Frontiers in Energy Research (Feb 2022)

Research on Energy Management of a Virtual Power Plant Based on the Improved Cooperative Particle Swarm Optimization Algorithm

  • Dongmin Yu,
  • Dongmin Yu,
  • Xuejiao Zhao,
  • Xuejiao Zhao,
  • Yong Wang,
  • Yong Wang,
  • Linru Jiang,
  • Huanan Liu,
  • Huanan Liu

DOI
https://doi.org/10.3389/fenrg.2022.785569
Journal volume & issue
Vol. 10

Abstract

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Energy management of virtual power plants (VPPs) directly affects operators’ operating profits and is also related to users’ comfort and economy. In order to provide a reasonable scheme for scheduling each unit of the VPP and to improve the operating profits of the VPP, this study focuses on the optimization of VPP energy management under the premise of ensuring the comfort of flexible load users. First, flexible loads are divided into time-shiftable load (TL), power-variable load (PL), and interruptible load (IL), and their accurate power consumption models are established, respectively. Then, aiming at maximizing the operation profits of a VPP operator, an optimization model of VPP energy management considering user comfort is proposed. Finally, the improved cooperative particle swarm optimization (ICPSO) algorithm is applied to solve the proposed VPP energy management optimization model, and the optimal scheduling scheme of VPP energy management is obtained. Taking a VPP in the coastal area of China as an example, results show that the optimization model proposed in this article has the advantages of good economy and higher user comfort. Meanwhile, the ICPSO algorithm has the characteristics of faster optimization speed and higher accuracy when solving the problem with multiple variables.

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