期刊
ENERGY
卷 195, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2020.116946
关键词
Orthogonal particle swarm optimization (OPSO) algorithm; Dynamic economic emission dispatch (DEED); Load demand management (LDM); Electric vehicle (EV); Inequality and equality operating power constraints Smart cities
A multi-objective problem, namely, dynamic economic emission dispatch is simultaneously solved under several practical equality and inequality operating power constraints, while applying the load demand management (LDM) on 30,000 electric vehicles (EVs) during crest shaving and valley filling (CSVF) regions. A novel algorithm named orthogonal particle swarm optimization (OPSO) is proposed for such a problem. Ten thermal-generating units (TGUs) from power-generating systems (PGSs) in two Case Studies, with and without LDM on the load demand of 30,000 EVs, are tested. The comprehensive analysis results reveal that the quantity of emissions released by the 10 TGUs was remarkable affected and reduced around 4005 kg/day and the operating fuel cost was saved around $409/day when applying the LDM on the load demand of 30,000 EVs in the CSVF regions. This study provides important outcomes about the future operation of PGSs when applying the LDM strategy on a large-scale penetration of EVs in smart cities into a sustainable environment. The study outcomes contribute in making the PGS flexible, economical, environmental, stable, and reliable. (C) 2020 Elsevier Ltd. All rights reserved.
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