Shuheng Chen
Wind generation, probability cost model, particle swarm optimization algorithm, reactive power optimization, uncertainty
On basis of the probabilistic economic cost model and the hybrid particle swarm algorithm, an improved reactive power optimization method of distribution network is presented, which embraces the effects of stochastic wind speed and load. Firstly, the probabilistic reactive power optimization model is presented after two important steps. One is to divide load curve into a number of fragments and augment the control vector dimension’s length, and the other is to divide wind speed probability density curve into a number of fragments and build the probabilistic cost model. Secondly, on basis of the independent controlling theory, the reactive power ability of wind generator is used to regulate the distribution network. As a result, with the Niche operations embedded into the original hybrid particle swarm algorithm, an improved reactive power optimization algorithm is presented. Thirdly, the corresponding reactive power optimization software program is developed in VC++ program language on the platform of SQL SERVER database. Lastly, with this software system, the case study is done. The experiment results have proved that this method possesses better adaptability and computational efficiency.
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