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Multi-time Scale Optimal Bidding Strategy for an EV Aggregator in Energy and Regulation Markets

机译:能源和调节市场中EV聚合器的多时间尺度最佳竞标策略

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The increasing proportion of renewable energy sources into the power grid is calling for more regulation capacities. Electric Vehicle (EV) has a huge potential for regulation ancillary service due to its large amount in the electricity market. This paper proposes a multi-time scale bidding strategy for the EV aggregator, which considers the battery degradation cost of individual EVs. Firstly, with the piecewise linear cost function, a battery degradation cost model is established and incorporated into the optimal bidding strategy. Secondly, the degradation cost is calculated based on the change of state of charge (SOC) every 5 minutes, which is more realistically. This problem is studied in the context of the United States Pennsylvania-New Jersey-Maryland (PJM) market rules. The case study results demonstrate that the proposed model effectively incentivizes the demand resources to provide regulation ancillary service without reducing the operating profit of EV aggregator significantly.
机译:可再生能源进入电网的增加比例呼吁更多的调节能力。 电动车(EV)由于电力市场中的大量巨大,具有巨大的监管辅助服务潜力。 本文提出了对EV聚合器的多时间尺度竞标策略,其考虑了个体EVS的电池劣化成本。 首先,通过分段线性成本函数,建立电池劣化成本模型并将其纳入最佳竞标策略。 其次,基于每5分钟的充电状态(SOC)的变化计算降级成本,这更逼真。 在美国宾夕法尼亚州 - 新泽西州 - 马里兰州(PJM)市场规则的背景下研究了这个问题。 案例研究结果表明,该建议的模型有效地激励了需求资源,以提供规范的辅助服务,而不会显着降低EV聚合器的营业利润。

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