6533b85dfe1ef96bd12bddbe
RESEARCH PRODUCT
A method for detecting malfunctions in PV solar panels based on electricity production monitoring
Stefan Van GulckLiesje De BoeckBart Van Der MeersscheTeresa LeónFermin MallorMichel Meulderssubject
Functional principal component analysisRenewable Energy Sustainability and the EnvironmentComputer sciencebusiness.industryElectricity production monitoring020209 energyPhotovoltaic systemStatistical quality control02 engineering and technologyAnomaly detectionStatistical process controlcomputer.software_genreSolar energyOutlier0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceControl chartAnomaly detectionData miningbusinesscomputerPhotovoltaic solar panel sister arraysParametric statisticsdescription
In this paper a new method is developed for automatically detecting outliers or faults in the solar energy production of identical sets (sister arrays) of photovoltaic (PV) solar panels. The method involves a two-stage unsupervised approach. In the first stage, "in control" energy production data are created by using outlier detection methods and functional principal component analysis in order to remove global and local outliers from the data set. In the second stage, control charts for the "in control" data are constructed using both a parametric method and three non-parametric methods. The control charts can be used to detect outliers or faults in the production data in real-time or at the end of the day. As an illustration, the method is applied to analysis of the real energy production data of six sets of "identical" PV solar panels over a period of three years. Tests indicate that the proposed method is able to successfully detect a reduction in efficiency in one of the solar panel sets by up to 5%. Control charts based on parametric and non-parametric methods both show good performance results. ispartof: Solar Energy vol:153 pages:51-63 status: published
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2017-09-01 |