Najdawi, Farah Z. and Villarreal, Ruben (2023) Utilizing the Vector Autoregression Model (VAR) for Short-Term Solar Irradiance Forecasting. Energy and Power Engineering, 15 (11). pp. 353-362. ISSN 1949-243X
![[thumbnail of epe_2023110314131322.pdf]](http://geographical.go2journals.com/style/images/fileicons/text.png)
epe_2023110314131322.pdf - Published Version
Download (2MB)
Abstract
Forecasting solar irradiance is a critical task in the renewable energy sector, as it provides essential information regarding the potential energy production from solar panels. This study aims to utilize the Vector Autoregression (VAR) model to forecast solar irradiance levels and weather characteristics in the San Francisco Bay Area. The results demonstrate a correlation between predicted and actual solar irradiance, indicating the effectiveness of the VAR model for this task. However, the model may not be sufficient for this region due to the requirement of additional weather features to reduce disparities between predictions and actual observations. Additionally, the current lag order in the model is relatively low, limiting its ability to capture all relevant information from past observations. As a result, the model’s forecasting capability is limited to short-term horizons, with a maximum horizon of four hours.
Item Type: | Article |
---|---|
Subjects: | Opene Prints > Medical Science |
Depositing User: | Managing Editor |
Date Deposited: | 09 Nov 2023 05:56 |
Last Modified: | 09 Nov 2023 05:56 |
URI: | http://geographical.go2journals.com/id/eprint/2999 |