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Optimal power flow in power system using walrus optimization algorithm
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AI
DOI：10.1007/s12065-026-01165-8.png)
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Abstract
En 中文
A comprehensive knowledge of optimal power flow (OPF) methods is essential for effective operation and planning of the electric system. OPF methods can be utilized to find the ideal state of the electric system, including fuel cost reduction with improvement of voltage profile, active and reactive power loss minimization while matching all system constraints. This paper provides an extensive analysis of conventionally constrained optimal power flow algorithms mainly focused on Walrus optimization technique (WaOA) to solve the different OPF issues. In order to achieve an efficient balance between exploration and exploitation, WaOA implements a data-driven exploration method with an adaptive population size that rapidly declines based on the previous search results. This proposed strategy is tested on IEEE 30-bus and IEEE 57-bus test systems, and it is contrasted with conventional metaheuristic techniques under the same restriction. WaOA decreases voltage deviation, increases the voltage stability index to 0.113, limits active power loss to 2.85 MW, and achieves a minimal fuel cost of 799.07 $/h for the IEEE 30-bus system. WaOA achieves an acceptable fuel cost of 38,433.46 $/h for the IEEE 57-bus system with lower power losses and better voltage profiles. WaOA consistently outperforms the evaluated algorithms in terms of convergence and computing time, demonstrating its resilience and efficacy for OPF applications.
Keywords:
Optimal power flow
Optimization
Constraints
Walrus optimization technique
Journal
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2.6
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