Investigation on Security Constrained Optimal Power Flows using Meta-heuristic Techniques

In this work different Meta-heuristic Techniques have been endeavored for addressing the Security Constrained Optimal Power Flow (SCOPF) and Optimal Power Flow (OPF)problem for minimizing the total fuel cost of the system. Here four meta-heuristics i.e. Genetic Algorithm (GA), Big Bang-Big Crunch Al...

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Bibliographic Details
Published in2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) pp. 1 - 6
Main Authors Ankeshwarapu, Sunil, Sydulu, Maheswarapu
Format Conference Proceeding
LanguageEnglish
Published IEEE 21.07.2022
Subjects
Big bang-Big crunch Algorithm (BBBC)
Costs
Fuels
Genetic Algorithm (GA)
Genetic algorithms
Jaya Algorithm (JA)
Metaheuristics
Security
Shuffled Frog Leap based Algorithm (SFLA)
Simulation
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DOI10.1109/ICICCSP53532.2022.9862459

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Summary:In this work different Meta-heuristic Techniques have been endeavored for addressing the Security Constrained Optimal Power Flow (SCOPF) and Optimal Power Flow (OPF)problem for minimizing the total fuel cost of the system. Here four meta-heuristics i.e. Genetic Algorithm (GA), Big Bang-Big Crunch Algorithm (BBBC), Shuffled Frog Leap Algorithm (SFLA) and Jaya Algorithms (JA) have been discussed. The problem was simulated on IEEE 30 bus standard test system under MATLAB environment. The simulation results show that JA outperforms GA, SFLA, and BBBC in terms of overall cost and computational time.
DOI:10.1109/ICICCSP53532.2022.9862459