Offshore wind power is one of the fastest-growing energy sources worldwide, which is
environmentally friendly and economically competitive. Short-term time series wind speed …

Wind power has become one of the essential solutions to renewable energy and
sustainable development problems. The accuracy of wind speed forecasts primarily …

Deep recurrent neural networks, such as gated recurrent units and long short-term
memories, have been widely applied in wind speed forecasting. However, the simulations of …

Due to the intermittent, fluctuating and random characteristics of wind system, the output of
wind power will become unstable with the change of wind, which brings severe challenges …

Accurate and reliable probabilistic wind power and wind speed forecasts provide large
amounts of uncertainty information, which is important for wind farm management and grid …

To achieve a high penetration of renewable energy integration, an effective solution is to
explore the interdependence between numerical weather prediction (NWP) data and …

We briefly review the main developments of Bayesian dynamic models. The emphasis is on
marketing applications. Typical examples in this area are discussed. The concepts of …

Wind energy, as a kind of environmentally friendly renewable energy, has attracted a lot of
attention in recent decades. However, the security and stability of the power system is …

The fluctuation of wind speed brings difficulty for wind energy utilization. Wind speed
forecasting can improve safety of wind power integration. To better forecast fluctuating wind …

We present a methodology to identify multiple pollutant sources in the atmosphere that
combines a data-driven dispersion model with Bayesian inference and uncertainty …