López-Lezama, Jesús M., Villada, Fernando, and Muñoz, Nicolás
Abstract
This paper presents an assessment of optimal location and sizing of distributed generation in distribution systems. For such an assessment the following search techniques were implemented: i) simulated annealing, ii) variable neighborhood search, iii) genetic algorithm and iv) hybrid genetic algorithm. Two objectives have been considered in the optimal location and sizing problem: the minimization of electric power losses and the improvement of voltage profile. To compare the effectiveness of the methodologies a 34 bus distribution test system is used. The correct location and sizing of the distributed generation allowed substantially improving the voltage profile of the network and reducing in 80% the power losses in the test system. [ABSTRACT FROM AUTHOR]
Narváez, Pablo A., López-Lezama, Jesús M., and Velilla, Esteban
Abstract
This paper presents a methodology for optimal Distributed Generation (DG) allocation using a hybrid genetic algorithm. In this case, the objective function is the minimization of power losses. The proposed algorithm involves an artificial neural network to evaluate the fitness function and a local search subroutine that allows the algorithm to explore a wider search space, and eventually, escape from local optimal solutions. The proposed approach was tested on a 34-bus system showing that the proper allocation of DG units allows the reduction of active power losses and the improvement of voltage profile. [ABSTRACT FROM AUTHOR]
Esteban Velilla, Pablo A Narváez, and Jesús M. López-Lezama
Subjects
Mathematical optimization, Electric losses, Computer science, Strategy and Management, Subroutine, Industrial and Manufacturing Engineering, Neural networks (Computer science), Reduction (complexity), Genetic algorithm, Distribución de energía eléctrica, algoritmos genéticos, Local search (optimization), Perdidas eléctricas, Fitness function, Artificial neural network, Electric power distribution, business.industry, generación distribuida, Genetic algorithms, AC power, Geotechnical Engineering and Engineering Geology, redes neuronales artificiales, Computer Science Applications, General Energy, Redes neurales (computadores), Distributed generation, business, Food Science
Abstract
RESUMEN: En este artículo se presenta una metodología para la ubicación óptima de Generación Distribuida (GD) usando un algoritmo genético híbrido. En este caso la función objetivo es la reducción de pérdidas. El algoritmo propuesto incorpora una red neuronal artificial para evaluar la función de adaptación y una búsqueda local que permite al algoritmo explorar un espacio de búsqueda más amplio. La contribución principal del artículo es la combinación de técnicas metaheurísticas con técnicas de inteligencia artificial para resolver un problema de optimización multi-modal y no convexo. La metodología propuesta es probada en un sistema de 34 barras mostrando que la ubicación apropiada de las unidades de GD permite reducir las pérdidas activas y mejorar el perfil de tensiones. ABSTRACT: This paper presents a methodology for optimal Distributed Generation (DG) allocation using a hybrid genetic algorithm. In this case, the objective function is the minimization of power losses. The proposed algorithm involves an artificial neural network to evaluate the fitness function and a local search subroutine that allows the algorithm to explore a wider search space, and eventually, escape from local optimal solutions. The proposed approach was tested on a 34-bus system showing that the proper allocation of DG units allows the reduction of active power losses and the improvement of voltage profile. COL0010477
Published
2015
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