Abstract
Predicting the amount of soiling accumulated on the collectors is a key factor when optimizing the trade‐off between reducing soiling losses and cleaning costs. An important influence on soiling losses is natural cleaning through rain. Several soiling models assume complete cleaning through rain for daily rain sums above a model specific threshold and no cleaning otherwise. However, various studies show that cleaning is often incomplete. This study employs two statistical learning methods to model the cleaning effect of rain, aiming to achieve more accurate results than a simple totally cleaned/no cleaning answer while also considering other parameters besides the rain sum. The models are tested using meteorological and soiling data from 33 measurement stations in West Africa. Linear regression seems to be a good alternative for predicting the reduction in soiling levels after a rainfall.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call