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On the most convenient mixed strategies in a mixed strategist dynamics approach for load management of electric vehicle fleets

机译:在电动汽车车队负荷管理的混合策略动力学方法中最方便的混合策略

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This manuscript explores the selection of appropriate mixed strategies (MSs) in a Mixed Strategist Dynamics (MSD) application for load management of Plug-in Electric Vehicle (PEV) fleets. This selection is based on the convenience of PEV owners, aiming to choose those MSs that privilege early high (or fast) charging rates when it is possible. The previously published MSD and Maximum Entropy principle (MSD-MEP) approach is revised and illustrated with several examples, specially in the context of selection of MSs. This revision allows a wider understanding of the method, and aims to inspire new contributions on domains where distributed optimization methods are pertinent. Results obtained without any management structure are compared to those obtained with the MSD-MEP approach under different scenarios, where full sets of MSs and reduced sets of convenient MSs are applied. The performance of the method, using conveniently reduced sets of MSs, is tested with real historical active power measurements, provided by the SOREA utility grid company in the region of Savoie, France.
机译:该手稿探讨了在混合策略汽车动力学(MSD)应用中为插电式电动汽车(PEV)车队进行负载管理的适当混合策略(MSs)的选择。该选择基于PEV所有者的便利,旨在选择那些可能的话,优先享受较高(或更快)充电速率的MS。修改了先前发布的MSD和最大熵原理(MSD-MEP)方法,并通过几个示例进行了说明,尤其是在选择MS的情况下。该修订版允许对该方法有更广泛的了解,旨在激发与分布式优化方法相关的领域的新贡献。在没有应用管理结构的情况下,将获得的结果与通过MSD-MEP方法在不同情况下获得的结果进行比较,在这种情况下,将应用全套MS和简化的便捷MS。使用由法国萨瓦省地区的SOREA公用电网公司提供的实际历史有功功率测量值,测试了使用方便减少的MS集的方法的性能。

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