Multiobjective Metaheuristics Artificial Fish School (FAFS) and Evolutionary Particles Swarm Optimization with Global Individual Stochastic Topology (FEPSO GIST). Part I: Framework and Theoretical Developments
DOI:
https://doi.org/10.21501/21454086.1370Keywords:
Artificial Fish School, Electric Distribution Systems, MetaHeuristics, Particles Swarm, Load UnbalanceAbstract
This work presents a model to Low Voltage (LV) Unbalance Degree Optimization in a Three-phase Electric Distribution Network (EDN). The combination of two new Fuzzy-MultiObjective MetaHeuristics FEPSO GIST (Fuzzy Particles Swarm Optimization with Global/Individual Stochastic Topology) proposed by the author and, FAFS (Fuzzy Artificial Fish Shool) extended to MultiObjective domain by the author, using Fuzzy Sets, are presented. Of multiple problems resulting from such unbalance degree, are considered the technical losses and the voltage drops. Both aspects are fundamentals in the rational use of energy, when this objective is focused from the offer side, and are observed for Regulatory Authority. In addition, a MatHeuristic approach composed for the classical approach based in Mixed-Interger Linear Programming and FEPSO GIST-FAFS MetaHeuristics, is introduced. In this Part I of the work, the framework and theoretical developments, required for the Models application, are presented.Downloads
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