Proactive home energy storage management system to severe weather scenarios

• Published in: Applied energy 2020-12, Vol.279, p.115797, Article 115797
• Main Authors: Schmitz, William Ismael, Schmitz, Magdiel, Canha, Luciane Neves, Garcia, Vinícius Jacques
• Format: Article
• Language: English
• Subjects: Energy storage system; Home energy storage management system; Home’s resilience; Severe weather events
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2020.115797

In dynamic energy markets with real-time tariffs, residential power management systems must identify optimal solutions for the energy stored and transacted with the power grid. On the other hand, in the event of severe weather events that lead to a power outage, this stored energy can also be used to supply this customer during the event. However, the arbitrage can lead to a situation of low state of charge at this moment, in which the priority for the customer is the uninterrupted power supply, instead of the profit. Thus, this paper proposes a novel mathematical model incorporating this characteristic into a Home Energy Storage Management System (HESMS) decision-making process, thereby enhancing the home’s resilience in the face of severe weather events. The model automatically decides in advance when to start the energy storage system (ESS) recharging, formulating the operational condition of the local distribution network and estimating the probability of a power outage associated with the incidence of strong winds, monitoring the meteorological parameters and state of charge of the local ESS. Case studies with real weather and power outages data demonstrate the effectiveness of the proposed method. Results show that the HESMS contributes to increasing the home’s electric resilience, with little interference in the standard operation of the ESS. •A mathematical model is presented for the ESS charging decision-making process.•Anticipation of power outages due to severe weather, ensuring reserve energy.•Continuous modeling of the current local distribution network operational status.•Estimation of residential power outage probability due to high speed winds.