, For load rate, For the line Maximum conveying capacity For the actual running current, This represents the total number of transmission lines in the power system.

[0048] interval The proportion of line load rate within Defined as:

[0049] ,

[0050] in, For interval The total number of lines within;

[0051] The weighted power flow entropy is calculated and expressed as:

[0052] ,

[0053] in, For weighted power flow entropy, For interval The average line load rate within the area.

[0054] As one preferred embodiment, the power transfer support strength is expressed as:

[0055] ,

[0056] in, For the transmission power of the critical channel after a failure, The initial power for the critical channel; To provide emergency power support for the regional power grid.

[0057] As one preferred embodiment, the optimization module is specifically used for:

[0058] The capacity value of the UPFC to be configured is randomly initialized as a particle, and the particle represents a UPFC configuration scheme;

[0059] Calculate the fitness value of each particle, and iteratively update the particles based on the fitness value and a nonlinear decreasing inertia weight.

[0060] When the result of the iterative update meets the preset convergence condition, the current result is output as the optimal configuration capacity of the UPFC to be configured.

[0061] Another embodiment of this application provides a UPFC configuration optimization device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the UPFC configuration optimization method as described above.

[0062] In another embodiment of this application, a computer-readable storage medium is provided, which stores a computer program, wherein when the device containing the computer-readable storage medium executes the computer program, it implements the UPFC configuration optimization method as described above.

[0063] Compared to the prior art, the beneficial effects of the embodiments of this application are at least one of the following:

[0064] (1) This application constructs a set of key channel lines by conducting in-depth analysis of the topology information and operating parameters of the target power system. This can accurately locate the lines that have the greatest impact on the power flow distribution of the system. This not only helps to understand the operating characteristics of the system, but also provides a scientific basis for subsequent UPFC configuration, thereby improving the operating efficiency of the entire power system.

[0065] (2) This application simulates the power flow distribution of the grid after the UPFC to be configured is connected to different key channel lines, calculates the load rate, and then calculates the weighted power flow entropy. This method can scientifically determine the optimal access line of the UPFC. This method avoids blindly configuring resources, ensures that the UPFC can play its maximum role, and optimizes resource allocation.

[0066] (3) This application can evaluate the stability of the system under fault conditions by performing power flow calculations on the power grid operating state under preset fault scenarios and calculating the power transfer support strength of key channel lines. This provides an important reference for the capacity configuration of UPFC and helps to enhance the stability of the system under various conditions.

[0067] (4) Based on the optimal access line and power transfer support strength, this application establishes a UPFC grid-connected capacity optimization model and uses an improved particle swarm optimization algorithm for calculation to obtain the optimal capacity of the UPFC to be configured. This method not only improves the accuracy of configuration optimization, but also improves the computational efficiency through algorithm optimization, making the configuration optimization process faster and more efficient. Attached Figure Description

[0068] Figure 1 This is a simplified schematic diagram of the UPFC principle in one embodiment of this application;

[0069] Figure 2 This is a flowchart illustrating the UPFC configuration optimization method in one embodiment of this application;

[0070] Figure 3 This is a typical power flow diagram of an IEEE 3-machine 9-node system in one embodiment of this application;

[0071] Figure 4 This is a schematic diagram of a UPFC configuration optimization system in one embodiment of this application;

[0072] Figure 5 This is a structural block diagram of the UPFC configuration optimization device in one embodiment of this application. Detailed Implementation

[0073] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The purpose of providing these embodiments is to make the disclosure of this application more thorough and comprehensive. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0074] In the description of this application, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first," "second," "third," etc., may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0075] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal communication between two components. The terms "vertical," "horizontal," "left," "right," "upper," "lower," and similar expressions used herein are for illustrative purposes only and do not indicate or imply that the device or component referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as limiting this application. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0076] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used in the specification of this application is for the purpose of describing specific embodiments only and is not intended to limit the application. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0077] It should be noted beforehand that the UPFC structure can be divided into a series section, a DC section, and a parallel section. The series section functions as a Static Synchronous Series Compensator (SSSC), while the parallel section can be considered a Static Synchronous Compensator (STATCOM, SVG). The two are connected via the DC side, allowing active power to flow freely in either direction at the AC terminals of both the series and parallel sections, and enabling the independent generation or absorption of reactive power at their AC output terminals.

[0078] Figure 1 This indicates several key parameters of the UPFC device, such as Figure 1 The diagram shown is a simplified schematic of a UPFC principle provided in an embodiment of this application. , This refers to the voltage at the beginning and end of the transmission line; Inject the AC system voltage into the series side of the UPFC; and These are the power injected (absorbed) into the system from the series side and the parallel side of the UPFC, respectively; This refers to the current value of the transmission line. This is the DC bus voltage value. After adding the UPFC, the power at both ends becomes:

[0079]

[0080]

[0081] Before UPFC was added, the initial power at the beginning and end of the line were respectively , Then the above formula can be expressed as:

[0082]

[0083]

[0084] Therefore, it can be considered that after adding UPFC, the power at the sending and receiving ends is the power before adding UPFC plus the power due to the introduction of UPFC. And generated For UPFC, the control needs to address the receiving-end power and the introduced power. The subsequent reactive power change.

[0085] UPFC primarily regulates the active and reactive power of a line through series converters. The active power required by the series converters is provided by parallel converters, and the transmission of active power is achieved through a shared DC link. Both the series and parallel sides can output reactive power within their capacity, while the control system ensures the exchange of active power on the DC bus. The operating mode of the UPFC can be determined by the operating modes of its series and parallel sides.

[0086] Parallel side: The working principle of a parallel converter is to exchange power with the transmission line through a parallel transformer, thereby achieving active power transmission and reactive power compensation. The current can be considered in two parts: active component and reactive component. The active component is used to provide the active power required by the series converter. Based on the purpose of the reactive component, it is divided into three categories: reactive current injection control, reactive power control, and voltage control.

[0087] Reactive current injection control can be given by the sending-end voltage. Orthogonal reactive current reference vector The actual reactive current vector Simply following the reference vector is very useful during the commissioning of UPFC devices or in operation with certain special requirements. To achieve this control method, the parallel converter is usually required to have good dynamic quality and tracking accuracy, that is, the control should be closed-loop.

[0088] In reactive power control mode, the parallel converter injects reactive current orthogonal to the voltage into the system's sending end through closed-loop or open-loop control, thereby achieving the purpose of injecting the required reactive power. In reactive power control mode, the reactive power demand needs to be transformed into a reactive current demand. The parallel side can send or absorb a certain amount of active power to the system to maintain DC voltage stability and reduce active power losses within the system.

[0089] Similar to reactive power control, voltage control injects reactive current orthogonal to the voltage at the connection point into the system's sending end via closed-loop control on the parallel side, thereby adjusting the voltage at the injection point. The reference input is the voltage at the connection point on the parallel side, and the feedback measurement is the actual voltage value at that point. The error signal obtained by comparing the two is used to generate a correction value for the injected reactive current through appropriate closed-loop control.

[0090] Series side: The series converter injects a voltage vector with a certain amplitude and phase directly into the system. To change the distribution of power flow in a line, there are usually four control modes: direct voltage injection control, phase angle control, line impedance control, and power flow control.

[0091] In direct voltage injection control mode, the UPFC generates a given voltage vector, the magnitude and phase angle of which can be arbitrarily set. The actual voltage is compared with the given voltage, and the error is processed and used as the input to the series converter. A special mode of direct voltage injection is where the injected voltage vector is orthogonal to the line current vector, so that the UPFC only provides series reactive power compensation.

[0092] Phase angle control mode controls the injected voltage vector to deviate the output voltage by a given angle, while maintaining the amplitude. The actual voltage is compared with the given voltage, and the error is processed before being used as the input to the series converter.

[0093] Line impedance control injects a voltage proportional to the line current into the series-side system, causing the series transformer to exhibit impedance characteristics when viewed from the line side. The required impedance value is typically used as a given reference value and usually includes both resistance and reactance. In this control mode, special care must be taken to avoid negative impedance or capacitive reactance, thereby reducing the risk of oscillations and instability.

[0094] Power flow control is the primary control mode of UPFC (Upstream Power Flow Control). In this mode, the control variables are the active and reactive power transmitted by the line. The control objective is to maintain these control variables at a given value. , The system compares the actual active and reactive power transmitted by the line with a given value, and generates a voltage injection vector through appropriate closed-loop control.

[0095] The two converters in a UPFC can also operate independently: the parallel converter operates as an independent SVG, and the series converter operates as an independent SSSC. In both operating states, neither converter can generate or absorb active power; that is, they can only be used as reactive power compensators. Line power can still be controlled, but active and reactive power cannot be controlled separately.

[0096] The control characteristics of UPFC demonstrate that it can achieve rapid switching of active and reactive power, laying the foundation for balancing emergency power transfer and power flow optimization between regional power grids. During steady-state operation, it achieves load balancing by optimizing line power flow and node voltage. In the event of a regional power grid fault, it can provide emergency power support to the regional power grid through rapid transfer of line power flow and dynamic reactive power support, thereby improving the frequency and voltage stability characteristics of the regional power grid.

[0097] Based on the above description, one embodiment of this application provides a UPFC configuration optimization method. For details, please refer to [link to relevant documentation]. Figure 2 , Figure 2The diagram shown is a flowchart of a UPFC configuration optimization method according to one embodiment of this application, specifically including steps S1-S5:

[0098] S1: Analyze the topology information and operating parameters of the target power system obtained, and construct a set of key channel lines based on the analysis results;

[0099] Analyzing the acquired topology information and operating parameters of the target power system to construct a set of critical transmission lines is a complex but crucial process. The following is a detailed description of this process:

[0100] Obtain power system topology information from design documents, operational records, or real-time monitoring systems. This information typically includes the connection relationships of nodes in the power grid (such as substations and power plants), line transmission capacity, and switch status. Collect real-time operating parameters of the power system, such as voltage, current, and power factor of each node, as well as power flow distribution and loss conditions of lines. These parameters can be obtained through real-time monitoring systems or Supervisory Control and Data Acquisition (SCADA) systems for the power system.

[0101] A thorough analysis of the power system topology is conducted using graph theory and network analysis methods. This includes identifying critical nodes and lines in the power grid, and analyzing the grid's connectivity, redundancy, and vulnerability. Based on real-time operating parameters, the load conditions, power flow distribution, and stability of each line in the power grid are assessed. Particular attention is paid to lines with heavy loads, large power flow variations, or poor stability. Combining the results of topology analysis and operating parameter assessment, critical pathway lines in the power grid are identified. These lines are typically located at grid hubs, undertaking important power flow transmission tasks, and their failures could have a significant impact on the grid. The identified critical pathway lines are integrated into a set, namely the critical pathway line set. This set will serve as the basis for subsequent UPFC (Unified Power Flow Controller) configuration optimization.

[0102] S2: Initialize the capacity of the UPFC to be configured, simulate the power flow distribution of the power grid after the UPFC to be configured is connected to different key channel lines in the key channel line set, and calculate the load rate of the key channel line based on the simulation results of the power flow distribution.

[0103] Preferably, in one embodiment of this application, the step of simulating the power flow distribution of different critical channel lines after the UPFC is connected to the critical channel line set, using the capacity of the UPFC to be configured as the compensation value, and calculating the load rate of the critical channel line based on the simulation results of the power flow distribution, includes:

[0104] Establish a power grid model for the target power system;

[0105] Using the capacity of the UPFC to be configured as the compensation value, determine the compensation strategy of the UPFC to be configured in different critical channel lines;

[0106] According to the compensation strategy, the UPFC to be configured is connected to the power grid model, and the power flow distribution of the power grid model after the UPFC to be configured is connected to the power grid model is simulated based on the power flow calculation method.

[0107] The load rate of the critical channel line is calculated based on the power flow distribution.

[0108] The goal of power flow optimization is to achieve a more balanced power flow distribution across lines. The degree of power flow balance can typically be calculated using line load factor analysis. To evaluate the effect of installing UPFC (Upload Power Flow Control) devices on reducing power flow differences between lines, weighted power flow entropy can be used for quantitative assessment.

[0109] Preferably, in one embodiment of this application, the step of calculating the weighted power flow entropy based on the load rate includes:

[0110] according to The load factor is differentiated, with each interval having a length of [length missing]. The load rate is expressed as:

[0111] ,

[0112] in, For load rate, For the line Maximum conveying capacity For the actual running current, This represents the total number of transmission lines in the power system.

[0113] interval The proportion of line load rate within Defined as:

[0114] ,

[0115] in, For interval The total number of lines within the area; when a line is overloaded, the interval is used as the reference. Differentiate by load factor;

[0116] The weighted power flow entropy is calculated and expressed as:

[0117] ,

[0118] in, For weighted power flow entropy, For interval The average line load rate within the area.

[0119] S3: Calculate the weighted power flow entropy based on the load rate, and select the key channel line with the smallest weighted power flow entropy as the optimal access line for the UPFC to be configured.

[0120] As can be seen from S2, the weighted power flow entropy It shows a negative correlation with the uniformity of tidal current distribution. The smaller the value, the more balanced the power flow distribution of the power system. Considering the optimal situation, where the load rates of all lines fall within the same equally divided interval, The value is 0.

[0121] When determining the location of the UFPC device, the location that has the best impact on the power flow distribution balance of the system after the UPFC is connected is the location with the minimum weighted power flow entropy of the system.

[0122] S4: Perform power flow calculation on the power grid operation status of the target power system under the preset fault scenario, and calculate the power transfer support strength of the key channel line based on the result of the power flow calculation;

[0123] Emergency power reciprocity is primarily used when a power grid failure or maintenance results in an active power deficit in a certain region. It enables neighboring power grids to provide minute-level, large-scale, rapid power support to the faulty region based on their power supply margins, achieving large-scale power transfer and fault support across time and space. Assessing the emergency power reciprocity capability between regional power grids allows for analysis of the regional power grid's power supply margin and the power transmission capacity of critical transmission channels.

[0124] Regional power grid supply margin refers to the maximum power that can be absorbed or generated without affecting the local power grid. Supply margin is related not only to regional load and total generation but also closely to the composition of power sources. Power sources considered for emergency power exchange mainly include thermal power units, adjustable hydropower units, pumped storage units, and other power sources that can flexibly adjust their power according to demand. Nuclear power units and new energy units are not considered for inter-regional emergency power exchange. The maximum upward power margin that the regional power grid can provide on a minute-by-minute scale is also considered. It can be expressed by the following formula:

[0125]

[0126] in, , , These refer to the number of thermal power units, adjustable hydropower units, and pumped storage units operating within the regional power grid. For the initial output of thermal power units, This represents the maximum ramping power of thermal power units in the minute range; This is the initial output of the hydropower unit. The maximum power capacity corresponding to the hydropower reservoir capacity; This is the initial output of the pumped storage unit. This refers to the upper limit of power output corresponding to the reservoir capacity of a pumped storage power station.

[0127] Maximum power reduction margin available in minutes by the regional power grid It can be expressed by the following formula:

[0128]

[0129] in, Minimize the technical output of thermal power units; This represents the lower limit of power output corresponding to the reservoir capacity. This refers to the upper limit of power output corresponding to the reservoir capacity of a pumped storage power station.

[0130] The power transmission capacity of critical transmission lines is jointly determined by the line's thermal stability limit and safe and stable operating boundary. Considering different operating modes, the power transmission capacity of critical transmission lines... Take the thermal stability limit of the line The smaller of the two limits for safe and stable operation. Assuming the power flow from the regional power grid is positive, the safe and stable operating range of the critical corridor is... Maximum transmission capacity of key channels It can be represented as:

[0131]

[0132] Maximum receiving capacity of critical channel It can be represented as:

[0133]

[0134] Taking into account the adjustable power margin of the regional power grid and the power transmission capacity of key channels, the emergency power supply capacity of the regional power grid after a fault occurs in an adjacent regional power grid is as follows: It can be represented as:

[0135]

[0136] Regional power grid emergency power absorption capacity It can be represented as:

[0137]

[0138] The power transfer support strength is the ratio of the power transferred to the critical channel after a fault to the power limit of that channel.

[0139] Preferably, in one embodiment of this application, the power transfer support strength is expressed as:

[0140] ,

[0141] in, For the transmission power of the critical channel after a failure, The initial power for the critical channel; To provide emergency power support for the regional power grid.

[0142] When providing power When absorbing power is . In When the interval is within the range, the adjacent regional power grid can normally provide emergency power support to the faulty power grid. The larger the value, the higher the strength of power transfer support for the critical channel after the fault.

[0143] As can be seen from the above analysis, in order to improve the support strength of power transfer, on the one hand, the initial power of key channels can be controlled to leave sufficient margin for the channels; on the other hand, the power supply margin of the regional power grid can be improved by adjusting the operation mode of the regional power grid.

[0144] S5: Based on the optimal access line and the power transfer support strength, establish a UPFC grid-connected capacity optimization model, and calculate the UPFC grid-connected capacity optimization model according to the improved particle swarm optimization algorithm to obtain the optimal capacity of the UPFC to be configured, so as to optimize the configuration of the UPFC to be configured.

[0145] The optimization objectives of UPFC configuration consider both uniform power flow distribution during steady-state operation and ensuring grid frequency stability through emergency power exchange between regions after a fault. To achieve these objectives, it is necessary to optimize the power flow during steady-state operation to avoid overloading on individual lines and to make the power flow distribution as balanced as possible. Furthermore, it is crucial to pre-control the initial power flow of key inter-regional power grid channels to provide sufficient margin for power exchange between regional power grids in the event of a fault. The UPFC location is determined through steady-state power flow optimization, and the UPFC capacity is further determined by considering emergency power exchange capabilities in the event of a fault, thus completing the optimized configuration of the UPFC.

[0146] Constructing a weighted power flow entropy The site selection model characterizing the equilibrium of power flow distribution is as follows:

[0147]

[0148] Where D represents the power flow distribution of the system after different line access unit capacities UPFC.

[0149] By solving the UPFC location model, the line that has the best impact on the power flow distribution balance after UPFC access can be determined.

[0150] Constructing strength supported by power transfer The objective function representing the emergency power exchange capability between regional power grids under fault conditions is as follows:

[0151]

[0152] in, This refers to the installation capacity of UPFC.

[0153] The constraints mainly include: inequality constraints on unit output, node voltage, line load factor, and power transfer support strength; equality constraints on active and reactive power flow in the system after UPFC installation; and the installation capacity of the UPFC should consider the maximum rated capacity limit of the UPFC device at the current voltage level.

[0154]

[0155] in, , These are the active and reactive power outputs of the generator unit, respectively. Node voltage; Line load rate; , These are the active and reactive power outputs of the load, respectively. , These represent the changes in active and reactive power of the line before and after the installation of UPFC; This represents the maximum rated capacity of the UPFC device at this voltage level.

[0156] A UPFC grid-connected capacity optimization model is constructed based on the location model, the objective function of emergency power mutual assistance capability between regional power grids under fault conditions, and the constraints.

[0157] Specifically, this application employs the Particle Swarm Optimization (PSO) algorithm to solve nonlinear optimization problems. PSO excels in nonlinear optimization due to its simple structure, few parameters, and good convergence. By simulating swarm intelligence, PSO can quickly converge to a near-optimal solution and is suitable for handling various complex nonlinear problems. Although PSO is prone to getting trapped in local optima, this problem can be mitigated to some extent through appropriate improvements and parameter tuning. Based on these characteristics, the PSO algorithm is chosen to solve the nonlinear optimization problem in the UPFC configuration model.

[0158] Preferably, in one embodiment of this application, the step of calculating the optimal configuration capacity of the UPFC to be configured based on the improved particle swarm optimization algorithm to obtain the grid-connected capacity optimization model of the UPFC includes:

[0159] The capacity value of the UPFC to be configured is randomly initialized as a particle, and the particle represents a UPFC configuration scheme;

[0160] Calculate the fitness value of each particle, and iteratively update the particles based on the fitness value and a nonlinear decreasing inertia weight.

[0161] When the result of the iterative update meets the preset convergence condition, the current result is output as the optimal configuration capacity of the UPFC to be configured.

[0162] Specifically, the particle swarm optimization algorithm for solving nonlinear optimization problems includes the following steps:

[0163] Step 1: Initialize particle swarm parameters: Determine the particle swarm size Particle dimension Maximum number of iterations Inertia weight Learning factors ;

[0164] Step 2: Randomly initialize the position and velocity of each particle: individual historical best position Group's historical best position Individual historical optimal fitness value The best fitness value in history ;

[0165] Step 3: Determine if the termination condition is met. If it is, output the optimal solution; otherwise, update the velocity and position of each particle.

[0166]

[0167]

[0168] In the formula, For the number of iterations, For the first The speed of each particle For the first The position of each particle. and As a learning factor, and For interval Random numbers within.

[0169] Step 4: Calculate the fitness value of each particle. ;

[0170] Step 5: Update the individual historical best fitness value and position of each particle;

[0171] Step 6: Update the population's historical best fitness and position;

[0172] Step 7: Update other parameters, such as inertia weight and number of iterations; return to Step 3.

[0173] Based on the particle swarm optimization algorithm, a nonlinear decreasing inertia weight method is adopted to dynamically adjust the search behavior of particles. The inertia weight plays a role in balancing global and local searches in the particle swarm optimization algorithm. By nonlinearly decreasing the inertia weight, the algorithm can optimize the search strategy at different stages of the search process: in the early stages of the search, a larger inertia weight encourages particles to conduct a broad global search, enhancing the algorithm's exploration capability; while in the later stages of the search, the inertia weight gradually decreases, causing particles to concentrate on local searches, thereby improving the accuracy and speed of local convergence. This strategy effectively avoids the risk of the particle swarm getting trapped in local optima too early, while ensuring the diversity of the search process and the approximation ability of the optimal solution, thus improving the overall convergence performance. The specific formula is shown below:

[0174]

[0175] in, and These are the upper and lower limits of the inertia weight, respectively.

[0176] Furthermore, a perturbation mechanism is introduced, which involves periodically applying small, random perturbations to the particle's velocity and position during the search process. This mechanism ensures that even when the particle swarm approaches a local optimum, particles still have the opportunity to escape the local region and continue exploring better solutions. By introducing randomness at appropriate times, the state of the particle swarm trapped in local optima is effectively broken, thereby enhancing the algorithm's global search capability and reducing the risk of getting trapped in local optima. The specific formula is shown below:

[0177]

[0178] in, For random perturbation weights, The initial values ​​for the random perturbation weights are... For interval Random numbers within.

[0179] By dynamically adjusting the inertia weight and introducing a particle perturbation mechanism, the risk of getting trapped in local optima during the solution process is further reduced, and the algorithm's global search capability and convergence performance are improved.

[0180] The following is a specific embodiment to illustrate the technical solution of this application.

[0181] Taking the IEEE 39-node system as an example, specifically, such as Figure 3 As shown, Figure 3This is a typical power flow diagram for an IEEE 3-machine, 9-node system. The IEEE 39-node system comprises two voltage levels and two main power supply areas. Power supply area one consists of BUS25 to BUS30, while the remaining nodes constitute power supply area two. During normal operation, power supply area one primarily draws power from the high-voltage node BUS28, and the power flow on the BUS24 to BUS25 line (the tie line between the two power supply areas) is essentially zero.

[0182] Step 1: BUS6-BUS28, BUS8-BUS28, and BUS24-BUS25 constitute the key passage.

[0183] Step 2: Configure UPFCs of the same capacity on the above lines respectively, and calculate the weighted power flow entropy. The results are shown in Table 1. Table 1 shows the weighted power flow entropy of the system after UPFC configuration.

[0184] Table 1

[0185]

[0186] The results above show that configuring UPFC at BUS28 on the BUS8-BUS28 line results in a more uniform power flow distribution in the system.

[0187] Step 3: Analyze the power supply zone 1, which has only load. Power supply zone 2 has BUS1, BUS2, BUS5, BUS8, and BUS11 as generator nodes, with BUS1 being a hydroelectric turbine. Based on the generator's current active power output, minimum technical output, maximum minute-level ramp power of the thermal power unit, and the power limit corresponding to the hydroelectric reservoir capacity, calculate the maximum upward power margin that power supply zone 2 can provide for power supply zone 1. The maximum downward power margin is 861.2MW. The result is 170.9 MW. Table 2 shows the adjustable power margin (unit: MW) for power supply zone 1.

[0188] Table 2

[0189]

[0190] The rated transmission powers of BUS6-BUS28, BUS8-BUS28, and BUS24-BUS25 are 32MVA, 32MVA, and 16MVA, respectively, without considering line overload capacity. Considering the maximum adjustable power of power supply zone one and the capacity of critical channels within the power supply zone, in the event of a fault in power supply zone two, the emergency power support capacity that power supply zone one can provide is limited by the rated transmission power of the critical channels.

[0191] Using a 5MW load change in power supply zone 2 (total load 16.5MW) as the check fault, calculate the power transfer support strength of the critical channel. The optimal UPFC configuration capacity is determined to be 1.2 MVA. At this point, the enhanced power flow entropy is 0.9260, and the critical channel power transfer support strength is 7.5%.

[0192] Another embodiment of this application provides a UPFC configuration optimization method. For details, please refer to [link to relevant documentation]. Figure 4 , Figure 4 The diagram shown is a flowchart illustrating a UPFC configuration optimization method according to one embodiment of this application, specifically including: an analysis module 11, a simulation module 12, a configuration module 13, a calculation module 14, and an optimization module 15, wherein...

[0193] Analysis module 11 is used to analyze the topology information and operating parameters of the target power system and construct a set of key channel lines based on the analysis results.

[0194] The simulation module 12 is used to initialize the capacity of the UPFC to be configured, simulate the power flow distribution of the power grid after the UPFC to be configured is connected to different key channel lines in the key channel line set, and calculate the load rate of the key channel line based on the simulation results of the power flow distribution.

[0195] Configuration module 13 is used to calculate the weighted power flow entropy based on the load rate, and to select the key channel line with the smallest weighted power flow entropy as the optimal access line of the UPFC to be configured.

[0196] Calculation module 14 is used to perform power flow calculation on the power grid operation status of the target power system under a preset fault scenario, and calculate the power transfer support strength of the key channel line based on the result of the power flow calculation.

[0197] The optimization module 15 is used to establish a UPFC grid-connected capacity optimization model based on the optimal access line and the power transfer support strength, and to calculate the optimal capacity of the UPFC to be configured by calculating the UPFC grid-connected capacity optimization model according to the improved particle swarm optimization algorithm, so as to optimize the configuration of the UPFC to be configured.

[0198] Preferably, in one embodiment of this application, the simulation module is specifically used for:

[0199] Establish a power grid model for the target power system;

[0200] Using the capacity of the UPFC to be configured as the compensation value, determine the compensation strategy of the UPFC to be configured in different critical channel lines;

[0201] According to the compensation strategy, the UPFC to be configured is connected to the power grid model, and the power flow distribution of the power grid model after the UPFC to be configured is connected to the power grid model is simulated based on the power flow calculation method.

[0202] The load rate of the critical channel line is calculated based on the power flow distribution.

[0203] Preferably, in one embodiment of this application, the configuration module is further configured to:

[0204] according to The load factor is differentiated, with each interval having a length of [length missing]. The load rate is expressed as:

[0205] ,

[0206] in, For load rate, For the line Maximum conveying capacity For the actual running current, This represents the total number of transmission lines in the power system.

[0207] interval The proportion of line load rate within Defined as:

[0208] ,

[0209] in, For interval The total number of lines within;

[0210] The weighted power flow entropy is calculated and expressed as:

[0211] ,

[0212] in, For weighted power flow entropy, For interval The average line load rate within the area.

[0213] Preferably, in one embodiment of this application, the power transfer support strength is expressed as:

[0214] ,

[0215] in, For the transmission power of the critical channel after a failure, The initial power for the critical channel; To provide emergency power support for the regional power grid.

[0216] Preferably, in one embodiment of this application, the optimization module is specifically used for:

[0217] The capacity value of the UPFC to be configured is randomly initialized as a particle, and the particle represents a UPFC configuration scheme;

[0218] Calculate the fitness value of each particle, and iteratively update the particles based on the fitness value and a nonlinear decreasing inertia weight.

[0219] When the result of the iterative update meets the preset convergence condition, the current result is output as the optimal configuration capacity of the UPFC to be configured.

[0220] Another embodiment of this application provides a UPFC configuration optimization device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the UPFC configuration optimization method as described above.

[0221] See Figure 5 This is a structural block diagram of the UPFC configuration optimization device provided in this application embodiment. The UPFC configuration optimization device provided in this application embodiment includes a processor 21, a memory 22, and a computer program stored in the memory 22 and configured to be executed by the processor 21. When the processor 21 executes the computer program, it implements the steps as described in the above UPFC configuration optimization method embodiment, for example... Figure 1 The steps S1 to S5 described above; or, when the processor 21 executes the computer program, it implements the functions of each module in the above-described device embodiments, such as the analysis module 11.

[0222] For example, the computer program may be divided into one or more modules, which are stored in the memory 22 and executed by the processor 21 to complete this application. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the UPFC configuration optimization device.

[0223] The UPFC configuration optimization device may include, but is not limited to, a processor 21 and a memory 22. Those skilled in the art will understand that the schematic diagram is merely an example of the UPFC configuration optimization device and does not constitute a limitation on the UPFC configuration optimization device. It may include more or fewer components than illustrated, or combine certain components, or different components. For example, the UPFC configuration optimization device may also include input / output devices, network access devices, buses, etc.

[0224] The processor 21 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor 21 is the control center of the UPFC configuration optimization device, connecting various parts of the entire UPFC configuration optimization device via various interfaces and lines.

[0225] The memory 22 can be used to store the computer programs and / or modules. The processor 21 implements various functions of the UPFC configuration optimization device by running or executing the computer programs and / or modules stored in the memory 22 and calling the data stored in the memory 22. The memory 22 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory 22 may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0226] If the modules integrated into the UPFC configuration optimization device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0227] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0228] Accordingly, another embodiment of this application provides a computer-readable storage medium storing a computer program, wherein when the device containing the computer-readable storage medium executes the computer program, it implements the UPFC configuration optimization method as described above.

[0229] The computer-readable storage medium is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the UPFC configuration optimization method in the above embodiments.

[0230] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application 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.

[0231] Compared to the prior art, the beneficial effects of the embodiments of this application are at least one of the following:

[0232] (1) This application constructs a set of key channel lines by conducting in-depth analysis of the topology information and operating parameters of the target power system. This can accurately locate the lines that have the greatest impact on the power flow distribution of the system. This not only helps to understand the operating characteristics of the system, but also provides a scientific basis for subsequent UPFC configuration, thereby improving the operating efficiency of the entire power system.

[0233] (2) This application simulates the power flow distribution of the grid after the UPFC to be configured is connected to different key channel lines, calculates the load rate, and then calculates the weighted power flow entropy. This method can scientifically determine the optimal access line of the UPFC. This method avoids blindly configuring resources, ensures that the UPFC can play its maximum role, and optimizes resource allocation.

[0234] (3) This application can evaluate the stability of the system under fault conditions by performing power flow calculations on the power grid operating state under preset fault scenarios and calculating the power transfer support strength of key channel lines. This provides an important reference for the capacity configuration of UPFC and helps to enhance the stability of the system under various conditions.

[0235] (4) Based on the optimal access line and power transfer support strength, this application establishes a UPFC grid-connected capacity optimization model and uses an improved particle swarm optimization algorithm for calculation to obtain the optimal capacity of the UPFC to be configured. This method not only improves the accuracy of configuration optimization, but also improves the computational efficiency through algorithm optimization, making the configuration optimization process faster and more efficient.

[0236] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A UPFC configuration optimization method, characterized in that, include: The topology information and operating parameters of the target power system are analyzed, and a set of key channel lines is constructed based on the analysis results. Initialize the capacity of the UPFC to be configured, simulate the power flow distribution of the power grid after the UPFC to be configured is connected to different key channel lines in the key channel line set, and calculate the load rate of the key channel line based on the simulation results of the power flow distribution. Calculate the weighted power flow entropy based on the load rate, and select the critical channel line with the smallest weighted power flow entropy as the optimal access line for the UPFC to be configured. Power flow calculation is performed on the power grid operation status of the target power system under a preset fault scenario, and the power transfer support strength of the key channel line is calculated based on the result of the power flow calculation. Based on the optimal access line and the power transfer support strength, a UPFC grid-connected capacity optimization model is established. The UPFC grid-connected capacity optimization model is calculated according to the improved particle swarm optimization algorithm to obtain the optimal capacity of the UPFC to be configured, so as to optimize the configuration of the UPFC to be configured.

2. The UPFC configuration optimization method as described in claim 1, characterized in that, The process of initializing the capacity of the UPFC to be configured involves simulating the power flow distribution of the grid after the UPFC to be configured is connected to different critical channel lines in the critical channel line set, and calculating the load rate of the critical channel lines based on the simulation results of the power flow distribution, including: Establish a power grid model for the target power system; Using the capacity of the UPFC to be configured as the compensation value, determine the compensation strategy of the UPFC to be configured in different critical channel lines; According to the compensation strategy, the UPFC to be configured is connected to the power grid model, and the power flow distribution of the power grid model after the UPFC to be configured is connected to the power grid model is simulated based on the power flow calculation method. The load rate of the critical channel line is calculated based on the power flow distribution.

3. The UPFC configuration optimization method as described in claim 1, characterized in that, The calculation of weighted power flow entropy based on the load rate includes: according to The load factor is differentiated, with each interval having a length of [length missing]. The load rate is expressed as: ， in, For load rate, For the line Maximum conveying capacity For the actual running current, This represents the total number of transmission lines in the power system. interval The proportion of line load rate within Defined as: ， in, For interval The total number of lines within; The weighted power flow entropy is calculated and expressed as: ， in, For weighted power flow entropy, For interval The average line load rate within the area.

4. The UPFC configuration optimization method as described in claim 1, characterized in that, The power transfer support strength is expressed as: ， in, For the transmission power of the critical channel after a failure, The initial power for the critical channel; To provide emergency power support for the regional power grid.

5. The UPFC configuration optimization method as described in claim 1, characterized in that, The step of calculating the optimal configuration capacity of the UPFC based on the improved particle swarm optimization algorithm to obtain the grid-connected capacity optimization model of the UPFC to be configured includes: The capacity value of the UPFC to be configured is randomly initialized as a particle, and the particle represents a UPFC configuration scheme; Calculate the fitness value of each particle, and iteratively update the particles based on the fitness value and a nonlinear decreasing inertia weight. When the result of the iterative update meets the preset convergence condition, the current result is output as the optimal configuration capacity of the UPFC to be configured.

6. A UPFC configuration optimization system, characterized in that, include: The analysis module is used to analyze the topology information and operating parameters of the target power system and construct a set of key channel lines based on the analysis results. The simulation module is used to initialize the capacity of the UPFC to be configured, simulate the power flow distribution of the power grid after the UPFC to be configured is connected to different key channel lines in the key channel line set, and calculate the load rate of the key channel line based on the simulation results of the power flow distribution. The configuration module is used to calculate the weighted power flow entropy based on the load rate, and to select the key channel line with the smallest weighted power flow entropy as the optimal access line of the UPFC to be configured. The calculation module is used to perform power flow calculation on the power grid operation status of the target power system under a preset fault scenario, and to calculate the power transfer support strength of the key channel line based on the result of the power flow calculation. The optimization module is used to establish a UPFC grid-connected capacity optimization model based on the optimal access line and the power transfer support strength, and to calculate the optimal capacity of the UPFC to be configured by calculating the UPFC grid-connected capacity optimization model according to the improved particle swarm optimization algorithm, so as to optimize the configuration of the UPFC to be configured.

7. The UPFC configuration optimization system as described in claim 6, characterized in that, The simulation module is specifically used for: Establish a power grid model for the target power system; Using the capacity of the UPFC to be configured as the compensation value, determine the compensation strategy of the UPFC to be configured in different critical channel lines; According to the compensation strategy, the UPFC to be configured is connected to the power grid model, and the power flow distribution of the power grid model after the UPFC to be configured is connected to the power grid model is simulated based on the power flow calculation method. The load rate of the critical channel line is calculated based on the power flow distribution.

8. The UPFC configuration optimization system as described in claim 6, characterized in that, The configuration module is also used for: according to The load factor is differentiated, with each interval having a length of [length missing]. The load rate is expressed as: ， in, For load rate, For the line Maximum conveying capacity For the actual running current, This represents the total number of transmission lines in the power system. interval The proportion of line load rate within Defined as: ， in, For interval The total number of lines within; The weighted power flow entropy is calculated and expressed as: ， in, For weighted power flow entropy, For interval The average line load rate within the area.

9. The UPFC configuration optimization system as described in claim 6, characterized in that, The power transfer support strength is expressed as: ， in, For the transmission power of the critical channel after a failure, The initial power for the critical channel; To provide emergency power support for the regional power grid.

10. The UPFC configuration optimization system as described in claim 6, characterized in that, The optimization module is specifically used for: The capacity value of the UPFC to be configured is randomly initialized as a particle, and the particle represents a UPFC configuration scheme; Calculate the fitness value of each particle, and iteratively update the particles based on the fitness value and a nonlinear decreasing inertia weight. When the result of the iterative update meets the preset convergence condition, the current result is output as the optimal configuration capacity of the UPFC to be configured.

11. A UPFC configuration optimization device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the UPFC configuration optimization method as described in any one of claims 1 to 5.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein when the device containing the computer-readable storage medium executes the computer program, it implements the UPFC configuration optimization method as described in any one of claims 1 to 5.

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