Abstract: Optimal power flow is an optimizing tool for operation and planning of modern power systems. This OPF problem involves the optimization of various types of objective functions while satisfying a set of operational and physical constraints while keeping the power outputs of generators, bus voltages, shunt capacitors/reactors and transformers tap settings in their limits. In an interconnected power system network obtaining maximum performance, maintaining system stability limits and facilitating efficient system operation are the challenging tasks. This project presents a new hybrid particle swarm optimization algorithm as a modern optimization tool to solve the optimal power flow (OPF) problem. The objective functions considered are the system power losses, fuel cost, valve point effects, ramp-rate limits, prohibited operating zones, and spinning reserves. The proposed algorithm makes use of the PSO, known for its global searching capabilities, to allocate the optimal control settings. PSO algorithm is combined with conventional IPM algorithm to form hybrid PSO algorithm. A hybrid inequality constraint handling mechanism that preserves only feasible solutions is incorporated in the proposed approach. To demonstrate its robustness, the proposed algorithm was tested on the IEEE 30-bus system. Several cases were investigated to test and validate the consistency of detecting optimal solution for each objective. The results show that the proposed hybrid method successfully and efficiently handles the equality and inequality constraints for PSO algorithms.
Keywords: PSO algorithms, OPF problem, Optimal power flow problem, EEE 30-bus system.
Title: NEW HYBRID PSO ALGORITHM FOR NON-CONVEX OPTIMAL POWER FLOW PROBLEM
Author: M. Sreenivasa reddy, V. Leela kumar
International Journal of Electrical and Electronics Research
ISSN 2348-6988 (online)
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