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DAI Jinglong, BAI Xiaoqing, BAO Haibo. Probabilistic Optimal Power Flow by Considering the Uncertainty of Source and Demand Side[J]. Modern Electric Power, 2016, 33(1): 34-40.
Citation: DAI Jinglong, BAI Xiaoqing, BAO Haibo. Probabilistic Optimal Power Flow by Considering the Uncertainty of Source and Demand Side[J]. Modern Electric Power, 2016, 33(1): 34-40.
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Probabilistic Optimal Power Flow by Considering the Uncertainty of Source and Demand Side

  • Guangxi Power System Optimization and Energy saving Technique Key Lab, Guangxi University, Nanning 530004,China

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  • Received Date: May 22, 2015
  • Published Date: February 13, 2016
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    • Abstract
  • In this paper, a probabilistic optimal power flow analysis model under electricity market environment is proposed, and is solved by unscented transform method based on symmetric sampling strategy. In order to reveal the market laws and the weaknesses of the operating system by considering probability, the uncertainties of renewable generation output, load demand and bidding are taken into account in the proposed model. In addition, probability information is transferred through nonlinear transformation by using unscented transform, in which the ratio and high order information parameters are introduced to reduce the local effect and high order errors, and its correlation impact on stochastic variables have been analyzed. Numerical results of IEEE 30 bus and 118 bus test systems show that the implementation of unscented transformation is simple and efficient, can accurately deal with probabilistic optimal power flow problem of electricity market, and the output statistic information of operation characteristics can provide more reliable, comprehensive references for evaluating operation status of electricity market.
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    • References (22)
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