Time-of-use (TOU) electricity rate for vehicle-to-grid (V2G) to minimize a charging station capacity

IF 5 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
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Abstract

This paper introduces a framework to yield an electricity rate for vehicle-to-grid (V2G) charging station (CS) to minimize installation capacity of a charging station considering electric vehicle (EV) arrival/departure time distribution. Two different layers are designed to avoid an obstacle encountered when formulating the problem as a convex optimization and to represent an EV aggregator and an electricity rate decision maker – a regulator. The EV aggregator layer focuses on increasing the profit and the regulator minimizes the peak load of the V2G CS. Linear programming was formulated for the former layer, and a modified particle swarm optimization (PSO) method was developed for the latter. Modification of the PSO approach allowed for easier escape of local minima, resulting in a new electricity rate for the V2G CS based on the EV arrival/departure time distribution data. The algorithm employs new matrices devised in this paper to accommodate EV information in the optimization process. In a simulation study, two distinct CSs with V2G operations were evaluated, each with a different EV arrival/departure time distribution. The simulation revealed that the peak load and the profit of the aggregator vary dramatically depending on the arrival/departure time distributions.

车辆到电网 (V2G) 的分时 (TOU) 电价,以尽量减少充电站容量
本文介绍了一个框架,用于计算车联网(V2G)充电站(CS)的电费,以在考虑电动汽车(EV)到达/离开时间分布的情况下,最大限度地降低充电站的安装容量。为了避免将问题表述为凸优化时遇到的障碍,设计了两个不同的层,分别代表电动汽车聚合器和电费决策者--监管者。电动汽车聚合层侧重于增加利润,而监管者则最大限度地降低 V2G CS 的峰值负荷。前一层采用线性规划,后一层采用改进的粒子群优化(PSO)方法。对 PSO 方法进行修改后,可以更容易地摆脱局部最小值,从而根据电动汽车到达/离开时间分布数据为 V2G CS 计算出新的电费。该算法采用了本文设计的新矩阵,以便在优化过程中考虑电动汽车信息。在一项模拟研究中,对两个不同的 V2G CS 进行了评估,每个 CS 都有不同的电动汽车到达/出发时间分布。模拟结果表明,峰值负荷和聚合器的利润随电动汽车到达/出发时间分布的不同而变化很大。
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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来源期刊
International Journal of Electrical Power & Energy Systems
International Journal of Electrical Power & Energy Systems 工程技术-工程:电子与电气
CiteScore
12.10
自引率
17.30%
发文量
1022
审稿时长
51 days
期刊介绍: The journal covers theoretical developments in electrical power and energy systems and their applications. The coverage embraces: generation and network planning; reliability; long and short term operation; expert systems; neural networks; object oriented systems; system control centres; database and information systems; stock and parameter estimation; system security and adequacy; network theory, modelling and computation; small and large system dynamics; dynamic model identification; on-line control including load and switching control; protection; distribution systems; energy economics; impact of non-conventional systems; and man-machine interfaces. As well as original research papers, the journal publishes short contributions, book reviews and conference reports. All papers are peer-reviewed by at least two referees.
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