Multi-Objective Particle Swarm for Optimal Load Shedding Remedy Strategies of Power System

Load shedding is an emergency strategy that mitigates substantial mismatch between the generation and the loads. It generally sustains system stability during/after severe disturbances. This article proposes robust, simple, and innovative Under-Frequency Load Shedding (UFLS) technique based on Multi...

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Bibliographic Details
Published in:Electric power components and systems 2019-11, Vol.47 (18), p.1651-1666
Main Authors: Hafez, Ahmed A., Hatata, Ahmed Y., Abdelaziz, Almoataz Y.
Format: Article
Language:English
Subjects:
adaptive
Adaptive algorithms
Computer simulation
genetic algorithm
Genetic algorithms
Load
Load shedding
lowest swing frequency
Multiple objective analysis
Particle swarm optimization
particles swarm optimization
Power factor
relay
Systems stability
Test systems
trip delay
Viability
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Summary:Load shedding is an emergency strategy that mitigates substantial mismatch between the generation and the loads. It generally sustains system stability during/after severe disturbances. This article proposes robust, simple, and innovative Under-Frequency Load Shedding (UFLS) technique based on Multi-Objective Particle Swarm Optimization (MOPSO). MOPSO has the objectives of: minimizing the amount of the dropped load and maximizing the lowest swing frequency. The functionality and feasibility of the proposed MOPSO are corroborated via comprehensive comparison with traditional, adaptive, Single Objective PSO (SOPSO), and Genetic Algorithm (GA) UFLS schemes. IEEE 9-bus and 39-bus systems are used cases for examining the reliability, applicability, and viability of the proposed MOPSO. Different scenarios as: outage of single, multiple generating plants and load increase are applied in the test systems, while load shedding is executed via MOPSO, SOPOS, GA, traditional, and adaptive UFLS approaches. The DigSilent power factor software is used for simulating the test systems while subjected to the different disturbance levels. MATLAB is used for coding SOPSO, MOPSO, adaptive, and GA algorithms. The results show that MOPSO-based UFLS relay produces higher lowest swing frequency and lower amount of dropped load than SOPSO and GA. MOPSO requires less computation requirements than GA approach.
ISSN:1532-5008
1532-5016
DOI:10.1080/15325008.2019.1689454