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  • 标题:Study on bi‐level multi‐objective collaborative optimization model for integrated energy system considering source‐load uncertainty
  • 本地全文:下载
  • 作者:Jing Wu ; Gejirifu De ; Zhongfu Tan
  • 期刊名称:Energy Science & Engineering
  • 电子版ISSN:2050-0505
  • 出版年度:2021
  • 卷号:9
  • 期号:8
  • 页码:1160-1179
  • DOI:10.1002/ese3.880
  • 语种:English
  • 出版社:John Wiley & Sons, Ltd.
  • 摘要:The uncertainty of both the generation side and the user side brings certain impacts on the source‐load coordinated operation of integrated energy system (IES). At first, the source‐load characteristics of the IES with large‐scale distributed energy is analyzed. Secondly, considering lower operating cost and higher renewable energy consumption rate, a bilevel optimization model of the source‐load coordination based on the IES operation structure is established, which considers the uncertainty of both the generation side, such as wind and photovoltaic (PV) power output, and the load side. The robust optimization theory and stochastic chance‐constrained programming theory are introduced to establish the upper layer and the lower layer models of the IES. Besides, the firefly algorithm is used to design the solution process of the bilevel optimization model. The results show that the uncertainty of the wind power, PV power, and the load are positively correlated with the comprehensive operation cost. Also, based on the full consideration of the bilevel uncertainties, the system operation cost is significantly reduced. Meanwhile, the improvement of the confidence level of the objective function and constraint conditions will enhance the optimistic value of the comprehensive operation cost of the system, which means gaining higher reliability by sacrificing partial system benefits. Overall, the bilevel optimization model considering the source‐load uncertainty can both improve the renewable energy consumption rate and reduce the comprehensive operation cost of the IES system.
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