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An Optimal Solution for Smooth and Non-Smooth Cost Functions-Based Economic Dispatch Problem

Author

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  • Chun-Yao Lee

    (Department of Electrical Engineering, Chung Yuan Christian University, No. 200, Zhongbei Road, Zhongli District, Taoyuan City 320, Taiwan)

  • Maickel Tuegeh

    (Department of Electrical Engineering, Chung Yuan Christian University, No. 200, Zhongbei Road, Zhongli District, Taoyuan City 320, Taiwan)

Abstract

A modified particle swarm optimization and incorporated chaotic search to solve economic dispatch problems for smooth and non-smooth cost functions, considering prohibited operating zones and valve-point effects is proposed in this paper. An inertia weight modification of particle swarm optimization is introduced to enhance algorithm performance and generate optimal solutions with stable solution accuracy and offers faster convergence characteristic. Moreover, an incorporation of chaotic search, called logistic map, is used to increase the global searching capability. To demonstrate the effectiveness and feasibility of the proposed algorithm compared to the several existing methods in the literature, five systems with different criteria are verified. The results show the excellent performance of the proposed method to solve economic dispatch problems.

Suggested Citation

  • Chun-Yao Lee & Maickel Tuegeh, 2020. "An Optimal Solution for Smooth and Non-Smooth Cost Functions-Based Economic Dispatch Problem," Energies, MDPI, vol. 13(14), pages 1-16, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3721-:d:386874
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    References listed on IDEAS

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    1. Zou, Dexuan & Li, Steven & Wang, Gai-Ge & Li, Zongyan & Ouyang, Haibin, 2016. "An improved differential evolution algorithm for the economic load dispatch problems with or without valve-point effects," Applied Energy, Elsevier, vol. 181(C), pages 375-390.
    2. Secui, Dinu Calin, 2016. "A modified Symbiotic Organisms Search algorithm for large scale economic dispatch problem with valve-point effects," Energy, Elsevier, vol. 113(C), pages 366-384.
    3. Xu Chen & Bin Xu & Wenli Du, 2018. "An Improved Particle Swarm Optimization with Biogeography-Based Learning Strategy for Economic Dispatch Problems," Complexity, Hindawi, vol. 2018, pages 1-15, July.
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    Cited by:

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    2. Chun-Yao Lee & Meng-Syun Wen & Guang-Lin Zhuo & Truong-An Le, 2022. "Application of ANN in Induction-Motor Fault-Detection System Established with MRA and CFFS," Mathematics, MDPI, vol. 10(13), pages 1-17, June.
    3. Ghulam Abbas & Irfan Ahmad Khan & Naveed Ashraf & Muhammad Taskeen Raza & Muhammad Rashad & Raheel Muzzammel, 2023. "On Employing a Constrained Nonlinear Optimizer to Constrained Economic Dispatch Problems," Sustainability, MDPI, vol. 15(13), pages 1-23, June.
    4. Chun-Yao Lee & Chang-En Wu, 2020. "Short-Term Electricity Price Forecasting Based on Similar Day-Based Neural Network," Energies, MDPI, vol. 13(17), pages 1-15, August.
    5. Faisal Tariq & Salem Alelyani & Ghulam Abbas & Ayman Qahmash & Mohammad Rashid Hussain, 2020. "Solving Renewables-Integrated Economic Load Dispatch Problem by Variant of Metaheuristic Bat-Inspired Algorithm," Energies, MDPI, vol. 13(23), pages 1-36, November.

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