Energy restoration in distribution systems using multi-objective evolutionary algorithm and an efficient data structure

Mansour, Moussa Reda; Santos, Adalberto J.; London, João Bosco Augusto; Delbem, Alexandre C. B.; Bretas, N.G.

doi:10.1109/ptc.2009.5282205

Cited by 26 publications

(28 citation statements)

References 8 publications

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“…In order to improve the EA performance in PDSR problems, the approach proposed by Santos et al [26,27] and Mansour et al [16] used a new tree encoding, named node-depth encoding (NDE) and its corresponding genetic operators [7]. The NDE can improve the performance obtained by EAs in PDSR problems because of the following properties:…”

Section: Introductionmentioning

confidence: 99%

“…The algorithm optimizes one combined objective function that weights the multiple objectives and penalizes the violation of constraints. The approach proposed in Mansour et al [16,17] uses the NDE and a modified version of the non-dominated sorting genetic algorithm-II (NSGA-II) [5]. Later, Santos et al [27] combined the NDE with a technique of multiObjective evolutionary algorithm (MOEA) based on sub-population tables, where each sub-population stores those solutions that better satisfy an objective or a constraint of the PDSR problem.…”

Section: Introductionmentioning

confidence: 99%

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Differential evolution using ancestor tree for service restoration in power distribution systems

Prado

Silva

Neto

et al. 2014

Applied Soft Computing

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Differential evolution using ancestor tree for service restoration in power distribution systems

Prado

Silva

Neto

et al. 2014

Applied Soft Computing

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“…[4], [5], [6], [7]; and the genetic operators that are used, generally these operators do not generate radial configurations [6]. In order to overcome such a hurdle, the MOEAs proposed in [8], [7], [1] use the tree encoding named Node-Depth Encoding (NDE) [9] to represent computationally the electrical topology of the DSs. The properties of NDE that improve MOEAs performance to treat SR problems are discussed in details in [7] and will be summarized in section II.…”

Section: Introductionmentioning

confidence: 99%

“…The method proposed in [8] combines NDE with a modified version of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) (NSDE hereafter). On the other side, the methodology proposed in [7], MoEA with Node-depth encoding named MEAN, uses NDE together with a technique of MOEA based on subpopulation tables, where each subpopulation stores the found solutions that better attend an objective or a constraint of the SR problem.…”

Section: Introductionmentioning

confidence: 99%

Integrating several subpopulation tables with node-depth encoding and strength Pareto for service restoration in large-scale distribution systems

Sanches

Gois²,

London³

et al. 2013

2013 IEEE Power &Amp; Energy Society General Meeting

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Abstract-Network reconfiguration for service restoration in distribution systems is a combinatorial complex optimization problem that usually involves multiple non-linear constraints and objectives functions. For large scale distribution systems, no exact algorithm has found adequate restoration plans in real-time. On the other hand, the combination of Multi-objective Evolutionary Algorithms (MOEAs) with the Node-Depth Encoding (NDE) has been able to efficiently generate adequate restoration plans for relatively large distribution systems (with thousands of buses and switches). The method called MEAN-NDS results from the combination of NDE with a technique of MOEA based on subpopulation tables and the MOEA called NSGA-II. In order to obtain a more efficient MOEA to treat service restoration problem in large scale distribution systems, this paper proposes a new method, which results from the combination of MEAN-NDS with the MOEA called SPEA-2. The idea is to improve the capacity of MEAN-NDS to explore both the search and objective spaces. Simulations results with distribution systems ranging from 632 to 1,277 switches, have shown that the proposed method found the configurations of lower switching operations, and explores the space of the objective solutions better than the MEAN-NDS, approximating better the Pareto-optimal front.

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“…(Zhu, 2002;Carreno et. al., 2008;Santos et al, 2008;Mendoza et al, 2006;Kumar et al, 2008;Mansour et al, 2009;Santos et al, 2010;Fantin et al, 2011). Tendo em vista a característica multiobjetivo do problema de restabelecimento de energia, para desenvolvimento da metodologia proposta utilizar-se-á o Algoritmo…”

Section: Motivaçãounclassified

Restabelecimento de energia em sistemas de distribuição de energia elétrica com priorização de chaves automáticas

Marquez¹

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1 Trata-se da versão corrigida da dissertação. A versão original encontra-se disponível na EESC/USP que aloja o programa de Pós-Graduação em Engenharia elétrica. Esta dissertação trata do problema de restabelecimento de energia em sistemas de distribuição de grande porte (com milhares de linhas, barras de carga e chaves seccionadoras) em situações de contingência. Este problema consiste basicamente na determinação de chaves seccionadoras que devem ser operadas para permitir a transferência de blocos de carga a fim de re-conectar consumidores fora de serviço atendendo às restrições operacionais do sistema. Remy Amorim Caero MarquezDiversas metodologias têm sido desenvolvidas para lidar com o problema de restabelecimento de energia. Entretanto, a maioria perde eficiência computacional quando aplicadas em sistemas de distribuição de grande porte e/ou não fazem distinção entre chaves manuais e automáticas (controladas remotamente).Propõe-se uma metodologia para obtenção, em tempo-real, de planos de restabelecimento de energia em sistemas de distribuição de grande porte, que priorize a utilização de chaves seccionadoras controladas remotamente. Priorizar a utilização de chaves controladas remotamente permite a obtenção de planos de restabelecimento mais rápidos de serem implantados. Para lidar com os múltiplos objetivos e restrições do problema de restabelecimento de energia, a metodologia proposta será baseada em Algoritmos Evolutivos Multi-Objetivo, enquanto que a eficiência computacional para possibilitar o tratamento de sistemas de grande porte será proporcionada através da utilização da codificação de dados denominada Representação Nó-Profundidade. Para validar a metodologia proposta realizarse-ão diversas simulações computacionais no sistema de distribuição real da cidade de São Carlos-SP, e nas suas versões duplicada, quadruplicada e octuplicada, considerando-se a ocorrência tanto de falta única quanto de múltiplas faltas. Several methodologies have been developed to deal with the service restoration problem in distribution systems. However, the majority of them demand high running time when used for large scale distribution systems and/or do not consider the existence of switches that can be remotely operated.It is proposed a methodology for determining, in real time, service restoration plans in large scale distribution systems. In order to determine service plans that can be implemented faster, the methodology will give priority to use remotely controlled switches. To deal with the multiple objectives and constraints of the service restoration problem, the proposed methodology will be based on Multi-objective Evolutionary algorithms. To guarantee computational efficiency to treat large scale distribution systems, the data encoding called Node-Depth Encoding will be used. The real distribution system of the São Carlos-SP city, and its doubled, quadruplicated and octuplicate versions will be used to validate the proposed methodology. It will be simulated cases considering one and multiple faults.

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Energy restoration in distribution systems using multi-objective evolutionary algorithm and an efficient data structure

Cited by 26 publications

References 8 publications

Differential evolution using ancestor tree for service restoration in power distribution systems

Differential evolution using ancestor tree for service restoration in power distribution systems

Integrating several subpopulation tables with node-depth encoding and strength Pareto for service restoration in large-scale distribution systems

Restabelecimento de energia em sistemas de distribuição de energia elétrica com priorização de chaves automáticas

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