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Load Curtailment Optimization Using the PSO Algorithm for Enhancing the Reliability of Distribution Networks

Author

Listed:
  • Laura M. Cruz

    (Department of Electric and Electronic Engineering, Universidad Nacional de Colombia, Bogotá 111321, Colombia)

  • David L. Alvarez

    (Department of Electric and Electronic Engineering, Universidad Nacional de Colombia, Bogotá 111321, Colombia)

  • Ameena S. Al-Sumaiti

    (Advanced Power and Energy Center, Electrical Engineering and Computer Science, Khalifa University, Abu Dhabi 127788, UAE)

  • Sergio Rivera

    (Department of Electric and Electronic Engineering, Universidad Nacional de Colombia, Bogotá 111321, Colombia)

Abstract

Power systems are susceptible to disturbances due to their nature. These disturbances can cause overloads or even contingencies of greater impact. In case of an extreme situation, load curtailment is considered the last resort for reducing the contingency impact, its activation being necessary to avoid the collapse of the system. However, load shedding systems seldom work optimally and cause either excessive or insufficient reduction of the load. To resolve this issue, the present paper proposes a methodology to enhance the load curtailment management in medium voltage distribution systems using Particle Swarm Optimization (PSO). This optimization seeks to minimize the amount of load to be cut off. Restrictions on the optimization problem consist of the security operation margins of both loading and voltage of the system elements. Heuristic optimization algorithms were chosen, since they are considered an online basis (allowing a short processing time) to solve the formulated load curtailment optimization problem. Best performances regarding optimal value and processing time were obtained using a PSO algorithm, qualifying the technique as the most appropriate for this study. To assess the methodology, the CIGRE MV distribution network benchmark was used, assuming dynamic load profiles during an entire week. Results show that it is possible to determine the optimal unattended power of the system. This way, improvements in the minimization of the expected energy not supplied (ENS) as well as the System Average Interruption Frequency Index (SAIDI) at specific hours of the day were made.

Suggested Citation

  • Laura M. Cruz & David L. Alvarez & Ameena S. Al-Sumaiti & Sergio Rivera, 2020. "Load Curtailment Optimization Using the PSO Algorithm for Enhancing the Reliability of Distribution Networks," Energies, MDPI, vol. 13(12), pages 1-15, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3236-:d:374918
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    References listed on IDEAS

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    1. Michael G. Pollitt, 2019. "The European Single Market in Electricity: An Economic Assessment," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 55(1), pages 63-87, August.
    2. Mohammad Dreidy & Hazlie Mokhlis & Saad Mekhilef, 2017. "Application of Meta-Heuristic Techniques for Optimal Load Shedding in Islanded Distribution Network with High Penetration of Solar PV Generation," Energies, MDPI, vol. 10(2), pages 1-24, January.
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    Cited by:

    1. Florin-Constantin Baiceanu & Ovidiu Ivanov & Razvan-Constantin Beniuga & Bogdan-Constantin Neagu & Ciprian-Mircea Nemes, 2023. "A Continuous Multistage Load Shedding Algorithm for Industrial Processes Based on Metaheuristic Optimization," Mathematics, MDPI, vol. 11(12), pages 1-19, June.
    2. Julian Garcia-Guarin & David Alvarez & Arturo Bretas & Sergio Rivera, 2020. "Schedule Optimization in a Smart Microgrid Considering Demand Response Constraints," Energies, MDPI, vol. 13(17), pages 1-19, September.

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