期刊
IET SCIENCE MEASUREMENT & TECHNOLOGY
卷 11, 期 8, 页码 1058-1070出版社
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-smt.2016.0444
关键词
electric vehicles; optimisation; electric vehicle charging; plug-in electric vehicle capacity; differential evolution based artificial bee colony algorithm; optimisation framework; active power-line conditioners; distribution system operator; hybrid optimisation algorithm
Plug-in electric vehicles (PEVs) can produce active, reactive and distorted power as well as pollution reduction. This study proposes an optimisation framework to allocate the PEVs capacity to generate each power component considering to grid and vehicle constraints, technical concerns and market price. In the proposed framework, PEVs compete with active power-line conditioners (APLCs) to generate distorted power and with generators to produce active and reactive power. An objective function is defined which includes distribution system operator (DSO) payment for each market participant. This function is minimised based on a hybrid optimisation algorithm (HOA) combining artificial bee colony (ABC) and differential evolution (DE) algorithms subject to grid and vehicles constraints. In the presented algorithm, a novel self-adaptive modification phase is proposed to improve overall ability of the algorithm for optimisation applications. The effectiveness and efficiency of the method is demonstrated on a low-voltage network with 134 customers as a case study.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据