FAULT PREVENTION AND DIAGNOSIS THROUGH SCADA TEMPERATURE DATA ANALYSIS OF AN ONSHORE WIND FARM

Wind turbines, due to the distribution of the source, are an energy conversion system having low density on the territory, whose operational behaviour and production on the short term strongly depends on the stochastic nature of wind. They therefore need accurate assessment prior installation and careful condition monitoring in the operative phase. In the present work, smart post processing of Supervisory Control And Data Acquisition (SCADA) control system data sets is employed for fault prevention and diagnosis through the analysis of the temperatures of the machines. Automatic routines are developed for monitoring the evolution of all the temperature SCADA channels against power production. The methods are tested on an onshore wind farm sited in southern Italy, where nine turbines with 2 MW rated power are installed. The tests are performed both ex post and in real time: it is shown that in the former case, a major mechanical problem is detected, and in the latter case a significant problem to the cooling system is identified before compromising turbine functionality.