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Event-Based Under-Frequency Load Shedding Scheme in a Standalone Power System

Author

Listed:
  • Ying-Yi Hong

    (Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan 32023, Taiwan)

  • Chih-Yang Hsiao

    (Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan 32023, Taiwan)

Abstract

Under-frequency load shedding (UFLS) prevents a power grid from a blackout when a severe contingency occurs. UFLS schemes can be classified into two categories—event-based and response-driven. A response-driven scheme utilizes 81L relays with pre-determined settings while an event-based scheme develops a pre-specified look-up table. In this work, an event-based UFLS scheme is presented for use in an offshore standalone power grid with renewables to avoid cascading outages due to low frequency protection of wind power generators and photovoltaic arrays. Possible “N-1” and “N-2” forced outages for peak and off-peak load scenarios in summer and winter are investigated. For each forced outage event, the total shed load is minimized and the frequency nadir is maximized using particle swarm optimization (PSO). In order to reduce the computation time, initialization and parallel computing are implemented using MATLAB/Simulink because all forced outage events and all particles in PSO are mutually independent. A standalone 38-bus power grid with two wind turbines of 2 × 2 MW and photovoltaics of 7.563 MW was studied. For each event, the proposed method generally obtains a result with a smaller shed load and a smaller overshoot frequency than the utility and existing methods. These simulation results verify that the proposed method is practically applicable in a standalone power system with penetration of renewables.

Suggested Citation

  • Ying-Yi Hong & Chih-Yang Hsiao, 2021. "Event-Based Under-Frequency Load Shedding Scheme in a Standalone Power System," Energies, MDPI, vol. 14(18), pages 1-19, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5659-:d:631720
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    References listed on IDEAS

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    1. Khezri, Rahmat & Golshannavaz, Sajjad & Vakili, Ramin & Memar-Esfahani, Bahram, 2017. "Multi-layer fuzzy-based under-frequency load shedding in back-pressure smart industrial microgrids," Energy, Elsevier, vol. 132(C), pages 96-105.
    2. Changrui Deng & Xiaoyuan Zhang & Yanmei Huang & Yukun Bao, 2021. "Equipping Seasonal Exponential Smoothing Models with Particle Swarm Optimization Algorithm for Electricity Consumption Forecasting," Energies, MDPI, vol. 14(13), pages 1-14, July.
    3. Talaat, M. & Hatata, A.Y. & Alsayyari, Abdulaziz S. & Alblawi, Adel, 2020. "A smart load management system based on the grasshopper optimization algorithm using the under-frequency load shedding approach," Energy, Elsevier, vol. 190(C).
    4. Martha N. Acosta & Choidorj Adiyabazar & Francisco Gonzalez-Longatt & Manuel A. Andrade & José Rueda Torres & Ernesto Vazquez & Jesús Manuel Riquelme Santos, 2020. "Optimal Under-Frequency Load Shedding Setting at Altai-Uliastai Regional Power System, Mongolia," Energies, MDPI, vol. 13(20), pages 1-18, October.
    5. Muhammed Y. Worku & Mohamed A. Hassan & Mohamed A. Abido, 2019. "Real Time Energy Management and Control of Renewable Energy based Microgrid in Grid Connected and Island Modes," Energies, MDPI, vol. 12(2), pages 1-18, 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. Lutfu Saribulut & Gorkem Ok & Arman Ameen, 2023. "A Case Study on National Electricity Blackout of Turkey," Energies, MDPI, vol. 16(11), pages 1-20, May.

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