Abstract
Current study results on have been published. According to news originating from Chengdu, People’s Republic of China, by NewsRx correspondents, research stated, “This paper proposes a diagnosis method based on time series and support vector machine (SVM) to improve the timeliness, accuracy, and feasibility of fault diagnosis for photovoltaic (PV) arrays.” Funders for this research include International Scientific And Technological Cooperation Projects of Chengdu City. Our news editors obtained a quote from the research from Chengdu Technological University: “It obtains the nominal output power of the PV array based on real-time collected data such as voltage, current, radiation, and temperature and normalizes the power values at different time points throughout the day to form a time series. Using the time series values as input data for a “one-to-one” multiclass classifier, we can identify and classify typical operational faults such as random shading, fixed shading, and aging degradation of PV arrays.”
NETL
NSTL
Hindawi Publishing Group