A Novel Hybrid GA-PSO-based Optimization of Transmission & Expansion Planning

In a power system environment, transmission & expansion planning (TNEP) is gaining attention and becoming an essential and computationally very challenging problem. Competent and robust optimization techniques are required to get the optimal solution technically and economically. Many computational techniques have been proposed to solve the TNEP problem earlier. Meta-heuristic techniques have gained a lot of importance in the last few years and successfully applied for TNEP. This paper aims to resolve transmission & expansion planning problems using hybrid algorithms. Two hybrid progressive algorithms based on the combination of PSO and GA methods are proposed and crossing over the PSO and GA have been implemented in this paper. The focus behind the proposed methods is to hybridize PSO and GA methods in a combination of parallel and series forms respectively. To validate the proposed hybrid algorithm and to test efficiency in comparison with other methods reported in the literature, it is tested on Garver’s-6 bus, IEEE-14 bus, and IEEE-24 bus test systems using MATLAB. The simulation and observations of the outcome demonstrate the effectiveness of the proposed hybrid algorithm's time and ability to find the global optimum solution.