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首页> 外文期刊>International journal of electrical power and energy systems >Stochastic optimal power flow incorporating offshore wind farm and electric vehicles
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Stochastic optimal power flow incorporating offshore wind farm and electric vehicles

机译:结合海上风电场和电动汽车的随机最优潮流

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In this paper, an optimal power flow model of a power system, which includes an offshore wind farm and plug-in electric vehicles (PEVs) connected to grid, is presented. The stochastic nature of wind power and the uncertainties in the EV owner's behavior are suitably modelled by statistical models available in recent literatures. The offshore wind farms are assumed to be composed of doubly fed induction generators (DFIGs) having reactive power control capability and are connected to offshore grid by HVDC link. In order to obtain the optimal active power schedules of different energy sources, an optimization problem is solved by applying recently introduced Gbest guided artificial bee colony algorithm (GABC). The accuracy of proposed approach has been tested by implementing AC-DC optimal power flow on modified IEEE 5-bus, IEEE 9-bus, and IEEE 39-bus systems. The results obtained by GABC algorithm are compared with the results available in literatures. This paper also includes AC-DC optimal power flow model, implemented on modified IEEE-30 bus test system by including wind farm power and V2G source. It has been shown that the uncertainty associated with availability of power from wind farm and PEVs affects the overall cost of operation of system. (C) 2014 Elsevier Ltd. All rights reserved.
机译:本文提出了一种电力系统的最优潮流模型,该模型包括一个海上风电场和并网的插电式电动汽车(PEV)。风能的随机性和电动车所有者行为的不确定性可以通过最近文献中可用的统计模型进行适当建模。假设海上风电场由具有无功功率控制能力的双馈感应发电机(DFIG)组成,并通过HVDC链路连接到海上电网。为了获得不同能源的最优有功功率调度,通过应用最近引入的Gbest引导人工蜂群算法(GABC)解决了优化问题。通过在改进的IEEE 5总线,IEEE 9总线和IEEE 39总线系统上实现AC-DC最佳功率流,已经测试了所提出方法的准确性。将通过GABC算法获得的结果与文献中提供的结果进行比较。本文还包括AC-DC最佳功率流模型,该模型通过包含风电场功率和V2G源在改进的IEEE-30总线测试系统上实现。已经表明,与来自风电场和PEV的电力可用性相关的不确定性会影响系统的总体运行成本。 (C)2014 Elsevier Ltd.保留所有权利。

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