Reactive power compensation device capacity configuration method and system for high-proportion new energy region

Abstract

The application discloses a kind of reactive power compensation device capacity configuration methods and systems for high proportion new energy area, it is related to power system optimization and reactive power compensation technical field.The method includes the following steps: obtaining the operating parameter of reactive power compensation equipment in new energy system high penetration rate area;According to the operating parameter of reactive power compensation equipment, the stability degree of system, the construction of cost is considered, and multi-dimensional index system is constructed, and multi-dimensional index system includes system stability index, new energy consumption capacity index and equipment cost index;Based on the influence relationship between each index in multi-dimensional index system, set up comprehensive cost function;The optimal result of capacity configuration is obtained by solving target function.The present application aims to solve the problem of system stability decline, equipment investment utilization rate is low and new energy consumption capacity is insufficient caused by unreasonable reactive power compensation equipment capacity configuration in new energy high penetration rate area, and realizes the collaborative optimization of system stability, economy and new energy friendliness.

Description

Technical Field

[0001] This invention relates to the field of power system optimization and reactive power compensation technology, and in particular to a method and system for configuring the capacity of reactive power compensation devices in areas with a high proportion of renewable energy. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] With the continuous increase in the proportion of new energy installed capacity, the proportion of traditional synchronous power sources in the power system is gradually decreasing, the system inertia and short-circuit capacity are significantly reduced, and the voltage support capacity and reactive power regulation capacity are significantly weakened. Against this background, reactive power compensation equipment (including static synchronous compensators (SVG), static var compensators (SVC), distributed synchronous condensers, grid-based energy storage, etc.) has become a key piece of equipment for maintaining voltage stability and improving the reactive power support capacity of the system.

[0004] Currently, the capacity configuration methods for reactive power compensation equipment in power systems have the following drawbacks:

[0005] (1) Set the equipment capacity according to the system voltage fluctuation range, load level or operating experience. Although this method is simple and easy to implement, it is difficult to take into account the dynamic characteristics of the system and adaptability to multiple scenarios.

[0006] (2) Calculations are made in accordance with the configuration principles given by relevant domestic standards and specifications. However, the capacity range is wide, making it difficult to achieve precise configuration.

[0007] (3) Using a single objective (such as minimizing voltage deviation, minimizing equipment investment, or minimizing reactive power loss) as the optimization objective, the equipment capacity is determined through mathematical programming or sensitivity analysis. This type of method ignores multi-dimensional factors such as system stability and the fluctuation of new energy output.

[0008] (4) In recent years, some studies have introduced intelligent optimization algorithms such as genetic algorithms, particle swarm optimization, and ant colony optimization to solve reactive power compensation capacity. However, most studies only consider static operating indicators and have failed to effectively establish a unified evaluation system among system stability, economy, and new energy absorption capacity, making it difficult to fully reflect system performance.

[0009] Therefore, existing solutions still have shortcomings in terms of comprehensiveness, dynamic adaptability, and consistency with physical constraints, and there is an urgent need for a more scientific, systematic, and feasible method for optimizing the configuration of reactive power compensation equipment capacity. Summary of the Invention

[0010] To address the shortcomings of existing technologies, the present invention aims to provide a method and system for configuring the capacity of reactive power compensation devices in areas with a high proportion of renewable energy. This method and system are designed to solve problems such as decreased system stability, low equipment investment utilization, and insufficient renewable energy absorption capacity caused by unreasonable capacity configuration of reactive power compensation equipment (such as SVG, SVC, synchronous condensers, and grid-type energy storage) in areas with high renewable energy penetration. The goal is to achieve synergistic optimization of system stability, economy, and renewable energy friendliness.

[0011] To achieve the above objectives, the present invention is implemented through the following technical solution:

[0012] The first aspect of this invention provides a method for configuring the capacity of reactive power compensation devices in areas with a high proportion of renewable energy, comprising the following steps:

[0013] Obtain the operating parameters of reactive power compensation equipment in areas with high penetration rates of new energy systems, and preprocess the operating parameters;

[0014] Based on the operating parameters of the reactive power compensation equipment, a multi-dimensional indicator system is constructed considering the system's stability, absorption capacity, and cost. The multi-dimensional indicator system includes system stability indicators, new energy absorption capacity indicators, and equipment cost indicators.

[0015] A comprehensive cost function is set based on the influence relationship between various indicators in a multi-dimensional indicator system;

[0016] The optimal capacity configuration is obtained by solving the objective function.

[0017] Furthermore, system stability indices are used to comprehensively reflect the system's transient steady-state performance under disturbances, including voltage support capability and frequency support capability. Voltage support capability is characterized by short-circuit ratio, transient voltage recovery index, and transient voltage peak index, while frequency support capability is characterized by frequency change rate and maximum frequency offset in the initial stage of disturbance.

[0018] Furthermore, the renewable energy consumption index is the ratio of the maximum renewable energy output to the installed capacity of the system under the same short-circuit ratio.

[0019] Furthermore, the equipment cost index is used as a penalty term in the comprehensive cost function to comprehensively reflect the economic constraints of different types of auxiliary equipment.

[0020] Furthermore, the formula for the comprehensive cost function is:

[0021] ,

[0022] in, For the comprehensive cost function, Indicates the capacity of the devices installed in the system. , , These are system stability indicators New energy consumption capacity indicators and equipment cost indicators The weighting coefficients satisfy the following constraints: Coupling terms This is used to characterize the combined effect of insufficient stability and insufficient absorption. The weighting coefficients of the coupling terms.

[0023] Furthermore, constraints for the comprehensive cost function are set based on node voltage amplitude safety, active power balance, reactive power variation, and equipment capacity limits.

[0024] A second aspect of the present invention provides a reactive power compensation device capacity configuration system for areas with a high proportion of renewable energy sources, comprising:

[0025] The data acquisition module is used to acquire the operating parameters of reactive power compensation equipment in areas with high penetration rates of new energy systems, and to preprocess the operating parameters.

[0026] The indicator system construction module is used to construct a multi-dimensional indicator system based on the operating parameters of reactive power compensation equipment, taking into account the system's stability, absorption capacity, and cost. The multi-dimensional indicator system includes system stability indicators, new energy absorption capacity indicators, and equipment cost indicators.

[0027] The objective function setting module is used to set the comprehensive cost function based on the influence relationship between various indicators in a multi-dimensional indicator system.

[0028] The capacity configuration optimization module is used to solve the objective function to obtain the optimal capacity configuration result.

[0029] A third aspect of the present invention provides a computer-readable storage medium storing a computer program adapted to be loaded by a processor and executed the steps of the method for configuring the capacity of reactive power compensation devices in areas with a high proportion of renewable energy as described in the first aspect of the present invention.

[0030] A fourth aspect of the present invention provides a computer device comprising:

[0031] A processor, adapted to execute computer programs;

[0032] A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the reactive power compensation device capacity configuration method for high-proportion renewable energy regions as described in the first aspect of the present invention.

[0033] A fifth aspect of the present invention provides a computer program product or computer program comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps in the reactive power compensation device capacity configuration method for high-proportion renewable energy areas as described in the first aspect of the present invention.

[0034] The above one or more technical solutions have the following beneficial effects:

[0035] This invention discloses a method and system for configuring the capacity of reactive power compensation devices in areas with a high proportion of renewable energy sources. This method optimizes the configuration of reactive power compensation equipment capacity by comprehensively considering system stability, renewable energy absorption capacity, and economic efficiency. By establishing a unified comprehensive cost function, normalizing and weighting the indicators, and combining system constraints with simulation results, the optimal configuration point of the equipment capacity is determined, thereby achieving a balance between economic efficiency and operational performance while satisfying system safety constraints.

[0036] This invention constructs a three-dimensional comprehensive evaluation system encompassing system stability, renewable energy absorption capacity, and economic efficiency, enabling a comprehensive reflection of system performance. By establishing a unified cost function through normalization and weighted processing, the dimensional differences between different indicators are effectively eliminated, allowing multi-objective optimization problems to be solved quantitatively.

[0037] This invention introduces system operation constraints (such as the qualified range of bus voltage, the upper limit of equipment capacity, and the system reactive power balance constraints) to ensure that the optimization results are feasible for engineering implementation.

[0038] This invention obtains the cost function versus equipment capacity variation curve through simulation calculations, which can intuitively reflect the sensitivity of system performance to capacity changes and provide a basis for engineering configuration decisions. It can be applied to the individual or combined configuration optimization of different types of reactive power compensation equipment and has good scalability and versatility.

[0039] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1This is a flowchart of the reactive power compensation device capacity configuration method for areas with a high proportion of renewable energy in Embodiment 1 of the present invention. Detailed Implementation

[0042] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0043] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0044] 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. 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.

[0045] The renewable energy penetration rate refers to the proportion of renewable energy power generation to total power generation within a specific time period (year, month, day) within a power grid control area, reflecting the system's power support capacity from renewable energy. The renewable energy power consumption responsibility weight refers to the proportion of renewable energy power that should be consumed according to provincial administrative region regulations, including the total consumption responsibility weight and the non-hydropower consumption responsibility weight. The total consumption responsibility weight is the renewable energy power to be consumed divided by the total social electricity consumption. The non-hydropower consumption responsibility weight only considers "new energy" such as wind power, photovoltaics, and biomass, excluding hydropower.

[0046] A higher weight for a region indicates that it possesses the resource conditions and system carrying capacity for a higher proportion of renewable energy use, and it is required to undertake a higher clean energy consumption task. Therefore, the non-hydropower consumption responsibility weight can represent the identification and requirements of the local clean energy proportion, and it corresponds highly with the actual power structure and has unified comparability. Thus, this weight can be used as a benchmark to judge the level of new energy penetration in a region.

[0047] Therefore, if the renewable energy penetration rate in region B of province A exceeds twice the non-hydropower consumption responsibility weight of province A, and the renewable energy penetration rate in region B exceeds 1.5 times the national average non-hydropower consumption responsibility weight of all provinces, then region B can be considered a region with high renewable energy penetration. This criterion ensures that region B's renewable energy penetration rate ranks among the top in the province and is significantly higher than the set average renewable energy penetration rate.

[0048] Regions with a high penetration rate of new energy sources have the following characteristics:

[0049] (1) The system short-circuit capacity has decreased significantly: the reduction of synchronous power supply leads to a decrease in SCR and insufficient voltage support capability.

[0050] (2) Inertia loss and increased frequency fluctuation: The power electronic interface power supply does not provide natural inertia, and RoCoF increases after disturbance.

[0051] (3) Reactive power demand exhibits strong volatility and dynamic coupling: rapid changes in the output of new energy sources lead to time-varying characteristics in reactive power support demand.

[0052] (4) Traditional static compensation configuration method fails: simply configuring capacity based on steady-state voltage deviation is difficult to cover the needs of transient voltage recovery and frequency support.

[0053] Therefore, in areas with a high proportion of renewable energy penetration, the power grid's ability to withstand extreme operating conditions such as fault impacts, load disturbances, and sudden changes in renewable energy output has significantly decreased. This has led to a weakening of the grid's voltage support capacity, insufficient frequency regulation capability, increased difficulty in power balance, and further problems such as deterioration of power quality.

[0054] Example 1:

[0055] Embodiment 1 of the present invention provides a method for configuring the capacity of reactive power compensation devices in areas with a high proportion of renewable energy. By constructing a comprehensive cost function, the method performs unified modeling and quantification of factors such as system operation stability, voltage and frequency support capabilities, equipment investment costs, and renewable energy output levels, thereby achieving a balance and optimization of multi-dimensional performance indicators and determining the optimal equipment configuration capacity.

[0056] like Figure 1 As shown, the specific steps include:

[0057] S1: Obtain the operating parameters of reactive power compensation equipment in areas with high penetration rates of new energy systems, and preprocess the operating parameters.

[0058] In one specific implementation, the operating parameters of the reactive power compensation equipment include stability index parameters, absorption index parameters, and cost index parameters, corresponding to system stability index, renewable energy absorption capacity index, and equipment cost index, respectively. The stability index parameters include short-circuit current, node voltage, and frequency, obtained through transient simulation calculations. The absorption index parameters include maximum stable grid-connected power and installed capacity, obtained through output increment simulations. The cost index parameters include unit capacity cost, maintenance factor, and lifespan conversion factor, obtained from existing engineering cost databases or manufacturer parameters.

[0059] In this embodiment, the following special designs were made for high-penetration areas during the target construction and solution process: The short-circuit ratio (SCR) and transient voltage recovery (TVR) were introduced into the indicator system to characterize the insufficient voltage support capacity under weak grid conditions. The rate of frequency change (RoCoF) and maximum frequency deviation (Δf) were added to the stability indicators to reflect the frequency safety boundary under inertia-deficient conditions. The renewable energy absorption index (NEAC) was used to characterize the effect of capacity configuration on the maximum grid connection limit, reflecting that the core objective in high-penetration areas is absorption capacity constraints rather than simply voltage compliance.

[0060] Subsequently, a coupled trade-off mechanism of stability, absorption, and cost is established in the comprehensive cost function to enable the optimization objective to adapt to the scenario where new energy fluctuations and weak support coexist.

[0061] S2: Based on the operating parameters of the reactive power compensation equipment, a multi-dimensional indicator system is constructed, taking into account the system's stability, absorption capacity, and cost. The multi-dimensional indicator system includes system stability indicators, new energy absorption capacity indicators, and equipment cost indicators.

[0062] In one specific implementation, in power systems with a high proportion of renewable energy integration, system stability, absorption capacity, and economic efficiency are often coupled and constrained. Existing technologies, which only consider equipment configuration from a single perspective, cannot comprehensively reflect the overall system performance. Therefore, this embodiment constructs a multi-dimensional, multi-level evaluation index system. This index system quantitatively characterizes the characteristics of different auxiliary equipment in terms of voltage support, frequency stability, system inertia response, and economic efficiency from three aspects: system stability, renewable energy absorption level, and equipment cost. By normalizing and weighting the various indicators, a unified comparison of performance indicators across different dimensions can be achieved under the same dimension, providing a quantitative basis for subsequent capacity optimization and cost function establishment.

[0063] S2.1: Set system stability indicators.

[0064] In one specific implementation, system stability is the primary indicator for evaluating the control performance of auxiliary equipment, reflecting the system's transient response and recovery capability after a disturbance occurs. With the increased proportion of renewable energy connected to the grid, voltage and frequency fluctuations intensify due to a significant decrease in synchronous inertia and an increase in system impedance. Therefore, a composite indicator system capable of simultaneously characterizing voltage support performance and frequency stability is required. System stability indicators This indicator comprehensively reflects the system's transient steady-state performance under disturbances, including voltage support capability and frequency support capability. A higher value indicates a stronger ability of the equipment to improve system stability. Voltage support capability is characterized by the short-circuit ratio, transient voltage recovery index, and transient voltage peak index, while frequency support capability is characterized by the frequency change rate and maximum frequency offset in the initial stage of the disturbance.

[0065] S2.1.1: Voltage support capability via short-circuit ratio ( Transient voltage recovery index ( ) and transient voltage peak index ( ) is characterized.

[0066] Short-circuit ratio The system's support capability is defined as:

[0067] .

[0068] In the formula, This refers to the short-circuit current at the node after a three-phase short-circuit fault occurs. The rated operating voltage of the node. The total installed capacity of new energy sources is given. The calculation condition is as follows: with the new energy output at 50%, a three-phase short-circuit fault is set at substation A (the fault occurs in 2 seconds and lasts for 0.5 seconds).

[0069] Transient voltage recovery index The deviation between the transient voltage of a node and its rated operating voltage after a disturbance occurs is represented by:

[0070] .

[0071] In the formula, For the node after the disturbance Voltage at any given moment; The initial operating voltage of the node is given. The calculation condition is: with the renewable energy output at 50%, the renewable energy output suddenly decreases by 20%.

[0072] Transient voltage peak index This indicates the severity of overvoltage at a node after a disturbance occurs.

[0073] .

[0074] The calculation condition is as follows: with the output of new energy at 50%, the output of new energy suddenly decreases by 20%.

[0075] S2.1.2: Frequency support capability through the rate of frequency change in the initial stage of the disturbance ( ) and maximum frequency offset ( ) to perform description and characterization.

[0076] Rate of change of frequency This represents the rate of frequency change during the initial stage of the disturbance.

[0077] .

[0078] The calculation condition is as follows: with the output of new energy at 50%, the output of new energy suddenly decreases by 20%.

[0079] Maximum frequency offset This represents the maximum frequency shift after the disturbance occurs.

[0080] .

[0081] In the formula, This represents the maximum frequency during the transient process. This represents the minimum frequency during the transient process. The calculation condition is: with the renewable energy output at 50%, the renewable energy output suddenly decreases by 20%.

[0082] Because the dimensions of different indicators differ significantly, and some parameters exhibit random fluctuations, preprocessing is required before comprehensive evaluation.

[0083] Outlier cleaning. This involves removing non-representative sampling points caused by transient spikes in the fault simulation.

[0084] Normalization. This ensures that metrics from different dimensions can be uniformly incorporated into the cost function. The normalization process is shown below. The formula is:

[0085] .

[0086] in, This represents the normalized system stability index. This represents the system stability index before normalization. This represents the maximum value of the system stability index. This represents the minimum value of the system stability index.

[0087] In summary, the system stability index can be obtained. :

[0088] .

[0089] in, , , , , These are the weighting coefficients for the corresponding items. Each weight can be allocated according to the system's focus, such as by adjusting based on experience.

[0090] S2.2: Set new energy consumption targets.

[0091] In one specific implementation, some enterprise standards define new energy accommodation capability (NEAC) as: under certain conditions of renewable energy resources and grid-connected capacity, conventional power generation capacity and load levels, the maximum installed capacity, maximum generating power, or maximum generating power percentage of renewable energy that the power system can accept, while meeting constraints such as reliable power supply, safe and stable operation, and economic efficiency. To measure the improvement effect of adding auxiliary equipment on the system's renewable energy accommodation capability, a renewable energy accommodation index is defined as... The renewable energy consumption index is the ratio of the maximum renewable energy output to the installed capacity of the system under the same short-circuit ratio. The higher this index, the stronger the equipment's ability to absorb renewable energy.

[0092] .

[0093] In the formula, This indicates the maximum power point at which stable grid connection can be obtained through simulation by gradually increasing the output after the equipment is installed. This indicates the total installed capacity of new energy sources.

[0094] The calculation condition is as follows: the system maintains the same short-circuit ratio, and the output of new energy sources is gradually increased until the system experiences voltage exceeding limits or frequency instability. This output is... .

[0095] right After normalization:

[0096] .

[0097] in, This represents the normalized indicator for new energy consumption. This represents the maximum value of the renewable energy consumption index. This represents the minimum value of the new energy consumption index.

[0098] S2.3: Set equipment cost indicators.

[0099] In one specific implementation, the equipment cost index serves as a penalty term in the comprehensive cost function, reflecting the economic constraints of different types of auxiliary equipment. A higher index indicates higher costs and thus penalizes the comprehensive cost function.

[0100] Considering the differences in cost, maintenance cost, and service life between energy-based SVG, non-energy-based SVG, and distributed synchronous condensers, this embodiment adopts a weighted investment model:

[0101] .

[0102] In the formula, Indicates equipment cost indicators, This indicates the unit capacity cost of each type of equipment. Indicates equipment capacity.

[0103] After normalizing the equipment cost indicators:

[0104] .

[0105] in, This represents the normalized equipment cost index. This represents the maximum value of the equipment cost index. This represents the minimum value of the equipment cost index.

[0106] By constructing the above indicators, a comprehensive evaluation framework can be formed that takes into account transient stability performance, voltage support, frequency support, economic efficiency, and the ability to absorb new energy sources.

[0107] More specifically, Table 1 compares the differences between different reactive power compensation devices.

[0108]

[0109] As shown in Table 1, different reactive power compensation devices differ in the following aspects: initial cost, operation and maintenance cost, and service life. Therefore, this embodiment adopts a life-cycle weighted investment model.

[0110] .

[0111] This represents the comprehensive cost index of the equipment, indicating the overall economic cost of the k-th type of reactive power compensation equipment over its entire life cycle. It consists of three items. The first item is the initial investment cost. This indicates the unit capacity cost of each type of equipment. The first item indicates the equipment's configured capacity. For the same capacity, a higher unit capacity cost results in a higher equipment purchase cost. The second item is the calculation of operation and maintenance costs. This represents the maintenance cost weighting factor. This indicates the annual maintenance cost per unit capacity. The third item is the depreciation cost based on lifespan. This represents the lifespan depreciation weighting factor. This indicates the lifespan of the equipment. For equipment of the same capacity, the longer the lifespan, the lower the cost per unit year. Therefore, the lifespan depreciation item reflects long-term economic efficiency.

[0112] In addition, due to the different unit capacity costs of different equipment Their operational characteristics, lifespan, and other features differ significantly.

[0113] Unit capacity cost: Energy-type SVG includes an energy storage system. Maximum; non-energy-type SVG only includes the power electronics portion. Medium; the synchronous condenser is a large rotating machine. Relatively high.

[0114] Maintenance characteristics: Due to frequent mechanical wear, lubrication, and maintenance, synchronous condensers... Maximum; Energy-type SVG requires battery replacement and thermal management maintenance. Medium; non-energy-type SVG modular electronics require less maintenance. Minimum.

[0115] Lifespan difference: The lifespan of a camera adjustment unit can reach 25–30 years. Maximum output, lowest cost per unit; non-energy SVG lifespan is approximately 15–20 years. Medium-energy SVG is limited by battery life of approximately 8–12 years. The smallest, but with the highest conversion cost.

[0116] Therefore, this embodiment adopts a life-cycle weighted investment model that includes three parts: initial investment, operation and maintenance costs, and lifetime depreciation. This model ensures that the differences in cost structure, maintenance requirements, and lifetime characteristics of different types of reactive power compensation equipment (energy-type grid SVG, non-energy-type grid SVG, and distributed synchronous condensers) can be uniformly mapped to a comprehensive cost index. The model in this embodiment achieves this: the differences between different equipment are not artificially differentiated, but automatically adapted through parameter mapping. This improves the engineering applicability and comparability of capacity optimization results.

[0117] S3: Set a comprehensive cost function based on the influence relationship between various indicators in the multi-dimensional indicator system.

[0118] S3.1: Set the comprehensive cost function.

[0119] In one specific implementation, in power systems with a high proportion of renewable energy integration, system stability, absorption capacity, and economic efficiency are often coupled and constrained. For example, a decrease in SCR (Saturated Voltage Regulator) leads to a decrease in TVR (Transient Voltage Regulator), thus lowering the absorption limit. Increasing NEAC (Non-Reactive Power Regulator) leads to increased reactive power demand, thus increasing cost and stability pressures. Reducing costs, on the other hand, leads to insufficient capacity, further increasing the risk of transient instability. Therefore, based on the coupling and constraint relationships among these three factors, this embodiment designs a comprehensive cost function formula as follows:

[0120] .

[0121] in, For the comprehensive cost function, Indicates the capacity of the devices installed in the system. , , These are system stability indicators New energy consumption capacity indicators and equipment cost indicators The weighting coefficients satisfy the following constraints: By adjusting the weighting coefficients, a balance can be struck between system stability, economy, and absorption capacity, depending on the research focus.

[0122] Coupling terms This is used to characterize the combined effect of insufficient stability and insufficient absorption. The weighting coefficients of the coupling terms are adjusted based on engineering experience.

[0123] Among them, the weighting coefficient , , and It is not fixed, but dynamically adjusted based on the constraints through a weighted adaptive mechanism.

[0124] The weight adaptation mechanism in this embodiment:

[0125] ,

[0126] .

[0127] .

[0128] in, It represents the active power output level of all new energy sources in the system. The higher the output of new energy sources, the greater the reactive power demand of the system, the more drastic the fluctuations, and the more unstable the voltage and frequency. for The standard deviation represents the degree of volatility in the output of new energy sources. This represents the output of the new energy source at time t. This represents the average output within the time window, and T represents the length of the statistical window.

[0129] and They are respectively and The initial value of . The meaning of represents the stability weight adjustment gain coefficient, which can be determined in the following ways: set according to power grid operation experience; calibrated through offline sensitivity analysis; or obtained through historical fault simulation fitting. The weighting gain coefficient for absorption capacity can be determined based on the fluctuation range of new energy output. For example, a larger value is used for wind power bases and a smaller value is used for photovoltaic smoothing areas.

[0130] When the power grid is weak (low SCR), the stability weight is increased; when the output of new energy sources fluctuates greatly, the absorption weight is increased. This gives the cost function scenario-awareness.

[0131] This embodiment uses an indicator coupling term and a weight adaptive adjustment mechanism to enable the optimization process to reflect the mutual constraint relationship between stability constraints and absorption capacity constraints in areas with high penetration of new energy sources, thus distinguishing it from the traditional independent indicator weighting scheme.

[0132] S3.2: Set constraints for the comprehensive cost function based on node voltage amplitude safety, active power balance, reactive power variation, and equipment capacity limits.

[0133] In one specific implementation, during the cost function optimization process, to ensure that the obtained results satisfy system operation constraints and engineering feasibility, the following constraints need to be introduced:

[0134] S3.2.1: The voltage amplitude of all nodes must be maintained within a safe range.

[0135] .

[0136] in, Let be the voltage amplitude at node i at time t. These represent the lower and upper limits of the allowable voltage at node i, respectively.

[0137] S3.2.2: Active power balance is the most fundamental constraint, requiring that power generation and power consumption (including network losses) be equal at any time.

[0138] .

[0139] in, The active power output of the h-th conventional generator at time t; The active power output of the j-th renewable energy power station at time t; Let t be the total system load. The active power loss of the power grid at time t (usually calculated through power flow): , These represent the number of traditional generators and new energy power stations, respectively.

[0140] Each generator (including thermal power, hydropower, wind power, photovoltaic, etc.) has an upper and lower limit for output.

[0141] .

[0142] in, Minimum technical output for the h-th generator (e.g., minimum output for stable combustion in a thermal power plant): This represents the maximum active power output of the h-th generator.

[0143] S3.2.3: Power flow and line capacity constraints: The power transmission of all lines in the power grid must not exceed their limits.

[0144] ,

[0145] .

[0146] in, Let be the active power flowing through line l at time t; This represents the thermal stability or stability limit of line l. Let be the power transfer distribution factor, representing the power flow change on line l caused by injecting 1 unit power at node i. New energy challenge: The power transfer distribution factor at the new energy injection point (node ​​i) is... When the value is too high, it can easily cause a certain line l to... That is, the transmission resistance plug.

[0147] S3.2.4: Backup capacity constraint: The system needs to maintain sufficient power generation capacity to cope with emergencies.

[0148] ,

[0149] .

[0150] in, The required upward reserve capacity at time t (to cope with sudden load increases or sudden drops in new energy output). Downward reserve capacity required at time t (to cope with sudden load drops or sudden increases in renewable energy output). Renewable energy challenges: Due to the uncertainty of renewable energy forecasting, and The demand has increased significantly.

[0151] S3.2.5: Changes in the penetration rate of new energy sources alter the short-circuit capacity of the power grid. Short-circuit capacity constraints need to be set based on changes in the number of new energy sources connected to the system that cause changes in short-circuit capacity and the minimum short-circuit capacity of the system.

[0152] .

[0153] in, This refers to the operating status of the new energy unit q. The minimum short-circuit capacity required for bus f. for The correction factor is k, where k is the total number of wind turbines and photovoltaic units. M represents the short-circuit capacity provided by unit q to bus f, and M represents the number of hybrid synchronous condensers. Contribution of short-circuit current to each group of hybrid synchronous condensers.

[0154] S3.2.6: The reactive power demand of the system changes with the change in the penetration rate of new energy sources. It is necessary to set reactive power constraints based on the changes in reactive power caused by the change in the number of new energy sources connected to the system and the reactive power output constraints of new energy sources.

[0155] .

[0156] in, , , , These are the minimum and maximum reactive power outputs of wind turbines and photovoltaic power units, respectively. and The minimum and maximum reactive power that the reactive power compensation equipment can generate are given. , , These refer to the reactive power of wind turbines, photovoltaic units, and reactive power compensation equipment, respectively. The number of wind turbine units. M represents the number of photovoltaic units and M represents the number of reactive power compensation devices.

[0157] S4: Solve the objective function to obtain the optimal capacity configuration result.

[0158] In one specific implementation, the ultimate optimization objective is:

[0159] .

[0160] This embodiment calculates the cost function values ​​for different auxiliary devices and their capacities through simulation, and uses MATLAB or other optimization tools to perform curve fitting on the results to obtain the cost function values ​​for various types of devices. The changing trend of the cost function. When the cost function reaches its minimum value, the corresponding capacity... This represents the optimal configuration capacity. At this point, the system can maximize its renewable energy absorption capacity while meeting stability and voltage constraints; achieve optimal system voltage and frequency stability; and minimize equipment investment costs.

[0161] Example 2:

[0162] Embodiment 2 of the present invention provides a reactive power compensation device capacity configuration system for areas with a high proportion of renewable energy, including:

[0163] The data acquisition module is used to acquire the operating parameters of reactive power compensation equipment in areas with high penetration rates of new energy systems, and to preprocess the operating parameters.

[0164] The indicator system construction module is used to construct a multi-dimensional indicator system based on the operating parameters of reactive power compensation equipment, taking into account the system's stability, absorption capacity, and cost. The multi-dimensional indicator system includes system stability indicators, new energy absorption capacity indicators, and equipment cost indicators.

[0165] The objective function setting module is used to set the comprehensive cost function based on the influence relationship between various indicators in a multi-dimensional indicator system.

[0166] The capacity configuration optimization module is used to solve the objective function to obtain the optimal capacity configuration result.

[0167] Example 3:

[0168] Embodiment 3 of the present invention provides a computer-readable storage medium storing a computer program adapted for loading by a processor and executing the steps in the reactive power compensation device capacity configuration method for high-proportion renewable energy areas as described in Embodiment 1 of the present invention.

[0169] Example 4:

[0170] Embodiment 4 of the present invention provides a computer device, the device comprising:

[0171] A processor, adapted to execute computer programs;

[0172] A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the steps in the reactive power compensation device capacity configuration method for high-proportion renewable energy areas as described in Embodiment 1 of the present invention.

[0173] Example 5:

[0174] Embodiment 5 of the present invention provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps in the reactive power compensation device capacity configuration method for high-proportion renewable energy areas as described in Embodiment 1 of the present invention.

[0175] The steps and methods involved in Examples 2, 3, 4 and 5 above correspond to those in Example 1. For specific implementation details, please refer to the relevant description section of Example 1.

[0176] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0177] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data processing device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, an optical medium, or a semiconductor medium, etc.

[0178] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for configuring reactive power compensation device capacity in areas with a high proportion of renewable energy, characterized in that: Includes the following steps: Obtain the operating parameters of reactive power compensation equipment in areas with high penetration rates of new energy systems, and preprocess the operating parameters; Based on the operating parameters of the reactive power compensation equipment, a multi-dimensional indicator system is constructed considering the system's stability, absorption capacity, and cost. The multi-dimensional indicator system includes system stability indicators, new energy absorption capacity indicators, and equipment cost indicators. System stability indices are used to comprehensively reflect the system’s transient steady-state performance under disturbances, including voltage support capability and frequency support capability. Voltage support capability is characterized by short-circuit ratio, transient voltage recovery index and transient voltage peak index, while frequency support capability is characterized by frequency change rate and maximum frequency offset in the initial stage of disturbance. A comprehensive cost function is set based on the influence relationship between various indicators in a multi-dimensional indicator system; The formula for the comprehensive cost function is: ， in, For the comprehensive cost function, Indicates the capacity of the devices installed in the system. , , These are system stability indicators New energy consumption capacity indicators and equipment cost indicators The weighting coefficients satisfy the following constraints: Coupling terms This is used to characterize the combined effect of insufficient stability and insufficient absorption. The weighting coefficients of the coupling terms; Weight adaptive mechanism: ， ， ， in, Indicates the short-circuit ratio. This represents the active power output level of all renewable energy sources in the system. The higher the renewable energy output, the greater the reactive power demand of the system, the more drastic the fluctuations, and the more unstable the voltage and frequency. for The standard deviation of this represents the degree of volatility in new energy output. This represents the output of the new energy source at time t. This represents the average output within the time window, and T represents the length of the statistical window. and They are respectively and initial value, The meaning of represents the stability weight adjustment gain coefficient. This represents the gain coefficient for weighted adjustment of absorption capacity; The optimal capacity configuration is obtained by solving the objective function.

2. The method for configuring reactive power compensation device capacity in areas with a high proportion of renewable energy sources as described in claim 1, characterized in that, The renewable energy consumption index is the ratio of the maximum renewable energy output to the installed capacity of the system under the same short-circuit ratio.

3. The method for configuring reactive power compensation device capacity in areas with a high proportion of renewable energy sources as described in claim 1, characterized in that, The equipment cost index, as a penalty term in the comprehensive cost function, is used to comprehensively reflect the economic constraints of different types of auxiliary equipment.

4. The method for configuring reactive power compensation device capacity in areas with a high proportion of renewable energy sources as described in claim 1, characterized in that, The constraints of the comprehensive cost function are set based on node voltage amplitude safety, active power balance, reactive power variation, and equipment capacity limits.

5. A reactive power compensation device capacity configuration system for areas with a high proportion of renewable energy, characterized in that: include: The data acquisition module is used to acquire the operating parameters of reactive power compensation equipment in areas with high penetration rates of new energy systems, and to preprocess the operating parameters. The indicator system construction module is used to construct a multi-dimensional indicator system based on the operating parameters of reactive power compensation equipment, taking into account the system's stability, absorption capacity, and cost. The multi-dimensional indicator system includes system stability indicators, new energy absorption capacity indicators, and equipment cost indicators. System stability indices are used to comprehensively reflect the system’s transient steady-state performance under disturbances, including voltage support capability and frequency support capability. Voltage support capability is characterized by short-circuit ratio, transient voltage recovery index and transient voltage peak index, while frequency support capability is characterized by frequency change rate and maximum frequency offset in the initial stage of disturbance. The objective function setting module is used to set the comprehensive cost function based on the influence relationship between various indicators in a multi-dimensional indicator system. The formula for the comprehensive cost function is: ， in, For the comprehensive cost function, Indicates the capacity of the devices installed in the system. , , These are system stability indicators New energy consumption capacity indicators and equipment cost indicators The weighting coefficients satisfy the following constraints: Coupling terms This is used to characterize the combined effect of insufficient stability and insufficient absorption. The weighting coefficients of the coupling terms; Weight adaptive mechanism: ， ， ， in, Indicates the short-circuit ratio. This represents the active power output level of all renewable energy sources in the system. The higher the renewable energy output, the greater the reactive power demand of the system, the more drastic the fluctuations, and the more unstable the voltage and frequency. for The standard deviation of this represents the degree of volatility in new energy output. This represents the output of the new energy source at time t. This represents the average output within the time window, and T represents the length of the statistical window. and They are respectively and initial value, The meaning of represents the stability weight adjustment gain coefficient. This represents the gain coefficient for weighted adjustment of absorption capacity; The capacity configuration optimization module is used to solve the objective function to obtain the optimal capacity configuration result.

6. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the reactive power compensation device capacity configuration method for high-proportion renewable energy regions as described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted to be loaded by a processor and executed as described in any one of claims 1-4, for the configuration of reactive power compensation device capacity in areas with a high proportion of renewable energy.

8. A computer device, characterized in that, include: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the method for configuring the capacity of reactive power compensation devices in areas with a high proportion of renewable energy as described in any one of claims 1-4.

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