id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-2490	Xu, Shiwei	Coastal Wind Power Forecasting Research Scheme Design	2022	6	.pdf	application/pdf	4896	206	46	However, LSTM still has the following shortcomings in wind power prediction: (i) hidden features in the data are more important than usual during extreme weather or large power fluctuations, but LSTM cannot identify the differences of these high-dimensional features; (ii) in the face of multi- dimensional long series of wind power data, there are problems such as easy to ignore the sequence structure information and difficult to solve the long-time dependence. Firstly, wind power forecasting provides a basis for coastal wind farms to make operation plans and grid dispatching departments to adjust dispatching plans, thus alleviating the impact of wind power access on the grid and ensuring the efficient and stable operation of the power system.	cache/fcis-2490.pdf	txt/fcis-2490.txt