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Transmission expansion planning systems using algorithm genetic with multi-objective criterion
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2017
Year
Electrical EngineeringEngineeringEnergy ManagementIntelligent OptimizationComputer EngineeringGenetic AlgorithmSystems EngineeringPower System OptimizationHybrid Optimization TechniqueTransmission ExpansionMulti-objective OptimizationAppropriate Genetic OperatorsCombinatorial OptimizationTransportation EngineeringEvolutionary Multimodal OptimizationEvolutionary ProgrammingOperations Research
In this paper the problem of planning the expansion of the transmission network (PERT) by means of a genetic algorithm on principles of multi-objective optimization (AGM) resolved. The proposed model uses an appropriate coding to optimize the PERT. In addition, appropriate genetic operators developed for efficient search space of feasible solutions. The model solves simultaneously: Minimize investment costs PERT, improve voltage levels at nodes and minimize losses on the lines of the transmission system. The AGM is tested in the system Garver 6 nodes and 24 nodes system IEEE_RTS achieving the best solutions.