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Hybrid Imperialist Competitive and Grey Wolf Algorithm to Solve Multiobjective Optimal Power Flow with Wind and Solar Units

Author

Listed:
  • Jalel Ben Hmida

    (Department of Mechanical Engineering, University of Louisiana at Lafayette, Lafayette, LA 70504, USA)

  • Mohammad Javad Morshed

    (Department of Electrical and Computer Engineering, University of Louisiana at Lafayette, Lafayette, LA 70504, USA)

  • Jim Lee

    (Department of Mechanical Engineering, University of Louisiana at Lafayette, Lafayette, LA 70504, USA)

  • Terrence Chambers

    (Department of Mechanical Engineering, University of Louisiana at Lafayette, Lafayette, LA 70504, USA)

Abstract

The optimal power flow (OPF) module optimizes the generation, transmission, and distribution of electric power without disrupting network power flow, operating limits, or constraints. Similarly to any power flow analysis technique, OPF also allows the determination of system’s state of operation, that is, the injected power, current, and voltage throughout the electric power system. In this context, there is a large range of OPF problems and different approaches to solve them. Moreover, the nature of OPF is evolving due to renewable energy integration and recent flexibility in power grids. This paper presents an original hybrid imperialist competitive and grey wolf algorithm (HIC-GWA) to solve twelve different study cases of simple and multiobjective OPF problems for modern power systems, including wind and photovoltaic power generators. The performance capabilities and potential of the proposed metaheuristic are presented, illustrating the applicability of the approach, and analyzed on two test systems: the IEEE 30 bus and IEEE 118 bus power systems. Sensitivity analysis has been performed on this approach to prove the robustness of the method. Obtained results are analyzed and compared with recently published OPF solutions. The proposed metaheuristic is more efficient and provides much better optimal solutions.

Suggested Citation

  • Jalel Ben Hmida & Mohammad Javad Morshed & Jim Lee & Terrence Chambers, 2018. "Hybrid Imperialist Competitive and Grey Wolf Algorithm to Solve Multiobjective Optimal Power Flow with Wind and Solar Units," Energies, MDPI, vol. 11(11), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:2891-:d:178011
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    References listed on IDEAS

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    1. Ghasemi, Mojtaba & Ghavidel, Sahand & Ghanbarian, Mohammad Mehdi & Gharibzadeh, Masihallah & Azizi Vahed, Ali, 2014. "Multi-objective optimal power flow considering the cost, emission, voltage deviation and power losses using multi-objective modified imperialist competitive algorithm," Energy, Elsevier, vol. 78(C), pages 276-289.
    2. Narimani, Mohammad Rasoul & Azizipanah-Abarghooee, Rasoul & Zoghdar-Moghadam-Shahrekohne, Behrouz & Gholami, Kayvan, 2013. "A novel approach to multi-objective optimal power flow by a new hybrid optimization algorithm considering generator constraints and multi-fuel type," Energy, Elsevier, vol. 49(C), pages 119-136.
    3. Ghasemi, Mojtaba & Ghavidel, Sahand & Aghaei, Jamshid & Gitizadeh, Mohsen & Falah, Hasan, 2014. "Application of chaos-based chaotic invasive weed optimization techniques for environmental OPF problems in the power system," Chaos, Solitons & Fractals, Elsevier, vol. 69(C), pages 271-284.
    4. Morshed, Mohammad Javad & Hmida, Jalel Ben & Fekih, Afef, 2018. "A probabilistic multi-objective approach for power flow optimization in hybrid wind-PV-PEV systems," Applied Energy, Elsevier, vol. 211(C), pages 1136-1149.
    5. Ghasemi, Mojtaba & Ghavidel, Sahand & Akbari, Ebrahim & Vahed, Ali Azizi, 2014. "Solving non-linear, non-smooth and non-convex optimal power flow problems using chaotic invasive weed optimization algorithms based on chaos," Energy, Elsevier, vol. 73(C), pages 340-353.
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    Citations

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    Cited by:

    1. Ali S. Alghamdi, 2022. "Optimal Power Flow in Wind–Photovoltaic Energy Regulation Systems Using a Modified Turbulent Water Flow-Based Optimization," Sustainability, MDPI, vol. 14(24), pages 1-27, December.
    2. Francisco G. Montoya & Raúl Baños & Alfredo Alcayde & Francisco Manzano-Agugliaro, 2019. "Optimization Methods Applied to Power Systems," Energies, MDPI, vol. 12(12), pages 1-8, June.
    3. Shahenda Sarhan & Ragab El-Sehiemy & Amlak Abaza & Mona Gafar, 2022. "Turbulent Flow of Water-Based Optimization for Solving Multi-Objective Technical and Economic Aspects of Optimal Power Flow Problems," Mathematics, MDPI, vol. 10(12), pages 1-22, June.

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