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Attainment of enhanced secured optimal power flow (OPF) has been established as one of the vital requirement of power system operation in a deregulated structure. This paper establishes a novel hybrid technique which is yielded by combining Radial Basic Function Neural Network (RBFNN) and Gravitational Search Algorithm (GSA). The new velocity and position of agents are less deviated by implementing RBFNN based GSA leading to realization of optimized Thyristor controlled series compensator (TCSC) parameters wherein the results are also compared with traditional GSA method and Fuzzy based GSA algorithm. The superiority of performance is established by comparing the proposed hybrid technique with the previously existing method. The Hybrid method proposed is implemented in MATLAB working platform and results are tested on standard IEEE 30 bus transmission system. The total generated power, power loss and cost of generation are evaluated with variation of system load and reduction in line power limit evaluates the system response to contingency.

Enhanced Secured Optimal Power Flow by TCSC Parameter Optimization using RBFNN based GSA