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Optimal Transmission Expansion Planning considering Distributed Generations by using Non-dominated sorting genetic algorithm-II (NSGAII)
  • Mehrdad Ahmadi Kamarposhti,
  • Ersan Kabalci
Mehrdad Ahmadi Kamarposhti
Department of Electrical Engineering, Jouybar Branch, Islamic Azad University, Jouybar, Iran. Corresponding Author Emails: [email protected], [email protected]
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Ersan Kabalci
Department of Electrical and Electronics Engineering, Nevsehir Haci Bektas Veli University, Nevsehir, Turkey.
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Reconstructing power systems has changed the traditional planning of power systems and has raised new challenges in transmission expansion planning (TEP). In this paper, investment cost, cost of density and dependability have been considered three objectives of optimization. Also, multi-objective genetic algorithm NSGAII was used to solve this non-convex and mixed integer problem. A fuzzy decision method has been used to choose the final optimal answer from the Pareto solutions obtained from NSGAII. Moreover, to confirm the efficiency of NSGAII multi-objective genetic algorithm in solving TEP problem, the algorithm was implemented in an IEEE 24 bus system and the gained results were compared with previous works in this field.