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非预期性与全场景可行性: 应对负荷与可再生能源不确定性的现状, 挑战与未来

  • Xi'an Jiaotong University
  • Thermal Power Research Institute

科研成果: 期刊稿件文章同行评审

49 引用 (Scopus)

摘要

Optimal scheduling of power systems with renewable energy is a typical multi-stage stochastic optimization problem. Recently, the importance of all-scenario- feasibility (ASF) and nonanticipativity of the scheduling decisions has been realized by researchers. Some effective security-constrained unit commitment (SCUC) methods have been proposed to guarantee the nonanticipativity and ASF in power system generation scheduling with thermal units and renewable resources. However, the nonanticipativity and ASF related difficulties in the scheduling of cascaded hydropower systems/energy storage systems with uncertain renewable energy/loads are still not resolved. In this paper, the meaning and importance of ASF and nonanticipativity were explained by a simple example. Meanwhile, this paper analyzed the core difficulties in scheduling of thermal units, storage systems and cascaded hydro systems and points out a series of scientific problems needed to be studied. Finally, the influence of nonanticipativity and ASF on the existing methods and concepts such as "reserve" were analyzed and the possible future methodswere envisaged. In conclusion, in order to deal with the uncertainty of renewable energy and loads, it is not only possible but also necessary to establish a new scheduling method satisfying nonanticipativity and ASF. A series of problems involved are needed to be solved in this process.

投稿的翻译标题Nonanticipativity and All-Scenario-Feasibility: State of the Art, Challenges, and Future in Dealing With the Uncertain Load and Renewable Energy
源语言繁体中文
页(从-至)6418-6432
页数15
期刊Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering
40
20
DOI
出版状态已出版 - 20 10月 2020

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

  1. 可持续发展目标 7 - 经济适用的清洁能源
    可持续发展目标 7 经济适用的清洁能源

关键词

  • All- scenario-feasibility (ASF)
  • Nonanticipativity
  • Power system scheduling
  • Renewable energy
  • Stochastic programming

学术指纹

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