Multi-objective Optimization Approach for Optimal Distributed Generation Sizing and Placement

Abstract—This article describes a multi-objective optimization method to solve the optimal distributed generation sizing and placement. The optimization problem considers two objectives: minimizing the total real power losses of the network and minimizing the overall distributed generation installation cost. The objectives are combined into a scalar objective optimization problem by using weighted sum method. Both objective functions and equality and inequality constraints are formulated as a non-linear program and solved by a sequential quadratic programming deterministic technique. The multi-objective optimization method gives several answers instead of a single (unique) one. These answers are optimal, and the designer (decision maker) can select the proper solution according to subjective preferences. These optimum results are known as the Pareto front. A fuzzy decision-making procedure for order preference is used for finding the best compromise solution from the set of Pareto solutions. The proposed method is tested using a 15-bus radial distribution system to show its applicability. A comparative study is performed to evaluate two cases—a single distributed generation unit installation and a multiple distributed generation installation—ending by a comparative study of the two cases.