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A Novel Stochastic Optimizer Solving Optimal Reactive Power Dispatch Problem Considering Renewable Energy Resources

Author

Listed:
  • Mohammed Hamouda Ali

    (Department of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Cairo 11751, Egypt)

  • Ahmed Mohammed Attiya Soliman

    (Department of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Cairo 11751, Egypt)

  • Mohamed Abdeen

    (Department of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Cairo 11751, Egypt)

  • Tarek Kandil

    (School of Engineering and Technology, Western Carolina University, Cullowhee, NC 28723, USA)

  • Almoataz Y. Abdelaziz

    (Faculty of Engineering and Technology, Future University in Egypt, Cairo 11835, Egypt)

  • Adel El-Shahat

    (Energy Technology Program, School of Engineering Technology, Purdue University, West Lafayette, IN 47907, USA)

Abstract

Optimal Reactive Power Dispatch (ORPD is thought of as a noncontinuous, nonlinear global optimization problem. Within the system’s constraints, the ORPD manages to accomplish the reactive power flow. Due to its more intricate linkage of variables, the reactive power issue is more challenging to resolve than the optimum power flow issue. With the existence of renewable energy resources (RERs), solving the ORPD problem to attain the most stable and secure system condition has become a more challenging task. The goal of this article is to solve the objective function of ORPD combined with RERs using a metaheuristic novel optimizer named the African Vultures Optimization Algorithm abbreviated by (AVOA), where the formulation of the ORPD issue including minimization of three single objective functions as follows, voltage deviation, system operating cost, and real power loss, is introduced and also transmission power loss minimization is embraced with the simultaneous incorporation of the optimal renewable energy resources (RERs). Where the ORPD problem complexity grows exponentially with a mixture of continuous and discrete control variables, two distinct continuous and discrete types of optimization variables are considered, and the proposed single objective functions that meet different operating constraints are then transformed into a coefficient multi-objective ORPD problem and elucidated using the weighted sum approach. To validate the suggested algorithm’s effectiveness in addressing the ORPD issue, it is evaluated on three standard IEEE networks: the IEEE-30 bus small-scale network, the IEEE-57 bus medium-scale network, and the IEEE-118 bus large-scale network using different scenarios and the outcomes are compared to these other popular optimization techniques. The findings show that the suggested AVOA algorithm provides an efficient and sturdy high-quality solution for tackling ORPD situations and vastly enhances the overall system performance of power at all scales.

Suggested Citation

  • Mohammed Hamouda Ali & Ahmed Mohammed Attiya Soliman & Mohamed Abdeen & Tarek Kandil & Almoataz Y. Abdelaziz & Adel El-Shahat, 2023. "A Novel Stochastic Optimizer Solving Optimal Reactive Power Dispatch Problem Considering Renewable Energy Resources," Energies, MDPI, vol. 16(4), pages 1-39, February.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1562-:d:1057699
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    References listed on IDEAS

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    1. Rui Chi & Zheng Li & Xuexin Chi & Zhijian Qu & Hong-bin Tu, 2021. "Reactive Power Optimization of Power System Based on Improved Differential Evolution Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-19, February.
    2. Zelan Li & Yijia Cao & Le Van Dai & Xiaoliang Yang & Thang Trung Nguyen, 2019. "Finding Solutions for Optimal Reactive Power Dispatch Problem by a Novel Improved Antlion Optimization Algorithm," Energies, MDPI, vol. 12(15), pages 1-31, August.
    3. Mohamed Ebeed & Ayman Alhejji & Salah Kamel & Francisco Jurado, 2020. "Solving the Optimal Reactive Power Dispatch Using Marine Predators Algorithm Considering the Uncertainties in Load and Wind-Solar Generation Systems," Energies, MDPI, vol. 13(17), pages 1-19, August.
    4. Salah K. ElSayed & Ehab E. Elattar, 2021. "Slime Mold Algorithm for Optimal Reactive Power Dispatch Combining with Renewable Energy Sources," Sustainability, MDPI, vol. 13(11), pages 1-25, May.
    5. Yongquan Zhou & Jinzhong Zhang & Xiao Yang & Ying Ling, 2020. "Optimal reactive power dispatch using water wave optimization algorithm," Operational Research, Springer, vol. 20(4), pages 2537-2553, December.
    6. Ahmed M. Abd-El Wahab & Salah Kamel & Mohamed H. Hassan & Mohamed I. Mosaad & Tarek A. AbdulFattah, 2022. "Optimal Reactive Power Dispatch Using a Chaotic Turbulent Flow of Water-Based Optimization Algorithm," Mathematics, MDPI, vol. 10(3), pages 1-26, January.
    7. Walter M. Villa-Acevedo & Jesús M. López-Lezama & Jaime A. Valencia-Velásquez, 2018. "A Novel Constraint Handling Approach for the Optimal Reactive Power Dispatch Problem," Energies, MDPI, vol. 11(9), pages 1-23, September.
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    Cited by:

    1. Faraz Bhurt & Aamir Ali & Muhammad U. Keerio & Ghulam Abbas & Zahoor Ahmed & Noor H. Mugheri & Yun-Su Kim, 2023. "Stochastic Multi-Objective Optimal Reactive Power Dispatch with the Integration of Wind and Solar Generation," Energies, MDPI, vol. 16(13), pages 1-22, June.
    2. Seyed Mohammad Sharifhosseini & Taher Niknam & Mohammad Hossein Taabodi & Habib Asadi Aghajari & Ehsan Sheybani & Giti Javidi & Motahareh Pourbehzadi, 2024. "Investigating Intelligent Forecasting and Optimization in Electrical Power Systems: A Comprehensive Review of Techniques and Applications," Energies, MDPI, vol. 17(21), pages 1-35, October.

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