The prediction of wind power output is part of the basic work of power grid dispatching and
energy distribution. At present, the output power prediction is mainly obtained by fitting and …

Reliable and accurate ultra-short-term prediction of wind power is vital for the operation and
optimization of power systems. However, the volatility and intermittence of wind power pose …

The widespread penetration of advanced metering infrastructure brings an opportunity to
detect electricity theft by analyzing the electricity consumption data collected from smart …

A novel Wasserstein generative adversarial network (WGAN) is proposed for stochastic wind
power output scenario generation. Wasserstein distance with gradient penalty adapts to the …

Accurate and reliable prediction of power load is critical to ensure the economy and stability
of power systems. However, deterministic point prediction can scarcely be accurate due to …

Determining the operation scenarios of renewable energies is important for power system
dispatching. This paper proposes a renewable scenario generation method based on the …

Specific emitter identification (SEI) is a technology that identifies different emitters through
their unique characteristics. Research on traditional specific emitter identification systems …

Short-term residential load forecasting is essential to demand side response. However, the
frequent spikes in the load and the volatile daily load patterns make it difficult to accurately …

We investigate sequential time series data through ensemble learning. Conventional
ensemble algorithms and the recently introduced ones have provided significant …

Many real-world scenarios require accurate predictions of time series, especially in the case
of long sequence time-series forecasting (LSTF), such as predicting traffic flow and electricity …