Atomic Scheduling of Appliance Energy Consumption in Residential Smart Grids

Kyeong Soo Kim, Sanghyuk Lee, Tiew On Ting and Xin-She Yang
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Kyeong Soo Kim: Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China
Sanghyuk Lee: Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam
Tiew On Ting: Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China
Xin-She Yang: School of Science and Technology, Middlesex University, London NW4 4BT, UK

Energies, 2019, vol. 12, issue 19, 1-18

Abstract: Most of the current formulations of the optimal scheduling of appliance energy consumption use the vectors of appliances’ scheduled energy consumption over equally divided time slots of a day as optimization variables, which does not take into account the atomicity of certain appliances’ operations, i.e., the non-interruptibility of appliances’ operations and the non-throttleability of the energy consumption patterns specific to their operations. In this paper, we provide a new formulation of atomic scheduling of energy consumption based on the optimal routing framework; the flow configurations of users over multiple paths between the common source and destination nodes of a ring network are used as optimization variables, which indicate the starting times of scheduled energy consumption, and optimal scheduling problems are now formulated in terms of the user flow configurations. Because the atomic optimal scheduling results in a Boolean-convex problem for a convex objective function, we propose a successive convex relaxation technique for efficient calculation of an approximate solution, where we iteratively drop fractional-valued elements and apply convex relaxation to the resulting problem until we find a feasible suboptimal solution. Numerical results for the cost and peak-to-average ratio minimization problems demonstrate that the successive convex relaxation technique can provide solutions close to and often identical to global optimal solutions.

Keywords: atomic scheduling; convex relaxation; demand-side management; energy consumption scheduling; optimal routing; smart grid (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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