The growing success of smart grids (SGs) is driving increased interest in load forecasting
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …

The balance between supplied and demanded power is a crucial issue in the economic
dispatching of electricity energy. With the emergence of renewable sources and data-driven …

The spatial–temporal distribution of electric vehicle (EV) charging load has strong
randomness and is affected by battery capacity and user behavior. In addition, the multinode …

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 …

In this paper a dynamic Artificial Neural Network (ANN) model called Meta-ANN is
developed for forecasting the short-term grid load. The primary ingredient of the model is a …

Spinning reserve without accurate load forecasting can lead to automatic disconnection of
critical loads by under-frequency load shedding devices. Such a predicament poses a grave …

The clean and low-carbon transition of China's power sector is of great importance to the
achievement of dual carbon targets and the control of global warming. This paper first …

Probabilistic wind power forecasting is an important input in the decision-making process in
future electric power grids with large penetrations of renewable generation. Traditional …

Artificial intelligence (AI) as a multi-purpose technology is gaining increased attention and is
now widely used across all sectors of the economy. The growing complexity of planning and …

Probabilistic multi-energy load forecasting in an integrated energy system is very complex,
because it needs to consider the following three aspects simultaneously: 1) Complex …