Short-term wind power forecast (WPF) depends highly on the wind speed forecast (WSF),
which is the prime contributor to the forecasting error. To achieve more accurate WPF …

With a high proportion of renewable energy injected into the power grid, the accurate wind
power prediction of wind farms is key to improving power quality and ensuring the stable …

As a kind of green, clean and renewable energy, wind power generation has been widely
utilized in various countries in the world. With the rapid development of wind energy, it is …

As an efficient tool for uncertainty quantification of renewable energy forecasting, prediction
intervals (PIs) provide essential prognosis to power system operator. Merely improving the …

Due to the stochastic and non-stationary characteristics of wind speed, the wind power
generation is highly uncertain and fluctuating, which significantly challenges the operation of …

The seasonality and randomness of wind present a significant challenge to the operation of
modern power systems with high penetration of wind generation. An effective short-term …

In this paper, an innovative hybrid multi-variable generator's actual-output-power predicting
model is proposed based on ant colony optimization algorithm and extreme learning …

The proportion of wind energy in global energy structure is growing rapidly, promoting the
development of wind power forecasting (WPF) technologies to solve the uncertainty and …

In this paper, a sparse machine learning technique is applied to predict the next-hour wind
power. The hourly wind power prediction values within a few future hours can be obtained …

In the context of high photovoltaic (PV) penetration, high-quality solar power interval
prediction is important for grid system operation. However, in some cases, sufficient amount …