Demand-side management, a new development in smart grid technology, has enabled
communication between energy suppliers and consumers. Demand side energy …

Artificial intelligence techniques lead to data-driven energy services in distribution power
systems by extracting value from the data generated by the deployed metering and sensing …

Non-intrusive load monitoring (NILM) is the task of disaggregating the total power
consumption into its individual sub-components. Over the years, signal processing and …

Daily peak load forecasting is a challenging problem in the filed of electric power load
forecasting. Since the nonlinear and dynamic of influence factors and their sequential …

Non-intrusive load monitoring (NILM) is the main method used to monitor the energy
footprint of a residential building and disaggregate total electrical usage into appliance …

World population growth and increased energy demand are taking a heavy toll on the
environment. Aside from developed countries, the adverse effects are far more apparent in …

Achieving carbon neutrality is widely recognized as the key measure to mitigate climate
change. As the basis for achieving carbon neutrality, corporate carbon footprint (CCF) …

Many non-intrusive load monitoring (NILM) studies use high-frequency data to classify the
device's ON/OFF state. However, these approaches cannot be applied in real-world …

Time-series classification is utilized in a variety of applications leading to the development of
many data mining techniques for time-series analysis. Among the broad range of time-series …

Non-intrusive load monitoring (NILM) technology can identify the energy consumed by each
individual device from the aggregate electricity measurements, contributing to energy saving …