.png){kind=icon}
.png){kind=icon}
Return
Wind speed modeling using a vector autoregressive process with a time-dependent intercept term
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ijepes.2015.11.027.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The effect of wind power on the electric power system is becoming increasingly important as more wind power is installed. This paper presents a Vector-Autoregressive-To-Anything (VARTA) process with a time-dependent intercept to model wind speeds in multiple locations. The model considers both temporal and spatial dependency structures in detail. It can be used in Monte Carlo simulations to assess the risk of very high or low wind speeds occurring in multiple locations at the same time and during consecutive hours. The long term simulation and short term forecasting results are assessed using measurements from 21 locations in Finland. A discussion on the applicability of the presented wind speed simulation method for the risk assessment of power systems is given. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords:
Forecasting
Generalized Pareto distribution
Monte Carlo simulation
Rank correlation
Vector autoregressive model
Wind speed
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
I
IF:
5
Papers:
1.1W
Citations:
3.1W