ANN-based Photovoltaic Fault Detection Algorithm

Muhammad Hussain (Speaker), Dhimish, M. (Contributor to Paper or Presentation), Schofield, N. (Contributor to Paper or Presentation), Titarenko, S. (Contributor to Paper or Presentation)

Activity: Talk or presentation typesOral presentation

Description

In this paper, a fault detection algorithm for photovoltaic systems based on artificial neural networks (ANN) is proposed. Numerous literatures can be found on the topic of PV fault detection through the implementation of artificial intelligence. The novel part of this research is the successful development, deployment and validation of a fault detection PV system using radial basis function (RBF), requiring only two parameters as the input to the ANN (solar irradiance and output power). The results obtained through the testing of the developed ANN on a PV installation of 2.2 kW capacity, provided an accuracy of 97.9%.
Period5 Nov 2020
Event title10th Solar & Storage Integration Workshop: International Workshop on Integration of Solar Power and Storage into Power Systems
Event typeWorkshop
Conference number10
Degree of RecognitionInternational