基于二元分解的电动汽车最优调度

Jinfeng Yang, Zaiyue Yang
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引用次数: 4

摘要

本文主要研究电动汽车的最优调度问题。电动汽车计划运行阶段和非运行阶段。在充分考虑营业收入、管制收入和业主习惯的情况下,将成本最小化问题表述为具有耦合约束的凸规划问题。利用对偶分解得到全局最优解。然后,引入一种改进的在线方法来减轻价格预测误差的影响。仿真结果表明,我们的算法可以在很大程度上降低成本。此外,与完全了解实时价格(RTP)的最优调度方案相比,在线调度方案可以达到相似的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal scheduling of electric vehicle using dual decomposition
This paper concentrates on the optimal scheduling of electric vehicle (EV). The EV is scheduled for both operating stage and non-operating stage. With full consideration of operating income, regulation revenue and the owner's habit, the cost minimization problem is formulated as a convex programming with coupling constrains. Dual decomposition is utilized to obtain the global optimal solution. Then, a modified online approach is introduced to alleviate the impact of price prediction error. The simulation reveals that our algorithms can reduce the cost to a large extent. Furthermore, it is demonstrated that the online scheduling scheme can achieve a similar performance compared with the optimal scheduling scheme having full knowledge of real time prices (RTP).
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