Maheesha Dhashantha Silva*, Qi Liu
CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2971-2989, 2024, DOI:10.32604/cmc.2024.051289
Abstract In recent years, Non-Intrusive Load Monitoring (NILM) has become an emerging approach that provides affordable energy management solutions using aggregated load obtained from a single smart meter in the power grid. Furthermore, by integrating Machine Learning (ML), NILM can efficiently use electrical energy and offer less of a burden for the energy monitoring process. However, conducted research works have limitations for real-time implementation due to the practical issues. This paper aims to identify the contribution of ML approaches to developing a reliable Energy Management (EM) solution with NILM. Firstly, phases of the NILM are discussed,… More >
Login
Register
