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Using a Meta Heuristic Algorithm, Design Simulation of Improved Optimal Power Flow in IEEE-118 Bus System

Chetan Khemraj, Arpit Sharma, Balwant Singh Kuldeep

Abstract


OPF algorithms, which are a major focus of current research, are critical for the efficient monitoring and preparation of power systems. Optimal power flow reduces the objective function. The number of objectives that can be pursued is limitless. This is the objective. Researchers are now looking into the optimum approach to transport power to keep fuel costs low while maintaining specified generator power outputs and voltages. Depending on the utility's interests and requirements, any other target could be picked instead. This encompasses linear, nonlinear, and quadratic programming, as well as Newton-based techniques, as well as parametric and interior point approaches. Soft computing technologies and other alternatives to classic algorithms have gained popularity as potential replacements for traditional algorithms. Due to these disadvantages, soft computer-based optimization approaches are required. Many sophisticated solutions for tackling the OPF problem have been proposed in the literature, including evolutionary programming and genetic algorithms. We've created a new cuckoo search approach that saves time and money while maintaining some limitations in place. The IEEE-118 bus system is used to test the suggested algorithm. A big improvement can be seen after implementing the recommended system. Losses in a PV system connected to the utility grid are examined. Keywords-Optimal Power Flow, Meta Heuristic Model, Cuckoo Search Algorithm, IEEE-118 Bus System

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