An Optimal Load Scheduling Approach Considering User Preference and Convenience Level for Smart Homes

Load scheduling remains an important role in home energy management systems (HEMS) in order to achieve maximum user satisfaction. With different load characteristics, home appliances need to be modeled accurately and efficiently to achieve the goals set by the homeowner. This paper introduces a new computationally efficient approach to model three different types of loads in HEMS, in which the goal is to simultaneously minimize electricity cost and maximize user convenience. A user convenience function is introduced to model the time an appliance is expected to run, according to the priority set by the user. To avoid the complexity and ambiguity in having two different objectives with different unit measurements, a weighted summation function with a normalization parameter is proposed in order to normalize the values between cost and convenience. Six home appliances which represent three different load characteristics are simulated in real time, where each appliance is assigned with a user preference parameter set as the weights to the objective function. Extensive simulations show that the proposed scheme is able to compensate between cost and convenience for different levels of preference parameters using a weighted summation optimization function.