Virtual power plant and microgrids controller for energy management based on optimization techniques

This paper discuss virtual power plant (VPP) and Microgrid controller for energy management system (EMS) based on optimization techniques by using two optimization techniques namely Backtracking search algorithm (BSA) and particle swarm optimization algorithm (PSO). The research proposes use of mult...

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Main Authors: Abdolrasol, M.G.M., Mohamed, A., Hannan, M.A.
Format: Article
Language:English
Published: 2018
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spelling my.uniten.dspace-113412018-12-14T04:09:32Z Virtual power plant and microgrids controller for energy management based on optimization techniques Abdolrasol, M.G.M. Mohamed, A. Hannan, M.A. This paper discuss virtual power plant (VPP) and Microgrid controller for energy management system (EMS) based on optimization techniques by using two optimization techniques namely Backtracking search algorithm (BSA) and particle swarm optimization algorithm (PSO). The research proposes use of multi Microgrid in the distribution networks to aggregate the power form distribution generation and form it into single Microgrid and let these Microgrid deal directly with the central organizer called virtual power plant. VPP duties are price forecast, demand forecast, weather forecast, production forecast, shedding loads, make intelligent decision and for aggregate & optimizes the data. This huge system has been tested and simulated by using Matlab simulink. These paper shows optimizations of two methods were really significant in the results. But BSA is better than PSO to search for better parameters which could make more power saving as in the results and the discussion. © JES 2017. 2018-12-14T02:42:51Z 2018-12-14T02:42:51Z 2017 Article en
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
description This paper discuss virtual power plant (VPP) and Microgrid controller for energy management system (EMS) based on optimization techniques by using two optimization techniques namely Backtracking search algorithm (BSA) and particle swarm optimization algorithm (PSO). The research proposes use of multi Microgrid in the distribution networks to aggregate the power form distribution generation and form it into single Microgrid and let these Microgrid deal directly with the central organizer called virtual power plant. VPP duties are price forecast, demand forecast, weather forecast, production forecast, shedding loads, make intelligent decision and for aggregate & optimizes the data. This huge system has been tested and simulated by using Matlab simulink. These paper shows optimizations of two methods were really significant in the results. But BSA is better than PSO to search for better parameters which could make more power saving as in the results and the discussion. © JES 2017.
format Article
author Abdolrasol, M.G.M.
Mohamed, A.
Hannan, M.A.
spellingShingle Abdolrasol, M.G.M.
Mohamed, A.
Hannan, M.A.
Virtual power plant and microgrids controller for energy management based on optimization techniques
author_facet Abdolrasol, M.G.M.
Mohamed, A.
Hannan, M.A.
author_sort Abdolrasol, M.G.M.
title Virtual power plant and microgrids controller for energy management based on optimization techniques
title_short Virtual power plant and microgrids controller for energy management based on optimization techniques
title_full Virtual power plant and microgrids controller for energy management based on optimization techniques
title_fullStr Virtual power plant and microgrids controller for energy management based on optimization techniques
title_full_unstemmed Virtual power plant and microgrids controller for energy management based on optimization techniques
title_sort virtual power plant and microgrids controller for energy management based on optimization techniques
publishDate 2018
_version_ 1644495182496792576
score 13.160551