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An Efficient Power Scheduling Scheme for Residential Load Management in Smart Homes

doi: 10.3390/app5041134
In this paper, we propose mathematical optimization models of household energy units to optimally control the major residential energy loads while preserving the user preferences. User comfort is modelled in a simple way, which considers appliance class, user preferences and weather conditions. The wind-driven optimization (WDO) algorithm with the objective function of comfort maximization along with minimum electricity cost is defined and implemented. On the other hand, for maximum electricity bill and peak reduction, min-max regret-based knapsack problem (K-WDO) algorithm is used. To validate the effectiveness of the proposed algorithms, extensive simulations are conducted for several scenarios. The simulations show that the proposed algorithms provide with the best optimal results with a fast convergence rate, as compared to the existing techniques.
- University of Alberta Canada
- Dalhousie University Canada
- Higher Colleges of Technology United Arab Emirates
- University of Alberta Libraries Canada
- COMSATS University Islamabad Pakistan
Technology, time of use pricing, swarm optimization, energy management, QH301-705.5, T, Physics, QC1-999, Engineering (General). Civil engineering (General), Chemistry, knapsack, demand response, TA1-2040, Biology (General), smart grid, QD1-999
Technology, time of use pricing, swarm optimization, energy management, QH301-705.5, T, Physics, QC1-999, Engineering (General). Civil engineering (General), Chemistry, knapsack, demand response, TA1-2040, Biology (General), smart grid, QD1-999
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).118 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
