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 multiobjective 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.

Optimal placement of DG in radial distribution systems based on new voltage stability index under load growth

“…Authors presented optimal DG allocation and sizing in distribution systems with an objective of loss minimization, guarantee acceptable reliability level and voltage profile using GA [12]. A goal programming technique is developed in [13] for formulation and evaluation of a multi objective function, for optimal planning of DG units in the distribution system. Multiple DG placement using improved analytical method and loss sensitivity factor (LSF) method is presented in [14].…”

GA-based multi-objective optimization for distributed generations planning with DLMs in distribution power systems

“…The Chu-Beasley GA solves a nonlinear bi-level ODGP problem that maximizes the profits of DGs' owner subject to the minimization of payments procured by the DNO (López et al, 2012). Goal programming transforms a multi-objective ODGP into a single objective one which is solved by GA (Vinothkumar and Selvan, 2012). GA and decision theory are applied to solve an ODGP problem under uncertainty including power quality issues (Caprinelli et al, 2003).…”

Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

“…The ε-constrained method [21,22]; MCS [23]; goal programming [26,32]; fuzzy, WSM [29]; MCS, AHP [30]; PSO [31] and multi-criteria stochastic programming model (MSPM) [34]; VPQ (B): GA based fuzzy multi-objective method [54,60].…”