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Solving multi-area economic dispatch problem using hybrid exchange market algorithm with grasshopper optimization algorithm

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  • Sharifian, Yeganeh
  • Abdi, Hamdi

Abstract

This research work proposes the hybrid meta-heuristic algorithm to solve the multi-area economic dispatch problem to operate the power systems economically. The proposed hybrid algorithm combines the exchange market and grasshopper optimization algorithms. The grasshopper optimization algorithm sometimes suffers from premature convergence. To overcome this drawback, a hybrid algorithm for the better balance between exploration and exploitation and thus finding optimal solutions with high quality and robustness, is proposed in this paper. The main target of this paper is to investigate the application of the hybrid algorithm for optimizing the multi-area economic dispatch problem, satisfying different constraints of the valve point loading effect, multiple fuels, prohibited operation zones, ramp-rate limit, the tie-line constraints, and transmission loses. In this regard, after validation of the proposed hybrid algorithm by applying it on some benchmark functions of diverse nature, the effectiveness and robustness of the proposed algorithm are evaluated in three case studies of the multi-area economic dispatch problem. The comparative results confirmed the effectiveness of the proposed method in terms of robustness and quality solutions. Also, the applied method reduces the fuel cost in the range of 0.0229%–1.1622%.

Suggested Citation

  • Sharifian, Yeganeh & Abdi, Hamdi, 2023. "Solving multi-area economic dispatch problem using hybrid exchange market algorithm with grasshopper optimization algorithm," Energy, Elsevier, vol. 267(C).
    • Handle: RePEc:eee:energy:v:267:y:2023:i:c:s0360544222034375
    DOI: 10.1016/j.energy.2022.126550
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    1. Mohammadi-ivatloo, Behnam & Rabiee, Abbas & Soroudi, Alireza & Ehsan, Mehdi, 2012. "Imperialist competitive algorithm for solving non-convex dynamic economic power dispatch," Energy, Elsevier, vol. 44(1), pages 228-240.
    2. Ghasemi, Mojtaba & Aghaei, Jamshid & Akbari, Ebrahim & Ghavidel, Sahand & Li, Li, 2016. "A differential evolution particle swarm optimizer for various types of multi-area economic dispatch problems," Energy, Elsevier, vol. 107(C), pages 182-195.
    3. David H. Wolpert & William G. Macready, 1995. "No Free Lunch Theorems for Search," Working Papers 95-02-010, Santa Fe Institute.
    4. Mohammadian, M. & Lorestani, A. & Ardehali, M.M., 2018. "Optimization of single and multi-areas economic dispatch problems based on evolutionary particle swarm optimization algorithm," Energy, Elsevier, vol. 161(C), pages 710-724.
    5. Secui, Dinu Calin, 2015. "The chaotic global best artificial bee colony algorithm for the multi-area economic/emission dispatch," Energy, Elsevier, vol. 93(P2), pages 2518-2545.
    6. Lin, Jian & Wang, Zhou-Jing, 2019. "Multi-area economic dispatch using an improved stochastic fractal search algorithm," Energy, Elsevier, vol. 166(C), pages 47-58.
    7. Fesanghary, M. & Ardehali, M.M., 2009. "A novel meta-heuristic optimization methodology for solving various types of economic dispatch problem," Energy, Elsevier, vol. 34(6), pages 757-766.
    8. Meng, Anbo & Xu, Xuancong & Zhang, Zhan & Zeng, Cong & Liang, Ruduo & Zhang, Zheng & Wang, Xiaolin & Yan, Baiping & Yin, Hao & Luo, Jianqiang, 2022. "Solving high-dimensional multi-area economic dispatch problem by decoupled distributed crisscross optimization algorithm with population cross generation strategy," Energy, Elsevier, vol. 258(C).
    9. Basu, M., 2014. "Teaching–learning-based optimization algorithm for multi-area economic dispatch," Energy, Elsevier, vol. 68(C), pages 21-28.
    10. Chen, Xu & Tang, Guowei, 2022. "Solving static and dynamic multi-area economic dispatch problems using an improved competitive swarm optimization algorithm," Energy, Elsevier, vol. 238(PC).
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