Reliability based optimum location of distributed generation

Banerjee, Binayak; Islam, Syed

doi:10.1016/j.ijepes.2011.06.029

Cited by 79 publications

(39 citation statements)

References 14 publications

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“…This efficiency is in line with the average efficiency of power plants reported by Connolly et al [4]. The introduction of decentralised electricity generation using renewable energy systems could mitigate some of the losses by producing electrical energy in close proximity to consumer demand [24] while also reducing the overall environmental impact of generation [25].…”

Section: Renewable Energy Resources In Irelandsupporting

confidence: 83%

Regional integration of renewable energy systems in Ireland – The role of hybrid energy systems for small communities

Goodbody

Walsh

McDonnell

et al. 2013

International Journal of Electrical Power & Energy Systems

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Due to a lack of indigenous fossil energy resources, Ireland's energy supply constantly teeters on the brink of political, geopolitical, and geographical unease. The potential risk to the security of the energy supply combined with the contribution of anthropogenic greenhouse gas emissions to climate change gives a clear indication of Ireland's need to reduce dependency on imported fossil fuels as primary energy source. A feasibility analysis to investigate the available renewable energy options was conducted using HOMER software. The Net Present Cost, the Cost of Energy, and the CO 2 emissions of each potential energy combination were considered in determining the most suitable renewable and non-renewable hybrid energy system. Wind energy was shown to have the greatest potential for renewable energy generation in Ireland:wind energy was a component of the majority of the optimal hybrid systems both in standalone and grid-connected systems. In 2010 the contribution of wind energy to gross electricity consumption in Ireland approximated 10%, and the results of this feasibility study indicate that there is great potential for wind-generated energy production in Ireland. Due to the inherent variability of wind energy the grid-connected system results are particularly relevant, which show that in more than half of the analyses investigating electrical energy demand the incorporation of wind energy offset the CO 2 emissions of the non-renewable elements to such a degree that the whole system had negative CO 2 emissions, which has serious implications for Kyoto Protocol emissions limits. Ireland also has significant potential for hydropower generation despite only accounting for 2% of the gross electricity consumption in 2010. Wind and hydroenergy should therefore be thoroughly explored to secure an indigenous primary energy source in Ireland.

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Section: Renewable Energy Resources In Irelandsupporting

confidence: 83%

Regional integration of renewable energy systems in Ireland – The role of hybrid energy systems for small communities

Goodbody

Walsh

McDonnell

et al. 2013

International Journal of Electrical Power & Energy Systems

View full text Add to dashboard Cite

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“…642 location of distributed generators with objectives like minimum power loss [9], [10], minimum cost [11], maximum DG penetration [12], maximum reliability [13] and maximum voltage stability index [14]. A multi-objective performance index [15] for distribution networks with time varying distributed generation is proposed.…”

Section: Optimal Siting Of Dg In a Distribution Network Using Artificmentioning

confidence: 99%

Optimal Siting of Distributed Generators in a Distribution Network using Artificial Immune System

Meera¹,

Hemamalini²

2017

IJECE

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Distributed generation (DG) sources are being installed in distribution networks worldwide due to their numerous advantages over the conventional sources which include operational and economical benefits. Random placement of DG sources in a distribution network will result in adverse effects such as increased power loss, loss of voltage stability and reliability, increase in operational costs, power quality issues etc. This paper presents a methodology to obtain the optimal location for the placement of multiple DG sources in a distribution network from a technical perspective. Optimal location is obtained by evaluating a global multi-objective technical index (MOTI) using a weighted sum method. Clonal selection based artificial immune system (AIS) is used along with optimal power flow (OPF) technique to obtain the solution. The proposed method is executed on a standard IEEE-33 bus radial distribution system. The results justify the choice of AIS and the use of MOTI in optimal siting of DG sources which improves the distribution system efficiency to a great extent in terms of reduced real and reactive power losses, improved voltage profile and voltage stability. Solutions obtained using AIS are compared with Genetic algorithm (GA) and Particle Swarm optimization (PSO) solutions for the same objective function.

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“…En este contexto, existen diferentes metodologías reportadas en la literatura técnica especializada que buscan encontrar la mejor ubicación de GD en las redes de energía eléctrica. Estas metodologías incluyen métodos analíticos (Khan y Choudhry, 2010), (Hung, 2010) heurísticas (Hemdan y Kurrat, 2011;Ouyang et al, 2011) metaheurísticas (López-Lezama et al 2012Kang et al 2012;Biswas et al 2012) y métodos basados en programación matemática (Khalesi et al 2011;Banerjee y Islam 2011).…”

Section: Introductionunclassified

Ubicación de Generación Distribuida para Minimización de Pérdidas Usando un Algoritmo Genético Híbrido

Narváez¹,

López-Lezama

Velilla

2015

Inf. tecnol.

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ResumenEn 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. Palabras clave: algoritmos genéticos, generación distribuida, redes neuronales artificiales Location of Distributed Generation for Power Losses Reduction using a Hybrid Genetic Algorithm AbstractThis 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.

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Reliability based optimum location of distributed generation

Cited by 79 publications

References 14 publications

Regional integration of renewable energy systems in Ireland – The role of hybrid energy systems for small communities

Regional integration of renewable energy systems in Ireland – The role of hybrid energy systems for small communities

Optimal Siting of Distributed Generators in a Distribution Network using Artificial Immune System

Ubicación de Generación Distribuida para Minimización de Pérdidas Usando un Algoritmo Genético Híbrido

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