Multi-objective home appliance scheduling with implicit and interactive user satisfaction modelling

Trinadh Pamulapati, Rammohan Mallipeddi and Minho Lee

Applied Energy, 2020, vol. 267, issue C, No S0306261920302026

Abstract: Residential consumers desire to minimize electricity bills while maximizing comfort by appropriate appliance scheduling. The conflicting nature of the objectives facilitates a multi-objective formulation that can provide a set of trade-off schedules enabling better decision making. In literature, user preference or comfort regarding each device at each time instance is obtained explicitly. In addition, scheduling interval of 1-hour is considered because reducing scheduling interval to 1 or 5 min drastically increases – (1) the dimensionality of search space and complicates the search process, and (2) the number of time instances for which the user has to explicitly provide the preference resulting in human fatigue. However, it is essential to schedule the devices at lower scheduling intervals to precisely-estimate the electricity consumption due to the presence of high power devices such as microwave that operate for shorter intervals (<5 min). In this work, we employ an efficient and scalable multi-objective evolutionary algorithm to solve the scheduling problem. In addition, the user preference is implicitly estimated from the past usage patterns obtained using energy disaggregation. And, if the estimated user preference deviates from the user expectation then the user can modify preference using weights referred to as priority weights. The novel implicit user satisfaction modeling and interactive customization through priority weights makes the proposed work a standalone approach suitable for any user. Experimental results and analysis for various user priorities and scheduling intervals (ranging from 1-minute to 1-hour) proves that the proposed framework is able to provide generalized schedules.

Keywords: Multi-objective scheduling; Home appliance scheduling; Electricity cost minimization; Implicit user satisfaction estimation; Interactive scheduling; Energy disaggregation (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (10)

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DOI: 10.1016/j.apenergy.2020.114690

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