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Distributed Generation Planning: A New Approach Based on Goal Programming

Abstract This article proposes a novel methodology that employs a goal programming technique and genetic algorithm for formulation and evaluation of a multi-objective function, respectively, for optimal planning of distributed generator units in the distribution system. The multi-objective function consists of various performance indices that govern the optimal operation of a distribution system with distributed generator units. The proposed method aims to greatly diminish the dependence in existing methods on the global preference information of the distribution system planner by means of simplicity in problem formulation utilizing a goal programming technique. The capacity of the distribution system to accept distributed generator integration is evaluated such that with the placement of every additional distributed generator unit, the value of multi-objective function reduces without any violation in the system operating constraints. The effectiveness of the proposed method is tested using various distribution systems of different sizes and configurations, and the results are validated with the existing methods, namely the iterative genetic algorithm method and the fuzzy embedded genetic algorithm method. Further, different types of distributed generator models are also employed to demonstrate the adaptability of the proposed method in distributed generator planning studies.