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Multi-objective optimal load dispatch of microgrid with stochastic access of electric vehicles

机译:电动汽车随机接入的微电网多目标最优负荷分配

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Large-scale uncoordinated charging of electric vehicles (EVs) will become a reality in the near future, which will have a great impact on the stability and security of power system operation. In this regard, this paper proposes a multi-objective optimal load dispatch model of microgrid with the stochastic access of EVs. The uncertainties of EVs are modeled by using the Monte Carlo simulation. The objective function of the model includes the operating cost, pollutant treatment cost and load variance. Distributed generations (DGs) are considered in the model, including photovoltaic (PV) array, wind turbine (WT), diesel engine (DE) and micro turbine (MT). In order to solve the proposed model effectively, an improved particle swarm optimization (PSO) algorithm is proposed. Then we discuss the dispatch results under three different scheduling scenarios, i.e., uncoordinated charging scenario, coordinated charging scenario with and without DGs. The simulation results show that charging loads will be shifted form high-priced periods to low-priced periods under the coordinated charging mode of EVs, which can reduce daily costs by 3.09% and effectively improve the stability of power system operation. Meanwhile, the penetration of DGs can further reduce 6.43% of total cost by managing output of DGs. Further, the influence of cost weight factor on dispatch results is discussed. It illustrates that the cost weight factor is a trade-off between the total cost and the load variance. The experimental results demonstrate the effectiveness of the model under different charging situations. (C) 2013 Elsevier Ltd. All rights reserved.
机译:电动汽车(EV)的大规模不协调充电将在不久的将来成为现实,这将对电力系统运行的稳定性和安全性产生重大影响。为此,本文提出了一种具有电动汽车随机接入的微电网多目标最优负荷分配模型。电动汽车的不确定性通过蒙特卡洛模拟来建模。该模型的目标函数包括运营成本,污染物处理成本和负荷变化。模型中考虑了分布式发电(DG),包括光伏(PV)阵列,风力涡轮机(WT),柴油发动机(DE)和微型涡轮机(MT)。为了有效地解决所提出的模型,提出了一种改进的粒子群算法。然后我们讨论了三种不同调度方案下的调度结果,即不协调计费方案,有和没有DG的协调计费方案。仿真结果表明,在电动汽车的协调充电模式下,充电负荷将从高价时段转变为低价时段,可将日成本降低3.09%,并有效提高电力系统运行的稳定性。同时,通过管理DG的产出,DG的渗透可以进一步降低总成本的6.43%。此外,讨论了成本加权因子对调度结果的影响。它说明了成本权重因子是总成本与负载差异之间的权衡。实验结果证明了该模型在不同充电条件下的有效性。 (C)2013 Elsevier Ltd.保留所有权利。

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