Gomes, I.L.R.Ruano, MariaRuano, Antonio2023-09-142023-09-142023-02http://hdl.handle.net/10400.1/19988This paper addresses the development of an innovative home energy management system (HEMS). The presented HEMS relies on a mixed-integer linear programming (MILP)-based model predictive control. The system takes advantage of the powerful formulation capabilities of a MILP-based mathematical pro-gramming problem with the capabilities of model predictive control to optimize, at each sample instant the HEMS operation using a receding-horizon formulation. The system is designed for a residence located in Algarve, Portugal. The results of the presented system are compared with the real experimental results obtained by a commercial PV-battery management system. Additionally, an analysis of the system???s per-formance is conducted, in terms of operation planning for 2021 market prices compared to 2022 prices, where there was a significant rise of buying price due to the energy world context. In all simulations per-formed, it is verified that the MILP-based model predictive control presents better results, with statistical relevance. CO 2023 Elsevier B.V. All rights reserved.engHome energy management systemHEMSModel predictive controlMixed-integer linear programmingEnergy storageRenewable energyDemand responsejournal article10.1016/j.enbuild.2023.1127741872-6178