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.
Multi-objective Optimization Approach for Optimal Distributed Generation Sizing and Placement
Electric power components and systems ; 43 , 7 ; 828-836
2015
Aufsatz (Zeitschrift)
Englisch
Decision making models , Nonlinear programming , distributed generation installation cost , multi-objective optimization , Optimization techniques , Mathematical problems , Quadratic programming , sequential quadratic programming , Electricity generation , distributed power losses generation , Pareto optimum
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