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Power system reactive power optimization method of wind power field

An optimization method and power system technology, applied in wind power generation, electrical components, circuit devices, etc., can solve the problems of complex fuzzy optimization algorithm to solve precise problems, no obvious improvement in calculation speed, trapped in local extreme values, etc. Excellent and global search ability, avoid falling into local optimum, improve the effect of voltage level

Pending Publication Date: 2016-10-12
任甜甜
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AI Technical Summary

Problems solved by technology

[0005] The disadvantage is that the simulated annealing algorithm and the genetic algorithm have many parameters, the parameter selection is more troublesome, and the dependence on the problem is too strong; the artificial neural network needs to invest in a large number of samples for training in the early stage, the self-learning cycle is long, and it is easy to fall into local extremum; Fuzzy optimization algorithm is too complicated to solve precise problems
Since it still boils down to a linear or nonlinear programming problem in the end, the calculation speed is not significantly improved, which will cause the model to become nonlinear and affect the calculation efficiency

Method used

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  • Power system reactive power optimization method of wind power field

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Embodiment Construction

[0018] The specific embodiment of the present invention will be described with reference to the accompanying drawings.

[0019] Analyze the actual data of Dabancheng wind farm in Xinjiang, and use PSASP to calculate the power flow according to the position information of each particle in the IEEE-30 node system, and calculate the active and reactive power flow of the line, the voltage amplitude, phase angle and active network loss of each node. As a result, preparations are made for reactive power optimization of subsequent nodal systems. Specific process such as figure 1 shown.

[0020] The improved differential evolution algorithm is applied to the reactive power optimization of the wind farm power system, and the optimization simulation calculation is carried out on the IEEE-30 node system. The simulation results can verify the feasibility and effectiveness of the differential evolution algorithm.

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Abstract

The invention relates to a reactive power optimization of a power system and specifically relates to a power system reactive power optimization method of a wind power field. The method includes random initialization of population, linear annealing weight introduction, gene fusion of genes of individuals in a new population and individual in a original population under a CR weight, target population generation, cross operation implementation, target individual fitness value calculation, one-to-one comparison of target individual fitness values and original individual fitness values, preferential saving, new population generation, and iteration search in the maximal evolution algebra range until the large evolution algebra is reached. According to the invention, dynamic adjustment is performed on parameters of a differential algorithm and a variation strategy of linear annealing is adopted for overlapped individuals in the population, so that a condition that the algorithm falls into local optimum is avoided, optimization and overall search capability are improved, the calculation time is shortened, influence on power grid reactive power distribution and voltage problems by the wind power field are eliminated, system grid loss is reduced and voltage level is improved.

Description

technical field [0001] The invention relates to a reactive power optimization method for a power system, in particular to a reactive power optimization method for a wind farm power system. Background technique [0002] Power system reactive power optimization refers to when the structural parameters and load conditions of the system are given, through the optimization of control variables, under all specified constraints, find the reactive power when one or more performance indicators of the system are optimal. means of adjustment. The purpose of reactive power optimization is to reduce the active network loss by adjusting the distribution of reactive power flow, and to ensure that the voltage is at the best level. Network loss, to achieve the smallest active network loss. Reactive power optimization is a multi-objective, multi-variable, multi-constraint hybrid nonlinear programming problem. The optimization variables include both continuous variables such as node voltages...

Claims

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Application Information

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IPC IPC(8): H02J3/50H02J3/38
CPCH02J3/386H02J3/50Y02E10/76
Inventor 任甜甜何颖朱晓明刘光辉张海丽朱婷婷马晓倩
Owner 任甜甜
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