METHOD OF PREDICATING ULTRA-SHORT-TERM WIND POWER BASED ON SELF-LEARNING COMPOSITE DATA SOURCE
Number of patents in Portfolio can not be more than 2000
United States of America Patent
Stats
-
N/A
Issued Date -
Oct 22, 2015
app pub date -
Apr 9, 2015
filing date -
Apr 22, 2014
priority date (Note) -
Published
status (Latency Note)
Importance
Abstract
A method of predicating ultra-short-term wind power based on self-learning composite data source includes following steps. Model parameters of an autoregression moving average model are obtained by inputting data. A predication result is obtained by inputting data required by wind power predication into the autoregression moving average model. A post-evaluation is performed to the predication result by analyzing error between the predication result and measured values, and performing model order determination and model parameters estimation again while the error is greater than an allowable maximum error.
First Claim
Family
International Classification(s)
- [Classification Symbol]
- [Patents Count]
Cited Art Landscape
Patent Citation Ranking
Recipient Email Address
Recipient Email Address
Comment
Recipient Email Address
Add to Portfolio(s)
To add this patent to one, or more, of your portfolios, simply click the add button.
This Patent is in these Portfolios:
Add to additional portfolios:
Last Refreshed On:
Changes done successfully