Transactive data-driven and consumer-centric home energy management system for local energy communities in Portugal
Farideh Ghanavati, Gerardo J. Osório, Jo�ão Matias, João P. S. Catalào
Abstract
This work investigates the performance of self-scheduling of smart homes (SHs) in the local energy community (LEC). The developed model is based on a computationally efficient model for energy analysis and practical tariff selection strategies for Portuguese residential clients, consisting of a straightforward and efficient home energy management system (HEMS), considering energy trading within the LEC. The HEMS model is based on a mixed-integer linear programming (MILP) optimization problem with the capability of self-scheduling of home appliances, electric vehicle (EV) charging at home, and local generation by photovoltaic (PV) panels. SHs are active prosumers aiming to reduce energy consumption costs, while trading energy within the LEC in a regulated energy market. This strategy aims to evaluate the benefits of interactive and interdependent energy transactions at the LEC level, ensuring mutual economic advantages for both consumers and active prosumers. In addition, the adaptability and scalability of the proposed HEMS model across different LEC sizes and market rules, to ensure its applicability to various energy management strategies and flexibility procurement have been identified. The LEC is composed of 50 residential end-users in Portugal and has been chosen to validate the model’s performance. Among these SHs, 15 end-users own EVs, and 15 PV systems significantly contribute to power consumption and generation, respectively. Several time-of-use (TOU) energy tariffs have been considered, and the economic cost reduction performance has been investigated through different scenarios, including self-scheduling and active energy trading within the LEC. The overall energy cost was reduced by almost 37.52% by considering the energy-sharing capability at the LEC.