Transmission planning with security criteria via enhanced genetic algorithm

This paper proposes an enhanced genetic algorithm model, named EGA-TEP, to solve the transmission expansion planning (TEP) problem of electric power system networks. Heuristic information is integrated into the evolutionary process of metaheuristic to improve the expansion plans (solutions). This heuristic information is translated in the form of sensitivity indices, based on the circuit loading/overloading and observed load shedding, considering both the intact network and the “N-1” contingency operating conditions (security criteria). In addition, an iterative process of evolutionary runs (ERs) is adopted as the basis for designing the EGA-TEP. These contributions make the optimization tool more robust and ready to handle different types of systems. The efficiency of the proposed EGA-TEP tool is consistently evaluated through performance statistical indices. Results obtained with systems with different characteristics and dimensions are presented and widely discussed.