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

Sahar Rahim, Nadeem Javaid, Ashfaq Ahmad, Shahid Ahmed Khan, Zahoor AliKhan, Nabil Alrajeh, Umar Qasim

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Pages (from-to)452-470
JournalEnergy and Buildings
Volume129
Early online date11 Aug 2016
DOIs
Publication statusPublished - 1 Oct 2016

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