Exploiting heuristic algorithms to efficiently utilize energy management controllers with renewable energy sources

Tools

Rahim, Sahar, Javaid, Nadeem, Ahmad, Ashfaq, Khan, Shahid Ahmed, AliKhan, Zahoor, Alrajeh, Nabil and Qasim, Umar (2016) Exploiting heuristic algorithms to efficiently utilize energy management controllers with renewable energy sources. Energy and Buildings, 129. pp. 452-470. ISSN 0378-7788

Full text not available from this repository.

Abstract

In this paper, we comparatively evaluate the performance of home energy management controller which is designed on the basis of heuristic algorithms; genetic algorithm (GA), binary particle swarm optimization (BPSO) and ant colony optimization (ACO). In this regard, we introduce a generic architecture for demand side management (DSM) which integrates residential area domain with smart area domain via wide area network. In addition, problem formulation is carried via multiple knapsack problem. For energy pricing, combined model of time of use tariff and inclined block rates is used. Simulation results show that all designed models for energy management act significantly to achieve our objections and proven as a cost-effective solution to increase sustainability of smart grid. GA based energy management controller performs more efficiently than BPSO based energy management controller and ACO based energy management controller in terms of electricity bill reduction, peak to average ratio minimization and user comfort level maximization.

Item Type:	Article
Uncontrolled Keywords:	sdg 7 - affordable and clean energy ,/dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy
Faculty \ School:	Faculty of Science > School of Computing Sciences
Related URLs:	http://dx.doi.org/10.1016/j.enbuild.2016...
Depositing User:	LivePure Connector
Date Deposited:	30 May 2022 10:30
Last Modified:	29 Sep 2023 10:30
URI:	https://ueaeprints.uea.ac.uk/id/eprint/85232
DOI:	10.1016/j.enbuild.2016.08.008

Actions (login required)

View Item