Data on Support Vector Machines (SVM) model to forecast photovoltaic power

Data in Brief

Volumn 9, Issue , 2016, Pages 13-16

  Malvoni, M ^a   De Giorgi, M G ^a   Congedo, P M ^a  

^a UNIVERSITY OF SALENTO   (Italy)

Author keywords

Forecast photovoltaic; Least Squares Support Vector Machines (LS SVM)

Indexed keywords

FORECASTING; SUPPORT VECTOR MACHINES;

DATA CONCERNS; DATA SIZE; FORECAST PHOTOVOLTAIC; HYBRID MODEL; INPUT DATAS; LEAST SQUARE SUPPORT VECTOR MACHINE; LEAST SQUARE SUPPORT VECTOR MACHINES; PHOTOVOLTAIC POWER; PHOTOVOLTAICS; SUPPORT VECTOR MACHINE MODELS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84989882746     PISSN: None     EISSN: 23523409     Source Type: Journal    
DOI: 10.1016/j.dib.2016.08.024     Document Type: DP

References (8)

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5. M.G. De Giorgi, P.M. Congedo, M. Malvoni, M. Tarantino, Short-term power forecasting by statistical methods for photovoltaic plants in south Italy, in: The 4th 5 TC19 Symposium on Environmental Instrumentation and Measurements: Protection Environment, Climate Changes and Pollution Control, 2013, pp. 171–175.
6. Malvoni, M., De Giorgi, M.G., Congedo, P.M., Data on photovoltaic power forecasting models for Mediterranean climate. Data Brief. 7 (2016), 1639–1642, 10.1016/j.dib.2016.04.063.
7. De Giorgi, M.G., Congedo, P.M., Malvoni, M., Laforgia, D., Error analysis of hybrid photovoltaic power forecasting models: a case study of Mediterranean climate. Energy Convers. Manag. 100 (2015), 117–130.
8. De Giorgi, M.G., Malvoni, M., Congedo, P.M., Comparison of strategies for multi-step ahead photovoltaic power forecasting models based on hybrid group method of data handling networks and least square support vector machine. Energy 107 (2016), 360–373, 10.1016/j.energy.2016.04.020.