PV Predictions Made Easy: Flexibility Through Simplicity

Marco E. T. Gerards*, Johann L. Hurink

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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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.
Original languageEnglish
Title of host publicationProceedings of the 25th International Conference on Electricity Distribution (CIRED 2019)
Number of pages5
ISBN (Electronic)978-2-9602415-0-1
Publication statusPublished - 3 Jun 2019
Event25th International Conference and Exhibition on Electricity Distribution, CIRED 2019 - Feria de Madrid, Madrid, Spain
Duration: 3 Jun 20196 Jun 2019
Conference number: 25

Publication series

NameCIRED Conference Proceedings
ISSN (Print)2032-9644


Conference25th International Conference and Exhibition on Electricity Distribution, CIRED 2019
Abbreviated titleCIRED
Internet address


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