Time and device based priority induced comfort management in smart home within the consumer budget limitation

In demand side management (DSM), scheduling of appliances based on consumer-defined priorities is an important task performed by a home energy management controller (HEMC). This paper presents a DSM technique that is capable of controlling loads within a smart home considering time-varying appliances' priorities. An evolutionary accretive comfort algorithm (EACA) is developed based on four postulations that allow time-varying priorities to be quantified in time and device-based features. Based on the input data considering the appliances' power ratings, its time of use, and absolute comfort derived from priorities, the EACA is able to generate an optimal energy consumption pattern which would give maximum satisfaction at a predetermined user budget. A cost per unit comfort index (χ) which relates the consumer expenditure to the achievable comfort is also demonstrated. To test the applicability of the proposed EACA, three budget scenarios of $1.5/day, $2.0/day and $2.5/day are performed. The results of each of the scenarios using EACA are compared to five base cases in which the appliances are randomly used. The simulation results revealed that the proposed EACA obtained an optimal absolute comfort with reduced cost per unit comfort values for all three scenarios within the budget limits.