Abstract
Wind power is one of the most widespread renewable resources, offering the benefits of no pollution and competitive cost when compared to conventional and other renewable sources. Since wind speed is highly stochastic, integrating wind power in the grid requires an accurate modeling and forecasting of wind speed and power. Including the seasonal trend of wind speed in the forecasting process is a key aspect of the modeling and forecasting process. One of the best methods for modeling and forecasting wind speed is the Auto-Regression and Moving Average (ARMA). In this paper, the impact of seasonal ARMA wind speed and power modeling on the reliability of power distribution systems is investigated. Daily and hourly wind speed modeling will be used to assess the reliability of residential, commercial and industrial loads when the wind power is installed at the local load.
| Original language | English |
|---|---|
| Title of host publication | 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 |
| Publisher | IEEE Computer Society |
| Pages | 1-5 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781538622124 |
| DOIs | |
| State | Published - 29 Jan 2018 |
Publication series
| Name | IEEE Power and Energy Society General Meeting |
|---|---|
| Volume | 2018-January |
| ISSN (Print) | 1944-9925 |
| ISSN (Electronic) | 1944-9933 |
Bibliographical note
Publisher Copyright:© 2017 IEEE.
Keywords
- ARMA
- Forecasting
- Reliability
- Seasonal effect
- Wind speed
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Nuclear Energy and Engineering
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
