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Demand side management of plug-in electric vehicles and coordinated unit commitment: a novel parallel competitive swarm optimization method

Wang, Ying, Yang, Zhile, Mourshed, Monjur, Guo, Yuanjun, Niu, Qun and Zhu, Xiaodong 2019. Demand side management of plug-in electric vehicles and coordinated unit commitment: a novel parallel competitive swarm optimization method. Energy Conversion and Management 196 , pp. 935-949. 10.1016/j.enconman.2019.06.012

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Abstract

Decreasing initial costs, the increased availability of charging infrastructure and favorable policy measures have resulted in the recent surge in plug-in electric vehicle (PEV) ownerships. PEV adoption increases electricity consumption from the grid that could either exacerbate electricity supply shortages or smooth demand curves. The optimal coordination and commitment of power generation units while ensuring wider access of PEVs to the grid are, therefore, important to reduce the cost and environmental pollution from thermal power generation systems, and to transition to a smarter grid. However, flexible demand side management (DSM) considering the stochastic charging behavior of PEVs adds new challenges to the complex power system optimization, and makes existing mathematical approaches ineffective. In this research, a novel parallel competitive swarm optimization algorithm is developed for solving large-scale unit commitment (UC) problems with mixed integer variables and multiple constraints typically found in PEV integrated grids. The parallel optimization framework combines binary and real-valued competitive swarm optimizers for solving the UC problem and demand side management of PEVs simultaneously. Numerical case studies have been conducted with multiple scales of unit numbers and various demand side management strategies of plug-in electric vehicles. The results show superior performance of proposed parallel competitive swarm optimization based method in successfully solving the proposed complex optimization problem. The flexible demand side management strategies of plug-in electric vehicles have shown large potentials in bringing considerable economic benefit.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Publisher: Elsevier
ISSN: 0196-8904
Funders: European Commission, China NSFC, Natural Science Foundation of Guangdong Province, China Post-doctoral Science Foundation, Chinese Academy of Sciences
Date of First Compliant Deposit: 12 June 2019
Date of Acceptance: 8 June 2019
Last Modified: 02 Jul 2020 20:00
URI: http://orca-mwe.cf.ac.uk/id/eprint/123365

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