A Genetic Algorithm based Transmission Expansion Planning

Z.M. Al-Hamouz, H. Al-Duwaish, A.H. Mantawy, I. El-Amin, and A. Al-Faraj (Saudi Arabia)


Planning, Transmission lines, GeneticAlgorithms, Optimization, Corona, Power Loss.


: This paper presents a new approach for formulating and solving the transmission expansion planning (TEP) problem. The main improvement is in introducing the corona power loss in the objective function and operating constraints. Introducing this new term reveals a nonlinear objective function which is solved by the genetic algorithms technique (GA). The corona power loss term has been tried for a practical number of sub-conductors (1, 2, 3, and 4) and practical sub-conductor radii. In order to test and justify this new formulation, it has been applied to Garver's 6-bus test sytem The outcome of the expansion process is the optimal scenario which defines the number of lines to be added. For each added line, the number and radii of sub conductors, phase spacing, height, and bundle radius are also generated as a result of the expansion process. When compared to previously reported TEP attempts, simulation results show a reduction in the total cost of the expanded network

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