A Short-Term Spatio-Temporal Approach for Photovoltaic Power Forecasting

• Type: Article in International Conference Proceedings Book
• Date: 2016

Authors

Tascikaraoglu, A (Author) Other; Sanandaji, BM (Author) Other; Chicco, G (Author) Other; Cocina, V (Author) Other; Spertino, F (Author) Other; Erdinc, O (Author) Other; Paterakis, NG (Author) Other; Catalao, JPS (Author) FEUP

Conference proceedings International

Title: 2016 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC)

Pages: 1-7

19th Power Systems Computation Conference (PSCC)

Genova, ITALY, JUN 20-24, 2016

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 15 Citations

Other information

Authenticus ID: P-00K-VFY

DOI: 10.1109/pscc.2016.7540958

Abstract (EN): This paper presents a Photovoltaic (PV) power conversion model and a forecasting approach which uses spatial dependency of variables along with their temporal information. The power produced by a PV plant is forecasted by a PV conversion model using the predictions of three weather variables, namely, irradiance on the tilted plane, ambient temperature, and wind speed. The predictions are accomplished using a spatio-temporal algorithm that exploits the sparsity of correlations between time series data of different meteorological stations in the same region. The performances of the forecasting algorithm as well as the PV conversion model are investigated using real data recorded at various locations in Italy. The comparisons with various benchmark methods show the effectiveness of the proposed approaches over short-term forecasts.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7