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A STARMA Model for Wind Power Space-Time Series
- Source :
- 2018 IEEE Power & Energy Society General Meeting (PESGM).
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- This paper had analyzed and modeled the wind power characteristic from the perspective of space-time series. Firstly, measured data of wind power had been analyzed for the coupled spatial-temporal correlation. Then, a spatial relation matrix, which was used to describe the location of wind farms, had been embedded into the Space-Time Auto Regressive Moving Average (STARMA) model in order to reflect the spatial-temporal correlation of multi-dimensional wind power series. Simulation results showed that this model has restored not only temporal autocorrelation, but also time shifting characteristic of spatial correlation of the original wind power series, which essentially reflected the coupled spatial-temporal characteristic of real wind power series. This model can be used to produce huge amount of simulated wind power data, which have same characteristics with real wind power data, and can provide basics for the planning and operation of wind power integration systems.
- Subjects :
- Spatial correlation
Wind power
Meteorology
Series (mathematics)
business.industry
Astrophysics::High Energy Astrophysical Phenomena
020209 energy
Space time
Autocorrelation
02 engineering and technology
Data modeling
Autoregressive model
Moving average
Physics::Space Physics
0202 electrical engineering, electronic engineering, information engineering
Environmental science
business
Physics::Atmospheric and Oceanic Physics
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2018 IEEE Power & Energy Society General Meeting (PESGM)
- Accession number :
- edsair.doi...........a0d7193d427105a6f78aa458763e1c01
- Full Text :
- https://doi.org/10.1109/pesgm.2018.8585919