GA based optimal location and size of the distributed generators in distribution system for different load conditions

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

In the recent past factors such as apprehensions over impacts of environmental aspects, distribution network improvement conditions, and other subsidised programs of the government have affected the distributed generators (DG) units count in commercial and domestic electrical power output. It is known that the optimal size and optimal placement of DG units may lead to low power losses, high voltage profiles. In real time scenario identifying an appropriate DG location and size is hard because of various system constraints. Therefore a method which can identify a optimum DG location and size is necessary. Using the method a power system with an acceptable reliability level and voltage profile can be designed. To serve this purpose in this paper a procedure/method which can calculate the optimum location for DG placement and appropriate DG size has been proposed. This method has been evaluated using a 14 bus distribution system. The optimization method has been designed using genetic algorithm (GA) and also for time varying loads.

Original languageEnglish
Title of host publication1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems, ICPEICES 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467385879
DOIs
Publication statusPublished - 13-02-2017
Event1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems, ICPEICES 2016 - Delhi, India
Duration: 04-07-201606-07-2016

Publication series

Name1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems, ICPEICES 2016

Conference

Conference1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems, ICPEICES 2016
Country/TerritoryIndia
CityDelhi
Period04-07-1606-07-16

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Control and Optimization
  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering

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