A reliable approach for solving the transmission network expansion planning problem using genetic algorithms

摘要

This paper presents a reliable approach for solving the transmission network expansion planning (TNEP) problem through a genetic algorithm (GA).Gas have demonstrated the ability to deal with non-convex, non-linear, integer-mixed optimization problems, such as the TNEP problem, better than a number of mathematical methodologies. The procedure presented consists on finding unfeasible solutions for he problem through the GA. These solutions are used for predicting the cost of the optimum solution using a 'loss of load limit curve', of the transmission system. Once this cost is estimated, the optimum solution can be found by performing a local search starting from the unfeasible solutions that have costs close to the estimated cost. This approach makes the GA more robust and reliable for solving the problem for different transmission systems.