Generation Expansion Planning and Generation Location Based on Genetic Algorithm and Analytical Hierarchy Process

Generation Expansion Planning (GEP) is a large-scale nonlinear optimization problem with stochastic behavior. Generation system planers tend to use many different methods to address the expansion problem and to determine optimum plans by minimizing the mathematical objective function subject to different constraints. This paper presents an Improved Genetic Algorithm (IGA) to solve (GEP) problem. This algorithm uses Capacity Outage Table (COT) method، Analytical Hierarchy Process (AHP)، Successive Forward and Backward method and a new approach to improve the GA. The expert engineers suggestions have important role in this algorithm.