Abstract
This paper presents biogeography-based optimization (BBO) and grey wolf Optimization(GWO) for solving the multi-constrained optimal power flow (OPF) problems in the power system. In this paper, the proposed algorithms have been tested in 9-bus system under various conditions along with IEEE 30 bus test system. A comparison of simulation results reveals optimization efficacy of the proposed scheme over evolutionary programming (EP), genetic algorithm (GA), mixed-integer particle swarm optimization (MIPSO) for the global optimization of multi-constraint OPF problems. It is observed that GWO is far better in comparison to other listed optimization techniques and can be used for aforesaid problems with high efficiency.
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