Electrical engineering

Physics

Meteorology

Energy (signal processing)

Wind power forecasting

Mathematics

Term (time)

Statistics

Engineering

Philosophy

Artificial intelligence

Wind speed

Power (physics)

Arbitrariness

Computer science

Linguistics

Quantum mechanics

Wind power

Real-time computing

Electric power system

Artificial neural network

Energy Reports

So as to decrease those cacoethic impact of a huge amount of wind energy generation systems associated with the electric power system and improve the utilization rate and the budgetary profits of wind power era, this paper raises a neural network in view of CEEMDAN-LSTM-TCN. Firstly, CEEMDAN is used to break down the wind velocity arrangement to decrease the sway of arbitrariness Furthermore variance about wind velocity. Secondly, the ultra-short-term wind power forecast depend upon LSTM and TCN is built to realize the real-time prediction for wind energy. Finally, the simulation results show that LSTM-TCN can deal with multi time order characteristics and predict ultra-short period wind energy with effect, which is better than LSTM and TCN. It also has a scientific reference for local power dispatching.

Prediction of ultra-short-term wind power based on CEEMDAN-LSTM-TCN