Optimal distributed generation planning considering reliability, cost of energy and power loss
Author(s) -
H. Yassami,
Ali Moeini,
M R Rafiei S,
Ahmad Darabi,
Amir Bagheri
Publication year - 2011
Publication title -
scientific research and essays
Language(s) - English
Resource type - Journals
ISSN - 1992-2248
DOI - 10.5897/sre10.955
Subject(s) - mathematical optimization , maximization , distributed generation , computer science , weighting , multi objective optimization , minification , reliability (semiconductor) , pareto principle , particle swarm optimization , evolutionary algorithm , function (biology) , key (lock) , set (abstract data type) , power (physics) , mathematics , medicine , physics , computer security , quantum mechanics , evolutionary biology , biology , radiology , programming language
This paper suggests a Pareto based Multi-objective Optimization Algorithm (MOA) called Strength Pareto Evolutionary Algorithm (SPEA) for Distributed Generation (DG) planning in distribution networks. As opposed to conventional multi-objective optimization techniques that correlate different objective functions by utilizing of weighting coefficients and create one single objective function, in SPEA, each objective function is optimized separately. Since the objective functions are in conflict with each other, the SPEA produces a set of optimum solutions instead of one single optimum one. Three different objective functions are considered in this study: (1) minimization of power generation cost (2) minimization of active power loss (3) maximization of reliability level. The goal is to optimize each objective function. The site and size of DG units are assumed as design variables. The results are discussed and compared with those of traditional distribution planning and also with Partial Swarm Optimization (PSO). Key words: Distributed generation, distribution network planning, multi-objective optimization.
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