4.7 Article

Multi-objective optimal dispatch of microgrid containing electric vehicles

期刊

JOURNAL OF CLEANER PRODUCTION
卷 165, 期 -, 页码 1572-1581

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2017.07.221

关键词

Microgrid; Optimal load dispatch; Multi-objective; Electric vehicles; Particle swarm optimization

资金

  1. National Natural Science Foundation of China [71501056]
  2. Fundamental Research Funds for the Central Universities [JZ2016HGTB0728]
  3. Anhui Provincial Natural Science Foundation Program [1608085QG165]
  4. China Post-doctoral Science Foundation [2017M612072]
  5. Foundation for Innovative Research Groups of the National Natural Science Foundation of China [71521001]

向作者/读者索取更多资源

As an important part of smart grid optimizations, optimal dispatch of microgrid is of great significance to reduce energy consumption, environmental pollution and user's electricity costs. The development objective of microgrid is not only to meet the basic demand of power supply, but also to improve its economic efficiency and environmental protection. In this regard, this paper proposes a multi-objective optimal dispatch model for microgrid under grid-connected mode, which comprehensively considers the operation cost and the environmental protective cost of the microgrid system. Distribution generators in the microgrid system include photovoltaic array, wind turbine, diesel engine, micro turbine and electric vehicle. The batteries of the accessed electric vehicles are treated as a kind of mobile distributed energy storage device in the model. In order to solve the proposed model effectively, according to the configuration and characteristics of the model, this paper proposes an improved particle swarm optimization algorithm to solve the optimization model. Two different operation scheduling scenarios under grid connected mode are researched, and the dispatch results of different optimization goals are discussed in this paper. The simulation results show that the effectiveness and superiority of the proposed model, which can effectively reduce the user's electricity costs and environmental pollution, promote the optimal operation of microgrid and achieve the economic management of the batteries of electric vehicles. (C) 2017 Elsevier Ltd. All rights reserved.

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