Minimizing the operation costs of a smart home using a HEMS with a MILP-based model predictive control approach

Abstract

The energy management of a home nowadays is a challenging task, since it is necessary to take into account not only technical aspects, but also information regarding the purchase and sale prices of energy, in order to obtain an operation with minimum cost. Thus, it is necessary to develop advanced energy management systems, the so-called home energy management systems (HEMS). This paper presents a new HEMS with a mixed-integer linear programming (MILP)-based model predictive control (MPC) approach. This approach allows to obtain better results than an approach purely using MILP, by having access to updated information at every moment. The results of a real case study in Algarve, Portugal, show the superiority of MILP-based MPC over MILP and over experimental results.