The smart grid concept is introduced to accelerate the operational efficiency and enhance
the reliability and sustainability of power supply by operating in self-control mode to find and …

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 …

Forecasting electricity demand requires accurate and sustainable data acquisition systems
which rely on smart grid systems. To predict the demand expected by the grid, many smart …

在“双碳” 目标的驱动下, 构建以新能源为主体的新型电力系统是促进现代电力系统低碳转型发展
的重要前提与必然趋势. 由于复杂易变的多元负荷是新型电力系统的重要组成部分 …

Load forecasting is a pivotal part of the power utility companies. To provide load-shedding
free and uninterrupted power to the consumer, decision-makers in the utility sector must …

The increased digitalisation and monitoring of the energy system opens up numerous
opportunities to decarbonise the energy system. Applications on low voltage, local networks …

Traditionally, load forecasting models are trained offline and generate predictions online.
However, the pure batch learning approach fails to incorporate new load information …

This study aims to examine the dynamic connection among economic growth, CO2
emissions, energy consumption, and foreign direct investments (FDIs). The panel section …

The progress of ICT technologies, day-ahead forecast, home energy management systems,
implementation of smart meters, and Distributed Energy Sources (DER) enables new …

Short-term load forecasting (STLF) enables distribution system operators to perform efficient
energy management by flexibly engaging energy consumers under the intelligent demand …