Stochastic residential energy resource scheduling by multi-objective natural aggregation algorithm

This paper studies the coordinated scheduling of residential energy resources in a smart home environment. The particularity of this paper is to consider the uncertainties of the must-run appliance load demand forecast errors and to addresses the residential energy resource scheduling through a multi-objective optimization approach. Multiple 1-day must-run appliance power demand scenarios are firstly generated from the house's historical energy consumption data. Based on this, a stochastic day-ahead appliance scheduling model is formulated, aiming to minimize the 1-day energy costs while maximizing the preference of the homeowner simultaneously. A new multi-objective optimization tool, i.e. Multi-Objective Natural Aggregation Algorithm (MONAA), is proposed to solve the stochastic day-ahead appliance scheduling model. Simulations are designed for the validation of the proposed method.