DocumentCode
3088463
Title
Developing a matlab tool while exploiting neural networks for combined prediction of hour´s ahead system load along with irradiation, to estimate the system load covered by PV integrated systems
Author
Kolentini, E. ; Sideratos, G. ; Rikos, V. ; Hatziargyriou, N.
Author_Institution
NTUA, Athens, Greece
fYear
2009
fDate
9-11 June 2009
Firstpage
182
Lastpage
186
Abstract
Renewable energy systems (RES), being a controversial issue regarding their integration into the electric power systems, create the necessity for research. In order to take part in the electricity market, a critical point is the prediction of the system load as well as the prediction of the RES production. Within this scope, a matlab tool was developed to facilitate both the prediction of the system load as well as the PV production in several penetration levels.
Keywords
neural nets; photovoltaic power systems; power generation economics; power markets; power system analysis computing; PV integrated systems; electricity market; matlab tool; neural networks; renewable energy systems; system load estimation; Artificial neural networks; Biological neural networks; Chromium; Economic forecasting; Electricity supply industry; Neural networks; Neurons; Production systems; Temperature; Voltage; grid integration; matlab GUI tool; neural networks (NN); photovoltaic systems (PV); renewable energy systems (RES); system load;
fLanguage
English
Publisher
ieee
Conference_Titel
Clean Electrical Power, 2009 International Conference on
Conference_Location
Capri
Print_ISBN
978-1-4244-2543-3
Electronic_ISBN
978-1-4244-2544-0
Type
conf
DOI
10.1109/ICCEP.2009.5212061
Filename
5212061
Link To Document