Authors: Rasool Bukhsh; Nadeem Javaid; Majid Iqbal Khan; Zahoor Ali Khan; Imran Usman
Addresses: Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan ' Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan ' Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan ' Computer Information Science, Higher Colleges of Technology, Fujairah, UAE ' College of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia
Abstract: In smart grid, the minimum cost for power consumption is attained by scheduling the appliances load. Shifting the appliances load from on-peak to off-peak time reduces the cost in user's bill without compromising the load demand. In this paper, four scheduling algorithms are proposed by hybridising elephant herding optimisation (EHO) with genetic, firefly, bacterial foraging and binary particle swarm optimisation algorithms. Extensive simulations are performed to schedule the home appliances using proposed algorithms with three pricing tariffs: day ahead real-time pricing, inclined block rates and critical peak pricing. The cost efficiency of optimised power consumption is analysed. Results show that more cost is reduced with proposed hybrid algorithms as compared to the unscheduled and state-of-the-art algorithms.
Keywords: smart metre; smart home; SH; operation time interval; OTI; cost efficiency; appliances schedule.
International Journal of Ad Hoc and Ubiquitous Computing, 2020 Vol.33 No.2, pp.90 - 108
Received: 31 Jul 2018
Accepted: 30 Nov 2018
Published online: 02 Mar 2020 *