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A two step optimization algorithm for wind turbine generator placement considering maximum allowable capacity

Author

Listed:
  • Safaei, A.
  • Vahidi, B.
  • Askarian-Abyaneh, H.
  • Azad-Farsani, E.
  • Ahadi, S.M.

Abstract

The wind turbine generation (WTG) sources are generally integrated into network in order to reduce power losses, avoid congestion, improve voltage profile and provide electricity during peak load. Appropriate sizing and sitting of WTGs play a notable role in minimization of the loss in distribution systems. In this paper, a new two-step PSO algorithm is proposed to facilitate placement of WTGs considering their maximum allowable capacity. Also, the location and maximum allowable capacity of WTGs are determined with the aim of minimizing power loss and sustaining the constraints such as bus voltage and loading of feeders in the desired range. In the proposed dual PSO algorithm, there are two steps in each iteration: the first step is implemented in determination of the WTGs optimal location as a control variable, and in the second step, the objective function value is determined among some scenarios which are generated based on the number and capacity of the WTGs, so that all constraints are satisfied. The proposed method feasibility is approved using sample 84-Bus and 32-Bus test systems.

Suggested Citation

  • Safaei, A. & Vahidi, B. & Askarian-Abyaneh, H. & Azad-Farsani, E. & Ahadi, S.M., 2016. "A two step optimization algorithm for wind turbine generator placement considering maximum allowable capacity," Renewable Energy, Elsevier, vol. 92(C), pages 75-82.
    • Handle: RePEc:eee:renene:v:92:y:2016:i:c:p:75-82
    DOI: 10.1016/j.renene.2016.01.093
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    References listed on IDEAS

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    1. Firouz, Y. & Farhadkhani, S. & Lobry, J. & Vallée, F. & Khakpour, A. & Durieux, O., 2014. "Numerical comparison of the effects of different types of distributed generation units on overcurrent protection systems in MV distribution grids," Renewable Energy, Elsevier, vol. 69(C), pages 271-283.
    2. Yang, Mian & Patiño-Echeverri, Dalia & Yang, Fuxia, 2012. "Wind power generation in China: Understanding the mismatch between capacity and generation," Renewable Energy, Elsevier, vol. 41(C), pages 145-151.
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    2. Mohana Alanazi & Abdulaziz Alanazi & Ahmad Almadhor & Hafiz Tayyab Rauf, 2023. "An Improved Fick’s Law Algorithm Based on Dynamic Lens-Imaging Learning Strategy for Planning a Hybrid Wind/Battery Energy System in Distribution Network," Mathematics, MDPI, vol. 11(5), pages 1-30, March.
    3. Amirreza Naderipour & Zulkurnain Abdul-Malek & Saber Arabi Nowdeh & Foad H. Gandoman & Mohammad Jafar Hadidian Moghaddam, 2019. "A Multi-Objective Optimization Problem for Optimal Site Selection of Wind Turbines for Reduce Losses and Improve Voltage Profile of Distribution Grids," Energies, MDPI, vol. 12(13), pages 1-15, July.
    4. Feng, Li & Liu, Jiajun & Lu, Haitao & Liu, Bingzhi & Chen, Yuning & Wu, Shenyu, 2022. "Robust operation of distribution network based on photovoltaic/wind energy resources in condition of COVID-19 pandemic considering deterministic and probabilistic approaches," Energy, Elsevier, vol. 261(PB).

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