Automatic PV production profile generation using geographic and historical weather data

Author

Vonk, B.M.J. ; Gibescu, Madeleine ; Veldman, Else ; Slootweg, J.G.

fYear

2014

fDate

2-5 Sept. 2014

Firstpage

1

Lastpage

6

Abstract

This paper introduces on a probabilistic model to automatically generate photovoltaic production profiles for a given geographical region and future scenarios for deployment of renewable energy resources. The model for these profiles uses local properties of buildings, demographic statistics, and historical weather data. Sub-models are calibrated with actual PV data from a smart grid pilot site in the Netherlands and literature based scenarios. It is shown that the model performs adequately and the results are compared with historical data of photovoltaic installations.

Keywords

neural nets; photovoltaic power systems; power engineering computing; probability; smart power grids; Netherlands; automatic PV production profile generation; building local properties; demographic statistics; geographic weather data; historical weather data; photovoltaic installations; probabilistic model; renewable energy resources; smart grid pilot site; Artificial neural networks; Buildings; Data models; Databases; Mathematical model; Meteorology; Probabilistic logic; GIS; Smart grid; neural network; photovoltaics;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Engineering Conference (UPEC), 2014 49th International Universities

Conference_Location

Cluj-Napoca

Print_ISBN

978-1-4799-6556-4

Type

conf

DOI

10.1109/UPEC.2014.6934668

Filename

6934668