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Smart Grid  2022 

基于粒子群算法的含风电系统多无功调控资源优化方法
Optimization Method for Multi-Reactive Power Regulation Resources of Wind Power-Containing Systems Based on Particle Swarm Algorithm

DOI: 10.12677/SG.2022.123008, PP. 67-74

Keywords: 粒子群算法,无功优化,风力发电,网损
Particle Swarm Optimization
, Reactive Power Optimization, Wind Power Generation, Network Loss

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Abstract:

风力发电作为一种优质的可再生能源发电技术,既可以缓解能源短缺又可以改善环境污染。但随着风电并网比例的增大,含风电系统的网损激增。本文以系统有功网损最小为目标函数,以常规发电机组、风电机组、静止无功补偿器、电容电抗器和变压器分接头作为无功控制资源,建立含风电系统的无功优化控制的数学模型,并采用粒子群算法求解该模型。最后基于MATLAB平台,在风电并网后的IEEE30节点系统中对建立好的数学模型进行算例分析,结果分析表明了该方法在降低含风电系统网损方面的有效性和可行性。
As a high-quality renewable energy power generation technology, wind power generation can not only alleviate energy shortage, but also improve environmental pollution. However, with the increase of the proportion of wind power connected to the grid, the network loss of wind power system increases sharply. In this paper, taking the minimum active power network loss of the system as the objective function and the conventional generator set, wind turbine set, static reactive power compensator, capacitor reactor and transformer tap as the reactive power control resources, the mathematical model of reactive power optimization control of wind power system is established, and the particle swarm optimization algorithm is used to solve the model. Finally, based on MATLAB platform, the established mathematical model is analyzed in the IEEE30 node system after wind power grid connection. The results show that this method is effective and feasible in reducing the network loss of wind power system.

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