Optimal demand Side Management for the Sparse Scheduling of Smart Charge of EVs

S. M. de Oca, P. Monzón, P. Belzarena
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Abstract

In this article, we provide a proof of concept realization of a demand response scheme modelling an EV-aggregator offering smart charging 1 coordination services to several Electric Vehicles (EV). The aggregator model promotes a distributed smart charge coordination of the EVs optimizing energy costs and energy charging profiles. This proposal considers EV’s battery health constraints and mobility constraints and promotes spars day-ahead charging profiles. We use a distributed scheme with the main objective of preserving the integrity of the private information of the active agents and scalability issue. The sparsity solution is identified using the alternating direction method of multipliers. The model proposed alternates between promoting sparsity of the charging profile accomplishing EV’s constraints and minimizing energy cost. We assume a decentralized communication between the participants of the optimization problem, exchanging adequate signal prices and power profiles keeping the integrity of the private information of each active agent.
基于稀疏调度的电动汽车智能充电最优需求侧管理
在本文中,我们提供了一个需求响应方案的概念验证,该方案建模了一个为多辆电动汽车(EV)提供智能充电协调服务的电动汽车聚合器。聚合器模型促进了电动汽车的分布式智能充电协调,优化了能源成本和能源充电配置。该方案考虑了电动汽车电池的健康约束和移动性约束,并推广了spars日前充电方案。我们使用分布式方案,其主要目标是保持活动代理私有信息的完整性和可伸缩性问题。稀疏解的辨识采用乘法器的交替方向法。该模型在提高充电轮廓的稀疏性以满足电动汽车的约束和最小化能源成本之间交替进行。我们假设优化问题的参与者之间的通信是分散的,交换足够的信号价格和功率配置文件,以保持每个活动主体私有信息的完整性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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