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Simulated Annealing Approach Applied to the Energy Resource Management Considering Demand Response for Electric Vehicles

机译:模拟退火算法在考虑电动汽车需求响应的能源管理中的应用

摘要

The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results
机译:虚拟电源播放器(VPP)聚合和管理分布式能源(DER)是智能电网环境中的一项重要任务。这些DER的能源管理(ERM)可能成为一个困难而复杂的优化问题。包括电动汽车(EV)在内的多个DER的大规模集成可能会导致VPP需要几个小时才能解决ERM问题的方案。这就是为什么必须使用元启发式方法来在合理的时间内提出好的解决方案的原因。本文提出了一种模拟退火(SA)方法来确定ERM,考虑到DERs(主要是EV)的大量使用。在本文中,考虑了将需求响应(DR)程序应用于电动汽车的可能性。此外,实施了减少行程的DR程序。在具有2000辆EV的32总线配电网络上测试了SA方法,并将SA结果与确定性技术和粒子群优化结果进行了比较

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