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首页> 外文会议>2016 International Conference on Electrical Power and Energy Systems >Customer and aggregator balanced dynamic Electric Vehicle charge scheduling in a smart grid framework
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Customer and aggregator balanced dynamic Electric Vehicle charge scheduling in a smart grid framework

机译：智能电网框架中的客户和聚合商平衡动态电动汽车充电调度

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摘要

Electric Vehicles (EVs) are already an integral part of the smart grid framework. The problem of scheduling the charging of these plug-in vehicles in coordination with the dynamic electricity tariffs and load-changes throughout the day is important and must be considered for efficient integration of such units. Since EVs are active and distributed storage units, they have the capability to provide regulation services to the power grid and hence can be used in schemes where the aggregator can compensate EVs for this service. The EV charging must also be scheduled in such a way that the customer or the vehicle owner incurs the least cost and the aggregator also makes the maximum revenue. The work presented in this paper attempts to satisfy the economy of both the EV owner and the aggregator by mathematically formulating this scheduling problem and solving it by different optimization techniques to arrive at the optimal cost and revenue for the customer and the aggregator respectively. Different heuristic techniques based evolutionary optimization algorithms have been applied to solve the optimal charge scheduling problem and the results compared and analyzed for assessing practical feasibility.
机译：电动汽车（EV）已经成为智能电网框架不可或缺的一部分。与全天动态电价和负荷变化协调安排这些插电式汽车的充电问题很重要，必须有效考虑这些单元的集成。由于电动汽车是主动式和分布式存储单元，因此它们具有向电网提供调节服务的能力，因此可以在聚合器可以为此服务补偿电动汽车的方案中使用。 EV充电还必须按以下方式安排：客户或车主花费最少的成本，而集合商也能获得最大的收益。本文提出的工作试图通过数学公式化此调度问题，并通过不同的优化技术解决它，从而分别为客户和聚合器提供最佳成本和收益，从而满足电动汽车所有者和聚合器的经济需求。已经应用了基于启发式技术的不同进化优化算法来解决最优充电调度问题，并对结果进行了比较和分析，以评估其实际可行性。

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