Electric Distribution Network Multiobjective Design Using a Problem-Specific Genetic Algorithm

Carrano, Eduardo G.; Soares, L. A.; Takahashi, Ricardo H. C.; Saldanha, R.R.; Neto, Oriane M.

doi:10.1109/tpwrd.2005.858779

Cited by 150 publications

(85 citation statements)

References 24 publications

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“…Constraints I, II, and III are commonly adopted in the literature [4,5]. The constraint IV is employed here due to reasons mentioned in Section 1.…”

Section: Ax ) II Line Flow Constraints (Or Device Capacity Constraints)mentioning

confidence: 99%

“…Every network operator has a different policy regarding the operation constraints of their power systems and different repositories of electrical facilities. Most studies evaluate the reliability of distribution networks based on the average failure rates and restoration times of components, in which reserve cables are considered as options to enhance the network reliability [4,5]. The result of such reliability analysis can then be capitalized into customer outage cost to include in the overall cost to be optimized [4] or can be treated as a separate objective function [5].…”

Section: Introductionmentioning

confidence: 99%

“…Most studies evaluate the reliability of distribution networks based on the average failure rates and restoration times of components, in which reserve cables are considered as options to enhance the network reliability [4,5]. The result of such reliability analysis can then be capitalized into customer outage cost to include in the overall cost to be optimized [4] or can be treated as a separate objective function [5]. However, it is shown that reliability in practice is a relative index as its calculation involves many intricate problems with high uncertainty [6].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Medium-Voltage Distribution Network Expansion Planning with Gene-pool Optimal Mixing Evolutionary Algorithms

Luong¹,

Grond

Bosman³

et al. 2014

Lecture Notes in Computer Science

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Abstract. Medium-voltage distribution network expansion planning involves finding the most economical adjustments of both the capacity and the topology of the network such that no operational constraints are violated and the expected loads, that the expansion is planned for, can be supplied. This paper tackles this important real-world problem using realistic yet computationally feasible models and, for the first time, using two instances of the recently proposed class of Gene-pool Optimal Mixing Evolutionary Algorithms (GOMEAs) that have previously been shown to be a highly efficient integration of local search and genetic recombination, but only on standard benchmark problems. One GOMEA instance that we use employs linkage learning and one instance assumes no dependencies among problem variables. We also conduct experiments with a widely used traditional Genetic Algorithm (GA). Our results show that the favorable performance of GOMEA instances over traditional GAs extends to the real-world problem at hand. Moreover, the use of linkage learning is shown to further increase the algorithm's effectiveness in converging toward optimal solutions.

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“…Constraints I, II, and III are commonly adopted in the literature [4,5]. The constraint IV is employed here due to reasons mentioned in Section 1.…”

Section: Ax ) II Line Flow Constraints (Or Device Capacity Constraints)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Medium-Voltage Distribution Network Expansion Planning with Gene-pool Optimal Mixing Evolutionary Algorithms

Luong¹,

Grond

Bosman³

et al. 2014

Lecture Notes in Computer Science

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“…En [3] se presenta un modelo que considera como funcionesobjetivo los costos y confiabilidad del sistema, y en la solución usan un algoritmo de búsqueda tabú. En [4] emplean un modelo matemático no lineal entero mixto que minimiza dos funciones-objetivo: económica y confiabilidad, y en la solución se valen de un algoritmo genético especializado. En [2,5] se emplea un algoritmo elitista de ordenamiento no dominado (NSGA-II), en la solución del problema multiobjetivo, donde el modelo matemático empleado es no lineal entero mixto.…”

Section: Introductionunclassified

Reconfiguración multiobjetivo en sistemas de distribución primaria de energía

Salazar-Fonseca

Pablo-de-la-Fé-Dotres

Torres-Guerrero

2017

Ingeniare. Rev. chil. ing.

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RESUMENEste trabajo aborda el problema de la disminución de las pérdidas de potencia en las redes de distribución sin afectar la calidad del servicio eléctrico ofrecido; para lo que se propone una metodología de reconfiguración multiobjetivo de estas redes. En el planteamiento del problema se trabaja con dos funciones objetivos; el Valor Actual Neto de los Costos (VANC) y la Duración Equivalente de la Potencia Interrumpida (DEPI). Mientras que en la solución del modelo se emplea un algoritmo evolutivo elitista de ordenamiento no dominado (NSGA-II), el que se implementa con ayuda del MATLAB, determinando un conjunto de soluciones factibles. La metodología propuesta es implementada en la reconfiguración de los circuitos Y-410, Y-283 y Y-285 de la ciudad de Camagüey, Cuba, donde se logran reducir las pérdidas de potencia de la red analizada en 51,7 kW y mejorar la calidad del servicio que se brinda, disminuyendo a 0,3966 horas/año las horas equivalentes en que falla el servicio eléctrico a cada kVA instalado en los clientes.Palabras clave: NSGA-II, pérdidas de potencia, reconfiguración multiobjetivo de redes de distribución. Y-410, Y-283 and Y-285 in the Camagüey city, Cuba, where the power losses were reduced in 51.7 kW, improving in that way the quality of the service supplied, diminishing to 0.3966 hours/year the equivalent hours in which the electric service fails for each kVA installed in the clients. ABSTRACT This paper presents the problem of power loss reduction in the distribution power systems without affecting the supplied electrical service quality. An approach of this problem using a methodology for the multi-objective reconfiguration is proposed. In the statement of the problem two objective functions are used: The Net Actual Value of Costs (VANC) and the Equivalent Duration of Interrupted Power (DEPI). While in the model's solution a Non-dominated Sorting Genetic Algorithm (NSGA-II) is used, which is an evolutionary algorithm implemented in MATLAB from where a feasible set of solutions is obtained. The methodology proposed is used in the reconfiguration of circuits

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“…기존 전력시장의 모델링에서 경제학자들의 연구는 상대적으로 더 많았는데, 주로 가격과 시장균형에 대한 연구 (Ventosa et al, 2005), 경매전략에 대한 연구 (Galiana et al, 2002;Hudson, 2001), 게임이론이나 유전 알고리즘 적용 등이 있다 (Son et al, 2004;Richter et al, 1998). 반면에 하나의 전력회사가 외부로부터의 전력 구매가 아닌 자신의 송배전망에서의 전력을 어떻게 분배하는 것이 경제적 인지에 관한 연구는 "전력배분계획(power distribution planning)" 또는 "최적 전력흐름(OPF : optimla path flow) 문제"란 이름으로 상당히 많은 연구 성과가 존재한다 (Acharyaa, 2006;Borges and Falco, 2006;Carrano et al, 2006;Fang and David, 1999;Kator and Leung, 1989;Pavia et al, 2005). 이 분야의 연구들은 단일기간 고 려, 다중기간 고려 등으로 나누어지며, 지선 네트워크(feeder) 수준 및 여러 개의 지선을 하나의 시스템으로 보는 수준 등 다 양한 문제가 정의되어 연구되어왔다.…”

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A Study on Electrical Power Trading in Minimum Price Wholesale Market

Seo¹,

Lee

2011

IE interfaces

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The importance of renewable energy technology is discussed and next generation power transmission networks, which is called the smart grid, are constructed in developed countries. However for construction and operation of the smart grid, it is required not only to develop the electrical power generation technologies and transmission equipments but also to study systematic analysis and optimization for design and operation of the smart grid. In this paper we study electrical power trade in the smart grid using operations research models and simulation methods. We also consider future electrical power exchange markets in Korea and build four scenarios and the related optimization and simulation models, which reflect electrical power transaction pricing strategies of stake-holders. We can also simulate electrical power exchange market and analyze the results of electrical power trading, which can give us some insights for future electrical power exchange market. 1)

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Electric Distribution Network Multiobjective Design Using a Problem-Specific Genetic Algorithm

Cited by 150 publications

References 24 publications

Medium-Voltage Distribution Network Expansion Planning with Gene-pool Optimal Mixing Evolutionary Algorithms

Medium-Voltage Distribution Network Expansion Planning with Gene-pool Optimal Mixing Evolutionary Algorithms

Reconfiguración multiobjetivo en sistemas de distribución primaria de energía

A Study on Electrical Power Trading in Minimum Price Wholesale Market

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