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A Novel Constraint Handling Approach for the Optimal Reactive Power Dispatch Problem

Author

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  • Walter M. Villa-Acevedo

    (Departamento de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de Antioquia, Calle 70 No 52-21, Medellín 050010, Colombia)

  • Jesús M. López-Lezama

    (Departamento de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de Antioquia, Calle 70 No 52-21, Medellín 050010, Colombia)

  • Jaime A. Valencia-Velásquez

    (Departamento de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de Antioquia, Calle 70 No 52-21, Medellín 050010, Colombia)

Abstract

This paper presents an alternative constraint handling approach within a specialized genetic algorithm (SGA) for the optimal reactive power dispatch (ORPD) problem. The ORPD is formulated as a nonlinear single-objective optimization problem aiming at minimizing power losses while keeping network constraints. The proposed constraint handling approach is based on a product of sub-functions that represents permissible limits on system variables and that includes a specific goal on power loss reduction. The main advantage of this approach is the fact that it allows a straightforward verification of both feasibility and optimality. The SGA is examined and tested with the recommended constraint handling approach and the traditional penalization of deviations from feasible solutions. Several tests are run in the IEEE 30, 57, 118 and 300 bus test power systems. The results obtained with the proposed approach are compared to those offered by other metaheuristic techniques reported in the specialized literature. Simulation results indicate that the proposed genetic algorithm with the alternative constraint handling approach yields superior solutions when compared to other recently reported techniques.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2352-:d:168110
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    References listed on IDEAS

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    1. Zhong-Kai Feng & Wen-Jing Niu & Jian-Zhong Zhou & Chun-Tian Cheng & Hui Qin & Zhi-Qiang Jiang, 2017. "Parallel Multi-Objective Genetic Algorithm for Short-Term Economic Environmental Hydrothermal Scheduling," Energies, MDPI, vol. 10(2), pages 1-22, January.
    2. Jae-Kun Lyu & Jae-Haeng Heo & Jong-Keun Park & Yong-Cheol Kang, 2013. "Probabilistic Approach to Optimizing Active and Reactive Power Flow in Wind Farms Considering Wake Effects," Energies, MDPI, vol. 6(11), pages 1-21, October.
    3. Kyu-Hyung Jo & Mun-Kyeom Kim, 2018. "Improved Genetic Algorithm-Based Unit Commitment Considering Uncertainty Integration Method," Energies, MDPI, vol. 11(6), pages 1-18, May.
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    Cited by:

    1. Sulaiman Z. Almutairi & Emad A. Mohamed & Fayez F. M. El-Sousy, 2023. "A Novel Adaptive Manta-Ray Foraging Optimization for Stochastic ORPD Considering Uncertainties of Wind Power and Load Demand," Mathematics, MDPI, vol. 11(11), pages 1-35, June.
    2. Ashraf Ramadan & Mohamed Ebeed & Salah Kamel & Almoataz Y. Abdelaziz & Hassan Haes Alhelou, 2021. "Scenario-Based Stochastic Framework for Optimal Planning of Distribution Systems Including Renewable-Based DG Units," Sustainability, MDPI, vol. 13(6), pages 1-23, March.
    3. Martín M. Sánchez-Mora & Walter M. Villa-Acevedo & Jesús M. López-Lezama, 2023. "Multi-Area and Multi-Period Optimal Reactive Power Dispatch in Electric Power Systems," Energies, MDPI, vol. 16(17), pages 1-24, September.
    4. 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.
    5. Ovidiu Ivanov & Bogdan-Constantin Neagu & Gheorghe Grigoras & Mihai Gavrilas, 2019. "Optimal Capacitor Bank Allocation in Electricity Distribution Networks Using Metaheuristic Algorithms," Energies, MDPI, vol. 12(22), pages 1-36, November.
    6. 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.
    7. Asma Meddeb & Nesrine Amor & Mohamed Abbes & Souad Chebbi, 2018. "A Novel Approach Based on Crow Search Algorithm for Solving Reactive Power Dispatch Problem," Energies, MDPI, vol. 11(12), pages 1-16, November.
    8. 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.

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