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Pareto-based multi-stage and multi-objective planning of DG enhanced distribution system

Barco, John E (2014) Pareto-based multi-stage and multi-objective planning of DG enhanced distribution system. IJOEE - International Journal of Electrical Energy, 2 (1). pp. 45-52. ISSN 2301-3656

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The efficient planning of radial distribution feeders is important to ensure energy supply to load demands as suitable quality of the service is provided. This planning is usually separated into two decision-making stages, i.e., design of topology infrastructure and protection system shaping. Moreover, these stages are performed pursuing the achievement of multiple objectives such as costs minimization and reliability maximization. In consequence, a multi-stage and multi-objective optimization problem arises. In this paper, an efficient Pareto-based approach is proposed to solve the aforementioned kind of optimization. Infrastructure preparation considers possible interconnections between loads and installation of Distributed Generation (DG). Furthermore, the shaping of protection system considers the amount of devices as their efficient placement in the feeder. DG have been largely considered as an alternative to increase the operation performance of distribution systems (DSs), besides its merely function to provide energy. On the other hand, Non-Dominated Sorting Genetic Algorithm (NSGA-II) is implemented to solve each stage of the planning. Finally, simulations are applied on a 33-nodes test feeder with available sources to install DG

Tipo de Elemento: Artículo
Palabras Clave: distribution system planning, multi-objective optimization, multi-stage optimization, evolutionary algorithm, optimum reclosers placement, optimal reconfiguration, Pareto-optimal solutions
Asunto: T Tecnología > TK Electrical engineering. Electronics Nuclear engineering
Division: Facultad de Ingeniería > Programa de Ingeniería Electrónica > Trabajos de grado
Depósito de Usuario: Andres Pantoja
Fecha Deposito: 28 Jun 2018 05:03
Ultima Modificación: 28 Jun 2018 05:03

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