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Peak dispatching for wind power with demand-side energy storage based on a particle swarm optimization model

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  • Song, Zongyun
  • Zhang, Jian
  • Zheng, Zedong
  • Xiao, Xinli

Abstract

Electric power system peak dispatching plays a very important role in leveling the load curve, strengthening grid stability, and conserving energy. The inadequate capability of peak dispatching is a leading factor in incomplete wind power integration and poor load characteristics. Adding energy storage on the demand side can improve system peak dispatching ability, promote wind power, and optimize the load curve. This paper first analyzes the mechanisms of regenerative electric heaters (REHs) and electric vehicles (EV) on peak dispatching, based on which a multi-energy hybrid peak dispatching system is designed. Taking into account economic, environmental, and societal benefits and equivalent load curve fluctuation level, this study establishes a multi-energy hybrid peak dispatching optimization model that considers general as well as REH and EV load-control constraints. In view of the shortcomings of particle swarm optimization (PSO), a two-phase force (TPF) rule is introduced in searching process to improve PSO searching performance. The research result reveals that: TPF rule can optimize PSO searching performance and help obtain the best peak-dispatching scheme. In addition, the multi-energy hybrid peak dispatching system designed here offers advantages in leveling the load curve, optimizing power output, conserving energy and reducing emissions, and yield economic benefits.

Suggested Citation

  • Song, Zongyun & Zhang, Jian & Zheng, Zedong & Xiao, Xinli, 2019. "Peak dispatching for wind power with demand-side energy storage based on a particle swarm optimization model," Utilities Policy, Elsevier, vol. 56(C), pages 136-148.
    • Handle: RePEc:eee:juipol:v:56:y:2019:i:c:p:136-148
    DOI: 10.1016/j.jup.2018.12.003
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    References listed on IDEAS

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    1. Zhang, Ning & Hu, Zhaoguang & Shen, Bo & Dang, Shuping & Zhang, Jian & Zhou, Yuhui, 2016. "A source–grid–load coordinated power planning model considering the integration of wind power generation," Applied Energy, Elsevier, vol. 168(C), pages 13-24.
    2. Biswas, Partha P. & Suganthan, P.N. & Qu, B.Y. & Amaratunga, Gehan A.J., 2018. "Multiobjective economic-environmental power dispatch with stochastic wind-solar-small hydro power," Energy, Elsevier, vol. 150(C), pages 1039-1057.
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    1. Solanke, Tirupati U. & Khatua, Pradeep K. & Ramachandaramurthy, Vigna K. & Yong, Jia Ying & Tan, Kang Miao, 2021. "Control and management of a multilevel electric vehicles infrastructure integrated with distributed resources: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).

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