Smart home appliances scheduling considering user comfort level

Abstract

Smart home appliances scheduling, employing optimization optimization algorithms to reduce utility costs, is gaining traction under the introduction of time-of-use tariffs and the development of Internet of Things (IoT). The prior electricity cost reduction scheduling algorithms, however, causes substantial discomfort to users for restricting users from using the appliances at their desired times. To address the problem, a novel versatile systematic method is proposed by pricing the mismatch of proposed schedule with users' usage preference pattern to quantify discomfort, coupled with comfort-cost weight factor. The method employing customizable user preference patterns, user-perceived pricing of mismatch and user-specified comfort-savings weightage, not only captures the complex dependence of comfort to individual preference, but the evolution with time by continuous user survey. The proposed method, formulated to be simple enough to be applied on an Excel spreadsheet, demonstrates substantial reduction of electricity cost and users' discomfort simultaneously. Studies on the algorithm found it to be robust against of fluctuations of parameters, with optimization performance comparable to prior work. The work demonstrates that despite the complex nature of comfort to users' behaviors and perception, simple pricing surveys can be used to accurately quantify, compare and optimize users' comfort together with economic savings.