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A hybrid dynamic economics emissions dispatch model: Distributed renewable power systems based on improved COOT optimization algorithm

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  • Sheng, Wanxing
  • Li, Rui
  • Yan, Tao
  • Tseng, Ming-Lang
  • Lou, Jiale
  • Li, Lingling

Abstract

This study proposes a hybrid dynamic economics emissions dispatch (HDEED) model for a distributed power system containing thermal generating units, wind farms and photovoltaic plants. The construction of novel distributed power system has been a significant means of tackling the energy crisis. (1) the relationship between each generation unit of the power generation system is analyzed, as well as the power balance constraint, transmission loss constraint, output capacity of each generation unit and slope constraint of the power system; and (2) the operating cost objective function is established with the objective of minimizing unit's generation cost, pollutant emission objective function, and the satisfaction weight coefficient. A novel and improved COOT optimization algorithm is presented to enhance convergence performance and solution speed in solving the problem by introducing a chaotic initialization strategy. A mutation strategy and an improved chain movement of the model solution are verified. The result shows that for the HDEED problem, the ICOOT algorithm reduces the operating cost targets by 1.28%, 6.99% and 7.44% and the pollutant emission targets by 2.98%, 5.46% and 10.88% compared to other algorithms. The developed model provides an effective solution for improving the operational stability, economy and cleanliness of system.

Suggested Citation

  • Sheng, Wanxing & Li, Rui & Yan, Tao & Tseng, Ming-Lang & Lou, Jiale & Li, Lingling, 2023. "A hybrid dynamic economics emissions dispatch model: Distributed renewable power systems based on improved COOT optimization algorithm," Renewable Energy, Elsevier, vol. 204(C), pages 493-506.
  • Handle: RePEc:eee:renene:v:204:y:2023:i:c:p:493-506
    DOI: 10.1016/j.renene.2023.01.010
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    2. Arunachalam Sundaram & Nasser S. Alkhaldi, 2024. "Multi-Objective Stochastic Paint Optimizer for Solving Dynamic Economic Emission Dispatch with Transmission Loss Prediction Using Random Forest Machine Learning Model," Energies, MDPI, vol. 17(4), pages 1-26, February.

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