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Multiobjective optimization model of collaborative dispatch in the microgrids

机译:微电网中协同调度的多目标优化模型

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The renewable energy wind, such as the wind power and photovoltaic power, has a lower absorptive capability in the microgrid. This work has proposed a model of cooperative dispatch of the electric vehicles and the energy storage system. The electric vehicles are adjusted into the grid network with the real-time electricity price. The model is solved by the improved version of the strength Pareto evolutionary algorithm 2 (SPEA2). The algorithm combines the SPEA2 with a shift-based density estimation (SDE) strategy. The results show that the electric vehicle and the energy storage system can better improve absorptive capability, and stabilize the microgrid system.
机译:可再生能源风,例如风能和光伏能,在微电网中具有较低的吸收能力。这项工作提出了电动汽车和储能系统协同调度的模型。电动汽车通过实时电价调整到电网。该模型由强度帕累托进化算法2(SPEA2)的改进版本解决。该算法将SPEA2与基于位移的密度估计(SDE)策略结合在一起。结果表明,电动汽车和储能系统可以更好地提高吸收能力,并稳定微电网系统。

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