Multi-objective planning of electrical distribution systems incorporating sectionalizing switches and tie-lines using particle swarm optimization

Sahoo, Niranjan; Ganguly, Sanjib; Das, Dulal Chandra

doi:10.1016/j.swevo.2011.11.002

Cited by 84 publications

(66 citation statements)

References 29 publications

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“…Locations and sizes of new substations [26,29,30,32,36,38,54,55,58,66,80,85,89] Sizes of existing substations for reinforcement [24,26,27,29,32,34,36,38 …”

Section: Traditional Variablesmentioning

confidence: 99%

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A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches

Wang

Chen³

et al. 2017

Energies

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Due to the widespread deployment of distributed energy resources (DERs) and the liberalization of electricity market, traditional distribution networks are undergoing a transition to active distribution systems (ADSs), and the traditional deterministic planning methods have become unsuitable under the high penetration of DERs. Aiming to develop appropriate models and methodologies for the planning of ADSs, the key features of ADS planning problem are analyzed from the different perspectives, such as the allocation of DGs and ESS, coupling of operation and planning, and high-level uncertainties. Based on these analyses, this comprehensive literature review summarizes the latest research and development associated with ADS planning. The planning models and methods proposed in these research works are analyzed and categorized from different perspectives including objectives, decision variables, constraint conditions, and solving algorithms. The key theoretical issues and challenges of ADS planning are extracted and discussed. Meanwhile, emphasis is also given to the suitable suggestions to deal with these abovementioned issues based on the available literature and comparisons between them. Finally, several important research prospects are recommended for further research in ADS planning field, such as planning with multiple micro-grids (MGs), collaborative planning between ADSs and information communication system (ICS), and planning from different perspectives of multi-stakeholders.

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“…Locations and sizes of new substations [26,29,30,32,36,38,54,55,58,66,80,85,89] Sizes of existing substations for reinforcement [24,26,27,29,32,34,36,38 …”

Section: Traditional Variablesmentioning

confidence: 99%

“…·Maximization of system reliability [28], [29], [38], [62], [84], [85], [101], [106]... ·Improvement of voltage profile (flicker, voltage violations, etc.) [37], [39], [50], [91], [100], [102], [104], [107]...…”

Section: Objectives Of Ads Planning Modelmentioning

confidence: 99%

A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches

Wang

Chen³

et al. 2017

Energies

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“…Equation (5) ensures that new and existing substations do not exceed their power injection capacity limits. Equation (6) corresponds to the condition of radial operation system which operates in conjunction with (2). Equations (7) and (8) define the binary characteristic of the decision variables, and finally, equations (9) and (10) correspond to the factors for calculating the power losses during the study period and the annualization factor of costs, respectively.…”

Section: Formulation Of Dsppmentioning

confidence: 99%

“…In the same year, a multi-objective particle swarm optimization algorithm (PSO) with two stages to solve the DSPP is developed [6]. The First stage defines the system topology, i.e., substations, lines with their wire gauges, and the candidate points to locate sectionalizers.…”

Section: Introductionmentioning

confidence: 99%

A new approach to solve the distribution system planning problem considering automatic reclosers

et al. 2017

Ingeniare. Rev. chil. ing.

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This article describes two new methodologies for optimal distribution system planning considering automatic reclosers to improve reliability indices. The first methodology proposed in this paper employs a two-stage cascade strategy to solve the problem. In the first stage a mono-objective Tabu Search (TS) algorithm is used to find the optimal distribution system topology. The installation cost of new elements, increasing capacity on existing elements and operational costs associated with technical losses are considered. In the second stage a Non-Dominated Sorting Genetic Algorithm known as NSGA II is employed, considering the optimal distribution system topology found by the first stage, and thus, solving the problem of optimal location of automatic reclosers in distribution systems. The non-supplied energy level of the network and installation cost of reclosers are considered as objective functions; and the min-max criterion to select a point on the optimal Pareto front is used. In the second methodology, a master-slave based optimization algorithm is used to find the best network topology including the associated to automatic reclosers. Master algorithm is a TS algorithm which is responsible to direct the optimization process through solution space, whereby, for each neighbor generated, the slave algorithm NSGA II is applied and min-max criterion is used to determine a configuration of reclosers for actual network topology. The proposed methodologies are applied on three-phase version of IEEE 34 nodes test feeder, with high quality results.Keywords: Distribution systems, min-max criterion, multi-objective optimization, NSGA-II Algorithm, reclosers, reliability. RESUMEN

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“…Con respecto a las funciones objetivo consideradas se tienen: costos y confiabilidad (Ramírez y Bernal, 2001); costos, confiabilidad y riesgo de inversión (Ramírez y Domínguez, 2004); costos e índices de fallas del sistema (Carrano, Soarez, Takahashi, Saldanha y Neto, 2006); costos, pérdidas y caída de tensión (Mori y Yamada, 2007); costos y caída de tensión (Mantway y Al-Muhaini, 2008); costos, pérdidas e interrupción del servicio (Kong et ál., 2008); costos y consumo de energía (Kayu y Ooka, 2009); costos, confiabilidad, pérdidas y caída de tensión (Ganguly, Sahoo y Das, 2011); costos de inversión y costos de interrupción del servicio (Ganguly, Sahoo y Das, 2013). Para solucionar el problema se han considerado diversas técnicas multiobjetivo, entre las que se destacan: algoritmos evolutivos (Ramírez y Bernal, 2001;Carrano, Soarez, Takahashi, Saldanha y Neto, 2006;Mori y Yamada, 2007;Kong et ál., 2008;Kayu y Ooka, 2009); búsqueda tabú (Ramí-rez y Domínguez, 2006); cúmulo de partículas (Mantway y Al-Muhaini, 2008;Sahoo, Ganguly y Das, 2012).…”

Section: Introductionunclassified

Planeación óptima de sistemas de distribución considerando múltiples objetivos: costo de inversión, confiabilidad y pérdidas técnicas

Solanilla

Isaza

Rendón

2015

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En este artículo se propone una metodología para solucionar el problema del planeamiento multiobjetivo de sistemas de distribución de energía eléctrica, empleando un algoritmo elitista de ordenamiento no dominado (NSGA-II). Esta metodología considera cuatro modelos matemáticos, donde las funciones objetivo son costos fijos, costos variables, costos fijos y variables, y confiabilidad de la red; como conjunto de restricciones se tienen criterios técnicos y operativos. Al solucionar cada uno de estos modelos se identifican los elementos comunes, los cuales son fijados para la siguiente etapa del proceso; esto se repite hasta hallar una configuración final del sistema. De esta forma, en cada paso del algoritmo se generan especies de cortes, los cuales reducen el espacio de solución. La metodología es verificada con un sistema de distribución de la literatura especializaday se obtienen resultados que muestran la efectividad del método al encontrar un punto de equilibrio entre todos los objetivos considerados.

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Multi-objective planning of electrical distribution systems incorporating sectionalizing switches and tie-lines using particle swarm optimization

Cited by 84 publications

References 29 publications

A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches

A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches

A new approach to solve the distribution system planning problem considering automatic reclosers

Planeación óptima de sistemas de distribución considerando múltiples objetivos: costo de inversión, confiabilidad y pérdidas técnicas

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