PV Predictions Made Easy: Flexibility Through Simplicity

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CIRED 2019 - 1857.pdf (739.88 KB)

Paper number

1857

Working Group Number

Conference name

CIRED 2019

Conference date

3-6 June 2019

Conference location

Madrid, Spain

Peer-reviewed

Yes

Short title

Convener

Authors

Gerards, Marco E. T., University of Twente, Netherlands
Hurink, Johann L., University of Twente, Netherlands

Abstract

Accurate predictions of PV output power play an important role in supporting the energy transition. This article presents an approach that aims at such predictions for PV installations on a household level. It is designed to be implemented easily on home energy management systems with low computational power. The presented prediction algorithm is self-learning, does not need physical parameters of the PV installation and can deal with changing circumstances such as objects (partially) blocking the PV panels. The method is straightforward to implement and a reference implementation in Matlab is given. An evaluation demonstrates that when the inputs used for the approach (irradiance) are correctly predicted, the predicted PV power output is also accurate.

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Publisher

AIM

Date

2019-06-03

Published in

CIRED 2019 Conference

Permanent link to this record

https://cired-repository.org/handle/20.500.12455/610
http://dx.doi.org/10.34890/831

ISSN

2032-9644

ISBN

978-2-9602415-0-1