The economic emission dispatch (EED) problem in a combined arrangement of power system integrated with solar photovoltaic source is solved in this paper. A novel algorithm named as Improved Multi-Objective Teaching Learning Based Optimization (IMOTLBO) has been proposed to address this inherently multi-objective problem. The concept of adaptive learning and self-motivation have been introduced to improve the convergence, and exploitation capability of the Teaching Learning Based Optimization (TLBO) algorithm. An effective constraint handling technique is applied to achieve the minimum constraint violation by restricting the solutions inside the feasible area. The Fuzzy Inference System (FIS) is also implemented to obtain best compromise solution among all the Pareto solutions present in Pareto front. The proposed algorithm is tested on two different test cases at various solar radiations. The Pareto optimal fronts for different hours of the day have been obtained suggesting the possible scheduling at the corresponding durations. The selection of the dispatch schedule is from the Pareto front using the FIS. It has been observed to show effective reduction of both cost and emission. The traditional method of assigning weights through the h-index concept to convert the multi-objective optimization problem to a single objective one is avoided.
Volume 12 | Issue 3