车–光–储电网成本与效益协同优化控制策略

Collaborative Optimization Control Strategy for Cost and Benefit of Vehicle-Photovoltaic-Energy Storage Grid

  • 摘要: 为解决大规模电动汽车无序充电给电网带来新的负荷高峰问题,提出了一种基于多方利益均衡的光伏储能电力系统协同优化方案。与常见的基于电网需求的光储系统参与模型不同,通过利用一天内的分时电价,协同了光储系统的参与情况。以电动汽车、充电站及电网运营商成本最小化,及收益的最大化为目标,建立了基于分时电价多目标优化模型,并提出一种改进的布谷鸟算法优化电动汽车充放电行为。所提出的优化算法,利用动态参数优化了算法的性能,提高了求解效率。最后,通过仿真算例验证了所提出的协同优化方案的有效性。

     

    Abstract: To address the issue of new load peaks caused by the uncoordinated charging of large-scale electric vehicles (EVs) on a power grid, a collaborative optimization scheme for photovoltaic-energy storage power systems based on multi-party interest balance is proposed. Unlike the common participation model of photovoltaic-storage systems which is based on grid demand, this study coordinates photovoltaic-storage system participation by utilizing the intraday time-of-use electricity price. A multi-objective optimization model based on time-of-use electricity pricing is established to minimize costs and maximize profits for EVs, charging stations, and grid operators. An improved Cuckoo algorithm is proposed to optimize the charging and discharging behavior of EVs. Finally, the effectiveness of the proposed collaborative optimization scheme is validated through simulation examples.

     

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