32results about How to "Reduce active network loss" patented technology

The invention discloses an operation optimization method for a power distribution network comprising a schedulable distributed power supply. The method comprises the following steps: inputting initial values of a line parameter, load level, network topology connection relationship, a distributed power supply connection position, a power factor, reference voltage and reference power according to a given power distribution system comprising the schedulable distributed power supply; establishing a mathematical model for an operation optimization problem of the power distribution network comprising the schedulable distributed power supply according to all the parameters; introducing a variable to perform indirect description on a branch switch state: when branch ij is disconnected, keeping the variable equal to zero, and when the branch ij is connected, keeping the variable equal to Xi; setting rotating cone constraint according to the network structure and scale; solving the mathematical model for the operation optimization problem of the power distribution network comprising the schedulable distributed power supply, an inequality for performing indirect description on the branch switching state and the rotating cone constraint by using a cone optimization method; and outputting a solving result. According to the method, the economy and the reliability for operation of the power distribution system are further improved, and simultaneous optimization of output power of a plurality of distributed power supplies is realized.

The invention provides a reactive voltage optimal control method for a wind power plant cluster. The reactive voltage optimal control method comprises the steps that whether the reactive voltage optimal control for the wind power plant cluster needs to be carried out or not is judged; the reactive source equipment adjustment range of wind power plants and a pooling station in the wind power plant cluster region is obtained; and a reactive voltage optimal control mathematic model for the wind power plant cluster is built and solved. According to the reactive voltage optimal control method, a wind power plant cluster access point is used as a central voltage control node, the wind power plant grid-tied point bus voltage of the cluster region and a transformer tap of a booster station of the wind power plant are regulated, reactive compensation equipment of the pooling station is regulated to have reactive power, and a transformer tap of the pooling station is also regulated, the pilot node is enabled to meet the control instruction range of a dispatching mechanism, meanwhile the quiescent voltage stability margin of the cluster region is enabled to be maximum, and the active power transmission loss is enabled to be minimum; the quiescent voltage stability margin in the wind power plant cluster region can be effectively improved, the grid active loss in the cluster region also can be reduced, the operating safety and stability of a system are improved, and the capacity of digesting and saving wind power of the system is also improved.

The invention discloses an offshore wind plant reactive power optimization configuration method considering wind turbine generator reactive power regulation. The method specifically comprises the steps of selecting compensation points and compensation modes according to the capacity and the conveying distance of an offshore wind plant; establishing an offshore wind plant equivalent model, optimizing the compensation capacity and the grouping number of high-voltage shunt reactors according to reactive requirements of the offshore wind plant at different active output levels, and formulating a PDFIG-n table; according to the requirements of offshore wind plant grid connection technical specifications for voltage, optimizing the compensation capacity of an SVG device through dynamic simulation, and ensuring transient voltage stability; and according to the optimized compensation capacity, coordinating and optimizing the reactive power output of the wind turbine generator and a reactive power compensation device by taking static voltage stability and low operation cost as targets and utilizing the reactive power regulation capability of the wind turbine generator. According to the method, the static and transient voltage stability of the offshore wind power plant is considered, the reactive power regulation capability of the wind turbine generator is fully utilized, and the economyand safety of a reactive power configuration scheme are improved.

The invention relates to the field of distributed energy resource access, and specifically a power network reconfiguration method for optimizing a distributed energy access point and an access proportion. The method comprises the following steps: adopting an adaptive weight particle swarm optimization algorithm, a Newton-Raphson method and a power distribution network reconfiguration method to perform an optimal reconfiguration on the power network in the presence of distributed energy resources, analyzing two or more access point optimal selection method, access active capacity calculation method and calculation method of system power flow before and after access when the distributed energy resources (wind power, photovoltaic energy) are accessed to a system; and adjusting the wind power and photovoltaic distributed energy resource access points and access proportions, analyzing the impact of different access proportions on the system economy and giving a system optimization measure. The method is applied to an IEEE-14 node model and an IEEE-30 node model, the reconfiguration result is analyzed, and optimum access points and access proportions of two distributed energy resources can be obtained; after a reconfiguration network is optimized, the network loss is the minimum and the reactive power output is reasonable, the economy of the system is improved and the voltage level satisfies the requirement of stable operation.

The invention provides an operating regulation computing method for an active power distribution network participated by an energy storage system. For the energy storage system which is formed by a storage battery, the minimum active loss of the power distribution network system is taken as the target function; the operating constraints which comprise system power flow constraint, operating voltage constraint, branch circuit constraint and energy storage system operating constraint, of the system are taken into consideration; the computational example is solved by a particle swarm optimization; and finally, the charging-discharging power of the energy storage system under each time frame is output to be used as the optimal solution under the premise that the reliability of the system is satisfied. Compared with the conventional method, the active power loss of the power distribution network system can be effectively reduced; the operating cost of the power grid can be lowered; and the utilization efficiency of the photovoltaic energy can be increased.

The invention relates to a multi-target probabilistically optimal power flow fuzzy modelling and solving method for a power distribution network. The multi-target probabilistically optimal power flow fuzzy modelling and solving method comprises the following steps: obtaining n (n is less than t) random variables in t nodes in a network, and establishing a random variable model; obtaining 2<n> sample points corresponding to the n random variables and weighting coefficients omega<1> and k corresponding to the sample points by adopting a two-point estimation method; establishing a multi-target probabilistically optimal power flow nonlinear programming model; converting the multi-target probabilistically optimal power flow model into a single-target nonlinear programming model on the basis of a fuzzy set theory, and obtaining optimal power flow values Z<1> and k corresponding to the 2<n> sample points; and obtaining origin moments of various orders of an optimal power flow Z. According to the multi-target probabilistically optimal power flow fuzzy modelling and solving method provided by the invention, the random distributed power supply output problem is solved by adopting a point estimation method; therefore, the probabilistically optimal power flow problem is converted into deterministic optimal power flow calculation and characteristic value statistics; various samples are calculated by adopting the multi-target optimal power flow modelling and solving method respectively; and thus, the statistical characteristic value of a probabilistically optimal power flow can be finally obtained.

The invention discloses a multi-source reactive power optimization control method for a power system. The multi-source reactive power optimization control method main comprises day-ahead optimization scheduling and intraday optimization correction, wherein the day-ahead optimization scheduling comprises the following steps: building a day-ahead optimization scheduling model according to parameters of the power system, obtaining day-ahead reactive power scheduling plans of a shunt capacitor bank and transformer taps in a power grid by the model, and providing the day-ahead reactive power scheduling plans of the shunt capacitor bank and the transformer taps in the power grid for the intraday optimization correction; the intraday optimization correction is updating scheduling information of the shunt capacitor bank and the transformer taps in the power grid by the day-ahead reactive power scheduling plans in real time; a real-time optimization scheduling scheme of an electric vehicle charging pile for intraday normal operation is obtained through the built optimization module for intraday normal operation or a reactive voltage optimization control scheme for the shunt capacitor bank in intraday fault operation is obtained according to the optimization module for intraday fault operation; and finally the optimization regulation and control of an intraday reactive power source are achieved.

The invention discloses a reactive voltage control method considering dynamic reactive power reserves of partitions and belongs to the technical field of power system optimized operation. The method comprises the steps of determining the reactive voltage control partitions of the power grid and identifying the key node of each partition, calculating the VQ curve of the key nodes and the dynamic reactive power reserves of the partitions, calculating the minimum reactive power reserve limiting value needed by each partition under the most serious failure, establishing a reactive voltage control model with the total dynamic reactive power reserve of the system as an optimization goal and the minimum reactive power reserve limiting value needed by each partition under the most serious failure as a constraint condition, and solving the reactive voltage control model. According to the reactive voltage control method, the reactive voltage control model contains the system total dynamic reactive power reserve optimized item and the minimum reactive power reserve limiting value constraint of each partition is established to balance the distribution of the dynamic reactive power reserve of each partition, and therefore, the voltage collapse phenomenon is avoided, and meanwhile, the purposes of reducing the active grid loss of the system, improving the voltage quality and enhancing the system voltage stability are achieved.

The invention relates to a reactive power optimization method of a photovoltaic system based on a quantum particle swarm algorithm, belonging to the technical field of reactive power regulation of a photovoltaic power station. The method of the invention comprises the following steps: (1) analyzing the influence of grid-connected photovoltaic power station on the voltage of the distribution network system; 2, establishing a mathematical model for optimizing that reactive power compensation of a distribution network of a photovoltaic power station; Step 3, solving the reactive power optimization model of the photovoltaic system by using the quantum particle swarm optimization algorithm. The reactive power optimization method of the photovoltaic system based on the quantum particle swarm algorithm provided by the invention can effectively reduce the active power network loss, obviously increase the voltage value of each node, and enable the distribution network system to run more economically and stably.

The invention discloses a wind power system reactive power planning method based on the golden section cloud particle swarm optimization algorithm. The wind power system reactive power planning method comprises the steps that a reactive power planning mathematic model is built, and a target function is determined; original data of a wind power system is input, and therefore an initial population is formed; all particles are generated randomly, a golden section judging criterion is used for dividing a particle swarm into three parts according to the self-fitness value of the particle swarm, and different inertia weight is set for each part of particles; new positions and speeds of the particles are obtained through the particle swarm optimization algorithm, the particles are divided into three parts and iterated repeatedly according to the method before an the end condition is met, an optimal solution is searched, and therefore reactive power planning of the wind power system is achieved. According to the wind power system reactive power planning method based on the golden section cloud particle swarm optimization algorithm, the node voltage level of the wind power system is effectively improved, network loss of a power network is reduced, the diversity of the particles is kept according to the algorithm, the prematurity phenomenon which easily occurs during optimization searching is avoided, and convergence rate in the optimization searching process is improved. In addition, the wind power system reactive power planning method based on the golden section cloud particle swarm optimization algorithm is small in calculated amount, and higher in operability.

The invention discloses a reactive power optimization method for a photovoltaic reactive power partition pricing power distribution network, and the method comprises the steps: proposing a controllable photovoltaic reactive power partition pricing model, taking the minimum reactive comprehensive cost and the minimum deviation between active power loss and voltage as optimization targets, and constructing a power distribution network active-reactive power optimization model including response PV inverter reactive partition electricity price, static Var compensator (SVC) dynamic compensation, on-load voltage regulation equipment OLTC tap and capacitor bank switching; and processing nonlinear terms in the model by adopting mathematical means such as second-order cone programming and a large Mmethod, finally obtaining a mixed integer second-order cone programming model of active-reactive coordination optimization of the power distribution network containing controllable photovoltaic in the power market environment, and segmenting and solving the model by adopting a Benders decomposition method. According to the invention, the reactive capacity of a photovoltaic inverter and the reactive support capability of original discrete equipment of a distribution network are reasonably and coordinately utilized, the active power loss is reduced, and the user voltage quality is ensured.

The invention discloses an advanced wattless power compensation method of power transformation engineering and relates to the power distribution engineering field. The advanced wattless power compensation method includes the following ten steps of initialization, coding, power flow calculation, fitness value calculation, selection operation, crossover operation, mutation operation, local optimal judgment, catastrophe strategy execution and termination criteria execution. The method is an improved type power grid wattless power optimization compensation method based on a genetic algorithm. According to the method, the selection operation, the crossover operation and the mutation operation are further improved, and therefore, premature convergence of the algorithm to obtain a local optimal solution can be avoided, and convergence can be speeded up; and the defect of proneness to falling into a dead cycle by using a heuristic method can be eliminated. With the advanced wattless power compensation method adopted, the difficulty to obtain an optimal solution can be greatly decreased; guarantee can be provided for the execution of the algorithm; active power loss of a power grid system can be effectively decreased; the time of iteration is short, and the frequency of the iteration is low; and efficiency is high.

Embodiments of the present invention provide an improved leapfrogging algorithm-based power grid reactive power optimization method and a device thereof, and relate to the technical field of the power system planning technology. The method and the device are applied to the reactive power optimization of a power distribution network. In this way, the better convergence and the higher degree of optimization are realized. The method comprises the steps of obtaining the control variables of the power distribution network and the state variables of the power distribution network; obtaining a specified number of frog individuals and frog populations corresponding to each of all the specified number of frog individuals; according to the frog populations, obtaining an initial reactive voltage; according to the initial reactive voltage, obtaining the optimum value of a local reactive voltage; and obtaining an optimal solution of a global reactive voltage according to the optimum value of the local reactive voltage. The optimal solution of the global reactive voltage is applied to the reactive power optimization of the power distribution network. The method and the device are used for the reactive configuration of the power distribution network.

The invention discloses a data network load distribution method for data centers capable of reducing power grid loss. According to work frequency and a utilization rate of a server CPU in the data center, energy consumption of each data center is acquired, and data network load condition and power network load condition in a next period are predicted, and under unified scheduling of a power grid, network load distribution of the data centers is controlled, so that power grid tide distribution is improved, active network loss of the system is reduced, an optical distribution scheme for data network load between the data centers is found, significant loss reduction benefit is achieved, electricity consumption of the data centers are included into the scope of improving the state of the power network as a resource, and thus good application prospects are provided.

The invention discloses a reactive power optimization method based on a stochastic load flow with consideration of photovoltaic power generation and harmonic pollution, which belongs to the technical field of optimization of electric systems and power distribution systems. The reactive power optimization method based on the stochastic load flow with the consideration of the photovoltaic power generation and the harmonic pollution disclosed by the invention considers multiple stochastic factors in running of a power distribution network such as uncertainty of load fluctuations, failure outage of a generator set and randomness of output of a photovoltaic power station, calculates results of the stochastic load flow through Monte Carlo simulation and then carries out reactive power optimization. During the reactive power optimization, a terminal voltage of a generator, the position of a tapping point of an adjustable transformer, a reactive power compensation amount of an reactive power compensation device, and reactive power capacity of the photovoltaic power station are optimized and controlled by a genetic algorithm, chance constraint is carried out to a fundamental voltage of a system node and a total harmonic distortion rate of a node voltage, and reduction of active power losses and the harmonic pollution is considered comprehensively in order to increase economical efficiency and safety of the running of the power distribution network.

The invention provides a reactive optimization method and system of a power system. The method comprises the steps: inputting power grid information data and relevant algorithm parameters, acquiring the voltage at a power generator end, a compensation capacitance value of a reactive compensation device and a transformation ratio of a transformer branch to form a control variable, generating an initial population, substituting each vector in the initial population into a Newton-Raphson method to calculate the reactive power of a voltage power generator node of each node in a load flow manner, calculating a fitness value, carrying out the mutation operation, carrying out the interlace operation of a covariance matrix learning mechanism, carrying out the selection operation, calculating each test vector fitness value, if the test vector fitness value is smaller than a target vector fitness value, reserving the test vector, entering a next generation of population, keeping a corresponding zoom factor and an interlace control parameter unchanged, entering the next generation, otherwise, allowing the target vector to directly enter the next generation, and generating a next generation of zoom factor and interlace control parameter according to a dual-peak distribution parameter; and when a maximum iteration times is achieved, outputting a final optimization result.

The invention discloses a multi-power-supply reactive power cooperation method and system for optimizing the voltage control capability of a wind power plant, and the method comprises the steps: determining the topological structure of the wind power plant, and carrying out the classification according to the node type of each node in the topological structure, so as to obtain a plurality of nodesets; for nodes in each node set, respectively determining equality constraint conditions based on reactive power of an alternating current line; determining equality constraint conditions based on active power and voltage of a wind power plant grid-connected point; determining upper and lower limit constraint conditions of each node voltage in the wind power plant and upper and lower limit constraint conditions of reactive power of each power generation unit according to operation requirements of a wind turbine generator and a reactive power compensation device SVG; and determining an objective function of multi-power-supply optimal reactive power output in the wind power plant, and determining reactive power output of each wind turbine generator set and the SVG. According to the invention, the active loss of the SVG and the active network loss of the power transmission line in the wind power plant can be reduced, the reactive voltage coordination control capability of the new energyplant station is improved, and the overall economic benefit of the wind power plant is improved.

The invention discloses a reactive power optimization method based on a stochastic load flow with consideration of photovoltaic power generation and harmonic pollution, which belongs to the technical field of optimization of electric systems and power distribution systems. The reactive power optimization method based on the stochastic load flow with the consideration of the photovoltaic power generation and the harmonic pollution disclosed by the invention considers multiple stochastic factors in running of a power distribution network such as uncertainty of load fluctuations, failure outage of a generator set and randomness of output of a photovoltaic power station, calculates results of the stochastic load flow through Monte Carlo simulation and then carries out reactive power optimization. During the reactive power optimization, a terminal voltage of a generator, the position of a tapping point of an adjustable transformer, a reactive power compensation amount of an reactive power compensation device, and reactive power capacity of the photovoltaic power station are optimized and controlled by a genetic algorithm, chance constraint is carried out to a fundamental voltage of a system node and a total harmonic distortion rate of a node voltage, and reduction of active power losses and the harmonic pollution is considered comprehensively in order to increase economical efficiency and safety of the running of the power distribution network.

The invention provides an active power distribution network energy optimization method and device adopting a power spring. The method comprises the following steps: acquiring input data of an active power distribution network; wherein the input data of the active power distribution network comprise a non-critical load power factor; according to the non-critical load power factor, determining an active power adjustment range based on a power spring flexible load; inputting the active power distribution network input data and the active power adjustment range based on the power spring flexible load into a preset active power distribution network energy optimization model to generate an optimization output result; wherein the preset active power distribution network energy optimization model comprises a constraint condition based on a power spring flexible load. According to the method, the power spring is used as a load adjusting medium, the voltage quality of the active power distribution network is improved, the active power loss and the operation cost of the active power distribution network are reduced, the operation benefit of the micro-grid is improved, and the correctness and the effectiveness of active power distribution network capability optimization are greatly improved.

The invention discloses a method for optimizing a configuration place and optimal compensation capacity of reactive equipment of a power system. The method comprises the following steps: setting powersystem parameters; obtaining a voltage stability sequence of load nodes of the power system according to the local voltage stability L index, and taking the nodes with low stability as reactive compensation nodes; initializing parameters; calculating a particle fitness value; updating the particle swarm; according to the updated particle swarm, obtaining a particle individual optimal value and aglobal optimal value of the current swarm through genetic operator operation to serve as the optimal compensation capacity of the reactive power equipment; and judging whether a calculation result reaches convergence precision or the maximum iteration frequency, if YES, outputting the currently calculated optimal compensation capacity of the reactive power equipment as the installation capacity, and if NO, updating the particles, returning to calculate the particle fitness value again, calculating the fitness value again, and updating the particle swarm. According to the invention, the configuration place and the optimal compensation capacity of the reactive power equipment of the power system can be quickly and effectively obtained.

The invention discloses a wind power system reactive power planning method based on the golden section cloud particle swarm optimization algorithm. The wind power system reactive power planning method comprises the steps that a reactive power planning mathematic model is built, and a target function is determined; original data of a wind power system is input, and therefore an initial population is formed; all particles are generated randomly, a golden section judging criterion is used for dividing a particle swarm into three parts according to the self-fitness value of the particle swarm, and different inertia weight is set for each part of particles; new positions and speeds of the particles are obtained through the particle swarm optimization algorithm, the particles are divided into three parts and iterated repeatedly according to the method before an the end condition is met, an optimal solution is searched, and therefore reactive power planning of the wind power system is achieved. According to the wind power system reactive power planning method based on the golden section cloud particle swarm optimization algorithm, the node voltage level of the wind power system is effectively improved, network loss of a power network is reduced, the diversity of the particles is kept according to the algorithm, the prematurity phenomenon which easily occurs during optimization searching is avoided, and convergence rate in the optimization searching process is improved. In addition, the wind power system reactive power planning method based on the golden section cloud particle swarm optimization algorithm is small in calculated amount, and higher in operability.

The invention discloses a multi-source reactive power optimization control method for a power system. The multi-source reactive power optimization control method main comprises day-ahead optimization scheduling and intraday optimization correction, wherein the day-ahead optimization scheduling comprises the following steps: building a day-ahead optimization scheduling model according to parameters of the power system, obtaining day-ahead reactive power scheduling plans of a shunt capacitor bank and transformer taps in a power grid by the model, and providing the day-ahead reactive power scheduling plans of the shunt capacitor bank and the transformer taps in the power grid for the intraday optimization correction; the intraday optimization correction is updating scheduling information of the shunt capacitor bank and the transformer taps in the power grid by the day-ahead reactive power scheduling plans in real time; a real-time optimization scheduling scheme of an electric vehicle charging pile for intraday normal operation is obtained through the built optimization module for intraday normal operation or a reactive voltage optimization control scheme for the shunt capacitor bank in intraday fault operation is obtained according to the optimization module for intraday fault operation; and finally the optimization regulation and control of an intraday reactive power source are achieved.

The invention relates to the field of distributed energy resource access, and specifically a power network reconfiguration method for optimizing a distributed energy access point and an access proportion. The method comprises the following steps: adopting an adaptive weight particle swarm optimization algorithm, a Newton-Raphson method and a power distribution network reconfiguration method to perform an optimal reconfiguration on the power network in the presence of distributed energy resources, analyzing two or more access point optimal selection method, access active capacity calculation method and calculation method of system power flow before and after access when the distributed energy resources (wind power, photovoltaic energy) are accessed to a system; and adjusting the wind power and photovoltaic distributed energy resource access points and access proportions, analyzing the impact of different access proportions on the system economy and giving a system optimization measure. The method is applied to an IEEE-14 node model and an IEEE-30 node model, the reconfiguration result is analyzed, and optimum access points and access proportions of two distributed energy resources can be obtained; after a reconfiguration network is optimized, the network loss is the minimum and the reactive power output is reasonable, the economy of the system is improved and the voltage level satisfies the requirement of stable operation.

The invention discloses a multi-power-supply reactive power cooperation method and system for optimizing the voltage control capability of a photovoltaic power station. The method comprises the stepsof determining a topological structure of the photovoltaic power station, and classifying the nodes according to the node type of each node in the topological structure so as to obtain a plurality ofnode sets; for the nodes in each node set, respectively determining the equality constraint conditions based on reactive power of an alternating current line; determining an equality constraint condition based on active power and voltage of a photovoltaic electric field grid-connected point; determining the upper and lower limit constraint conditions of each node voltage in the photovoltaic powerstation and the upper and lower limit constraint conditions of the reactive power of each power generation unit respectively according to the operation requirements of a photovoltaic inverter and a reactive power compensation device SVG; and determining an objective function of multi-power-supply optimal reactive power output in the photovoltaic power station, and determining the reactive power output of each photovoltaic inverter and SVG. According to the invention, the active loss of the SVG and the active network loss of the power transmission line in the photovoltaic power station can be reduced, and the reactive voltage coordination control capability of a new energy station is improved.

An optimization control method for a reactive voltage of a wind farm cluster comprises the following steps: determining whether it is required to perform optimization control on a reactive voltage of a wind farm cluster; obtaining adjusting ranges of reactive source devices of wind farms and pooling stations in a cluster area; and establishing and solving a reactive voltage optimization control mathematic model of the wind farm cluster. In the optimization control method for a reactive voltage of a wind farm cluster, a wind farm cluster access point is used as a central voltage control node, and the wind farm integration point bus voltage, the wind farm step-up substation tap, the reactive power output of a reactive compensation device of the pooling station, and the pooling station transformer tap in the cluster area are adjusted; in this way, the central node is ensured to satisfy the control instruction range of a scheduling mechanism, and the stability margin of the static voltage in the cluster area maintains at the maximum and the active power loss maintains at the minimum, thereby improving the security stability during system operation and enhancing the capability of utilization of the wind power.

The invention discloses a distribution network reactive power optimization method for photovoltaic reactive power partition pricing, which includes proposing a controllable photovoltaic reactive power partition pricing model, with the minimum reactive power comprehensive cost, the minimum active network loss and voltage deviation as the optimization target, Construct active-reactive power optimization model of distribution network including response to PV inverter reactive power partition price, static var compensator SVC dynamic compensation, on-load voltage regulation equipment OLTC tap and capacitor bank switching; adopt second-order cone programming The nonlinear terms in the model are processed by mathematical methods such as the large M method, and finally a mixed integer second-order cone programming model for the coordinated optimization of active and reactive power of the distribution network with controllable photovoltaics under the power market environment is obtained, and the Bund The Sri Lankan decomposition method solves the model segmentation. The invention rationally and coordinately utilizes the reactive power capacity of the photovoltaic inverter and the reactive power support capability of the original discrete equipment of the distribution network, reduces active power network loss, and ensures user voltage quality.

The invention discloses an operation optimization method for a power distribution network comprising a schedulable distributed power supply. The method comprises the following steps: inputting initial values of a line parameter, load level, network topology connection relationship, a distributed power supply connection position, a power factor, reference voltage and reference power according to a given power distribution system comprising the schedulable distributed power supply; establishing a mathematical model for an operation optimization problem of the power distribution network comprising the schedulable distributed power supply according to all the parameters; introducing a variable Xi<ij> to perform indirect description on a branch switch state: when branch ij is disconnected, keeping Xi<ij> to be equal to zero, and when the branch ij is connected, keeping Xi<ij> to be equal to Xi; setting rotating cone constraint according to the network structure and scale; solving the mathematical model for the operation optimization problem of the power distribution network comprising the schedulable distributed power supply, an inequality for performing indirect description on the branch switching state and the rotating cone constraint by using a cone optimization method; and outputting a solving result. According to the method, the economy and the reliability for operation of the power distribution system are further improved, and simultaneous optimization of output power of a plurality of distributed power supplies is realized.

The invention discloses a power distribution network reactive power optimization method and device based on data driving, and the method comprises the steps: inputting historical data into a preset lower-layer neural network for training, and obtaining a lower-layer training model and unmeasurable key node voltage data; inputting a preset upper neural network for training according to the acquired voltage data of the measurable nodes and the non-measurable key nodes of the target regional power grid and a preset switching state of discrete reactive power regulation equipment, and acquiring an upper training model and a switching action instruction of the discrete reactive power equipment; deploying the lower-layer training model and the upper-layer training model to a power distribution network in actual operation, and obtaining an overall operation model; and constructing a target function according to the operation network loss and the switching action instruction of the discrete reactive power equipment, solving the target function by adopting an A2C algorithm, and obtaining a reactive power optimization result of the power distribution network. According to the invention, the voltage distribution is optimized and the network loss is reduced by obtaining the overall operation model and combining the network loss and the switching action instruction.

The invention discloses an optimization method of an electric power system and relates to the technical field of electric power system reactive power optimization. The method includes the steps of (1)reading electric power system parameters and setting particle population parameters; (2) initializing the velocity and positions of population particles; (3) calculating load flow and fitness values;(4) calculating the dimensional diversity and inertia weight vectors; (5) performing iterative calculation and updating the velocity and position of a particle swarm; (6) calculating the load flow and the fitness values; (7) checking whether or not convergence conditions are satisfied; (8) determining whether or not an variation occurs; (9) performing a variability operation on a dimension the diversity of which is the worst. Through improvement of existing particle swarm optimization algorithms, the inertia weight vectors are introduced, the dimension diversity is calculated, dimension searching is refined, and the problem that the existing algorithms have a low convergence speed is solved. The active power network loss is effectively reduced, and a better global searching capability isachieved.