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  • 标题:Multi-Objective Day-Ahead Optimal Scheduling of Isolated Microgrid Considering Flexibility
  • 本地全文:下载
  • 作者:Liang Zhang ; Bo Pang ; Ruipeng Yi
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2018
  • 卷号:53
  • 页码:1-5
  • DOI:10.1051/e3sconf/20185301024
  • 出版社:EDP Sciences
  • 摘要:In isolated microgrid, renewable energy sources including photovoltaic and wind power, have the nature of intermittence and variability. Making a reasonable day-ahead generation schedule could improve system ability to cope with uncertainty. Therefore, based on day-ahead generation schedule, flexibility insufficiency rate is proposed considering economy and flexibility. Aiming at the lowest flexibility insufficiency rate and optimal operating cost, a day-ahead generation schedule optimizing model of isolated microgrid is established. Under multi-objective particle swarm optimization, Pareto optimal solution set of the day-ahead generation schedule is found. Simulation results of an isolated microgrid show that, day-ahead generation schedule made with the proposed method can improve ability of power system to cope with uncertainty and reduce economic losses.
  • 其他摘要:In isolated microgrid, renewable energy sources including photovoltaic and wind power, have the nature of intermittence and variability. Making a reasonable day-ahead generation schedule could improve system ability to cope with uncertainty. Therefore, based on day-ahead generation schedule, flexibility insufficiency rate is proposed considering economy and flexibility. Aiming at the lowest flexibility insufficiency rate and optimal operating cost, a day-ahead generation schedule optimizing model of isolated microgrid is established. Under multi-objective particle swarm optimization, Pareto optimal solution set of the day-ahead generation schedule is found. Simulation results of an isolated microgrid show that, day-ahead generation schedule made with the proposed method can improve ability of power system to cope with uncertainty and reduce economic losses.
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