2016 6th International Conference on Intelligent and Advanced Systems (ICIAS) 2016
DOI: 10.1109/icias.2016.7824086
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An analytical approach for the sizing and siting of battery-sourced inverters in distribution networks

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Cited by 7 publications
(8 citation statements)
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“…technical, economic, and environmental (in case of renewables). Power loss minimisation, voltage regulation, improvement in system reliability and loadability, improved power quality, relieved transmission and distribution networks, and increased overall energy efficiency are among the major technical benefits of DGs [2]. Economic benefits of DGs includes saving world fuel, saving transmission, and distribution costs, and reducing wholesale electricity prices.…”
Section: Background and Motivationmentioning
confidence: 99%
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“…technical, economic, and environmental (in case of renewables). Power loss minimisation, voltage regulation, improvement in system reliability and loadability, improved power quality, relieved transmission and distribution networks, and increased overall energy efficiency are among the major technical benefits of DGs [2]. Economic benefits of DGs includes saving world fuel, saving transmission, and distribution costs, and reducing wholesale electricity prices.…”
Section: Background and Motivationmentioning
confidence: 99%
“…The objectives of the existing work on DG placement can be categorised as minimisation of power loss [1,2,[11][12][13][14][15][16][17], enhancement of voltage profile [1,2,[11][12][13][14][15][16][17], enhancement of system stability [18,19], improvement of loading margin [20], profit maximisation, and reduction of harmful emissions [21][22][23][24]. Both single objective [1,2,11,13,14,16,25] and multi-objective [20][21][22]26] functions have been used for optimal placement of DGs by different researchers. The popular methods used by different researchers for optimal siting and sizing of DGs are analytical approaches [2], mixed-integer non-linear programming [19], particle swarm optimisation (PSO) [13,14,16,17], genetic algorithms (GAs) [15,20,21], sensitivity analysis…”
Section: Literature Reviewmentioning
confidence: 99%
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