Posters

Abstract

With a large number of wind farms operating over years, the performance analysis of those farms becomes an important subject. This study tries to propose a general methodology to address this issue and a case study to demonstrate its application. * Firstly, the failure in measurement system must be detected at the first step. It could be separated into 2 categories: data missing and data erroneous. After being detected, those measurement failure datapoints will be excluded from further analysis. * Secondly, the total dataset after measurement failure detection will be classified into 7 categories: normal, stop, curtailment, partial stop & partial curtailment (transition between stop/curtailment and normal), over production and under production: output power lower than expected * The calculation of the real power curve is implemented on normal datapoint only, with the respect to the IEC-61400-12-1 standard. Air density correction is implemented on the wind speed if the measurement of temperature, humidity and pressure are available. * Then, the losses are estimated by applying the measured speed (corrected if possible) to the real power curve determined in the previous step. * At last, in order to have a general view on the performance of wind turbines, several KPIs are calculated. A case study: La Haute Borne Wind Farm Firstly, the measurement failure is detected and classified based on the cause. Currently, our algorithm is capable to detect 14 types of measurement failure.