Home energy management system based on task classification and the resident’s requirements

Abstract In this paper, an approach for home energy management system is introduced that is based on task classification. The problem is to find the best task activation plan regarding the resident’s requirements and appliances constraints, considering time of use pricing. We show that to have a best task activation plan it is necessary to specify four specific values for each task. In this regard, a quadratic utility function is derived based on the law of diminishing marginal utility in microeconomic. With the parameters such as sensitivity index and monetary equivalent value, each task’s utility function can be configured in accordance to the resident’s personal preferences. In this model, the concept of tasks interaction are also taken into account, for the first time. The problem is transformed to a mixed integer nonlinear programming problem, so that the available commercial solvers can successfully solve it in an acceptable solving time. The outputs of numerical examples show that they are reasonable and can be considered as optimal or near optimal results. The results indicate that the less sensitive the resident is to changing his/her desire task parameters, the more profit he/she will get. It is also shown that by increasing the monetary equivalent value, the task activation is shifted toward the times that are more preferable or has more favorite environment conditions. These results as well as the acceptable solving times, show that the proposed approach can be a promising model for home energy management systems in the future smart homes.