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Multi-objective Robust Optimization of Microgrid System with Electric Vehicles and New Renewable Energy

机译:电动汽车和新可再生能源微电网系统的多目标鲁棒优化

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This paper proposed an adjustable robust optimization algorithm based on interval prediction theory, which integrates photovoltaic power unit, energy storage system and electric vehicle charging station. Based on the interval prediction theory, the mathematical models are established respectively, and the adjustable robust optimal scheduling model is constructed. Besides, an uncertain group scheduling method is proposed for the arrival time of electric vehicles, the number of uncertain factors is determined by setting robust optimization parameters. The model transformed into a linear model by decoupling, solved by lagrange relaxation algorithm, and the effectiveness of the optimization algorithm is verified by introducing the probability of violating load reserve constraints. The case combined photovoltaic power unit, energy storage system and electric vehicle charging station demonstrates the robustness and economy of the system.
机译:提出了一种基于区间预测理论的可调鲁棒优化算法,该算法集光伏发电单元,储能系统和电动汽车充电站于一体。基于区间预测理论,分别建立了数学模型,并建立了可调整的鲁棒最优调度模型。此外,针对电动汽车的到达时间,提出了一种不确定的组调度方法,通过设置鲁棒的优化参数来确定不确定因素的数量。通过解耦将模型转换为线性模型,并通过拉格朗日松弛算法进行求解,并通过引入违反负荷储备约束的概率来验证优化算法的有效性。结合光伏发电单元,储能系统和电动汽车充电站的案例展示了该系统的坚固性和经济性。

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