Load forecasting is vital for a reliable and sustainable smart grid as it is used to predict the demand and make price adjustment accordingly. Electric consumption data which is …
F Zhang, Q Yang, D An - IEEE/CAA Journal of Automatica …, 2023 - ieeexplore.ieee.org
The smart grid utilizes the demand side management technology to motivate energy users towards cutting demand during peak power consumption periods, which greatly improves …
In the smart home, vast amounts of data are being collected via various interconnected devices. Although this assists in improving the quality of life at home, often the user is not …
M Aghvamipanah, M Amini, C Artho… - 2024 IEEE 9th …, 2024 - ieeexplore.ieee.org
Smart home devices collect and transmit user data to smart home Trigger Action Platforms (TAPs) for processing and executing automation rules. However, this data can also be used …
Abstract Industrial IoT (IIoT) era is evolving rapidly in parallel to the progress in Industry 4.0, which leads factories to increase the engagement with external parties through different …
PV Sindhwad, P Ranka, S Muni, F Kazi - International Journal of …, 2024 - Springer
In today's swiftly evolving digital environment, the security and dependability of software applications are crucial. In light of industries' increasing reliance on software, identifying and …
F Wu, X Wang, M Yang, H Zhang… - 2022 13th Asian …, 2022 - ieeexplore.ieee.org
Over the past decade, smart grids have been widely implemented. Real-time pricing can better address demand-side management in smart grids. Real-time pricing requires …
The rising demand for efficient power distribution and management has brought enormous opportunities for researchers. It has resulted in moving from the traditional grid system to the …