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

Aggregates; Energy management; Forecasting; Learning algorithms; Optimization; Particle swarm optimization (PSO); Weather forecasting; Backtracking search algorithms; Distribution generation; Intelligent decisions; Micro grid; Optimization techniques; Particle swarm optimization algorithm; Virtual p...

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Main Authors: Abdolrasol M.G.M., Mohamed A., Hannan M.A.
Other Authors: 35796848700
Format: Article
Published: Engineering and Scientific Research Groups 2023
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spelling my.uniten.dspace-232182023-05-29T14:38:31Z Virtual power plant and microgrids controller for energy management based on optimization techniques Abdolrasol M.G.M. Mohamed A. Hannan M.A. 35796848700 57195440511 7103014445 Aggregates; Energy management; Forecasting; Learning algorithms; Optimization; Particle swarm optimization (PSO); Weather forecasting; Backtracking search algorithms; Distribution generation; Intelligent decisions; Micro grid; Optimization techniques; Particle swarm optimization algorithm; Virtual power plants; Virtual power plants (VPP); Energy management systems 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. Final 2023-05-29T06:38:31Z 2023-05-29T06:38:31Z 2017 Article 2-s2.0-85020073428 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020073428&partnerID=40&md5=48d2e644d37d20451ccca07a7ae74994 https://irepository.uniten.edu.my/handle/123456789/23218 13 2 285 294 Engineering and Scientific Research Groups Scopus
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/
description Aggregates; Energy management; Forecasting; Learning algorithms; Optimization; Particle swarm optimization (PSO); Weather forecasting; Backtracking search algorithms; Distribution generation; Intelligent decisions; Micro grid; Optimization techniques; Particle swarm optimization algorithm; Virtual power plants; Virtual power plants (VPP); Energy management systems
author2 35796848700
author_facet 35796848700
Abdolrasol M.G.M.
Mohamed A.
Hannan M.A.
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_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
publisher Engineering and Scientific Research Groups
publishDate 2023
_version_ 1806427807255887872
score 13.222552

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