Optimal volt/var control of distribution system using MOPSO

M, Ramesh Babu; Kumar, Chanchal; Sreekanth, R. S.

doi:10.11591/ijeecs.v16.i3.pp1088-1095

Cited by 2 publications

(1 citation statement)

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“…IoT and cloud computing can be used to develop an efficient communication system [34]. Increased penetration of electric vehicles in the conventional system has given rise to the need of optimal voltage control of the distribution system and efficient power management of an electric vehicle [35], [36]. However, the approach towards developing a load management system based on regional classification of loads is yet to be taken.…”

Section: Introductionmentioning

confidence: 99%

Development of regional load management system based on rural, semi urban and urban loads-a critical analysis

Ganguly

Sil

2022

Bulletin EEI

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The sharp rise in population during the last half century has created immense pressure on the resources required for generation of energy essential to lead a comfortable and healthy lifestyle. The drive towards 100% electrification in developing countries like India has also contributed to this increase in demand. Till recently, fossil fuel was use to supply the bulk of this power. Now, the world is moving more and more towards renewable energy. This paper presents a model where several regions are combined together based on the demand profile of the regions segregated as urban, semi urban and rural along with the flexibility to schedule loads on the basis of availability of renewable energy sources within the area of the regions. The main focus is on detailed neural-networking based load forecasting and developing a load management system to manage load based on availability of distributed generation capacity and available tariff system. A solution is proposed in this paper based on a new approach to answer load management on the basis of region, population demographics and per capita energy consumption. A considerable amount of improvement to manage demand is intended to be attained and has been demonstrated in this research work.

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Section: Introductionmentioning

confidence: 99%