A Multi Objective Optimization of Transmission Expansion Planning Using Genetic Algorithm Considering Reliabilty Criteria

An electric power system plays a crucial role in the economic and social development of a country. Economic growth in India has spurred the need for more power and hence the infrastructure to transport the power. Sufficient transmission capacity is very essential in any long-term planning for improving the availability and supply of power. So Transmission Expansion Planning (TEP) is integral to the development of a stable and reliable power infrastructure. TEP infuture is a very complex task which needs a coordinated and analytical analysis of various scenarios and contingencies. In this work we have implemented a scheme for TEP which factors load growth and considers N-1 contingency. Both economics and technical considerations are considered in the appraisal of the most desirable transmission network. A multi objective optimization approach is suggested and the optimization of the expansion plan is done with the help of Backward Search (BS), Forward Search (FS), Hybrid Search (HS) and Genetic Algorithm (GA). The TEP is prepared for a 6 Bus-Roy Billinton Test System (RBTS). Transmission Planning Index (TPI) is introduced to provide a clear indication to the planner about the choice of the plan. The plans suggested by different optimization algorithms are compared in terms of performance measures and reliability indices.