Network Expansion Planning Using Improved Controlled NSGA-II

SUMMARY This paper presents the application of multiobjective optimization methods to network expansion planning. Distribution network expansion planning minimizes system cost and distribution loss while satisfying the constraints. Problem formulation yields combinatorial optimization problems that are difficult to solve due to their complexity. This research applies a genetic algorithm, which is a meta‐heuristics method. The present study proposes a new method of multiobjective optimization: NSGA‐II, SPEA2, and Controlled NSGA‐II are assumed to be the best methods now. The proposed method introduces the concept of a linkage identification genetic algorithm, enabling more efficient searching than methods hitherto known. In the past, most research on network expansion planning did not include the load curve. This research demonstrates that the investigation must include the load curve. It also proposes a new method of search including the load curve.