Performance analysis of an operating windfarm of 21MW in Greece for a period of three years

Abstract

Wind power is currently the fastest growing exploited source of energy globally. Hence there is an urgent need to understandhow wind turbines perform from different perspectives. Even though condition monitoring systems have a huge impact inoptimizing wind farm performance via fault anticipation, they do omit several aspects concerning performance. Seemingly,there is a scarcity of studies that attempt to deliver a quick and practical method for wind farm performance analysis, which isthe aim of this study.This paper presents a methodology for evaluating the performance of operating wind farms via the use of the SupervisoryControl and Data Acquisition System (SCADA) and modeled data. The potential annual energy is calculated per individualturbine, factoring in underperforming/loss events to present their power output in accordance with a representative derivedoperational power curve. Losses/underperformance events are calculated and categorized into several groups, aimed atidentifying and quantifying their causes.The methodology requires both anemometry data from the SCADA system, an onsite meteorological mast, a lidar incombination with the mast as well as modeled data. The discrepancy of the data representing the valid points of the powercurve is also taken into consideration when assessing performance, i.e. wind speed vs power output of events that are notloss/underperformance. Production loss and relative standard deviation of power/energy output are the main results obtainedin this paper. Finally, a number of optimization measures are suggested in order to boost performance, which can enhancea wind farm’s financial results.To assess the reliability of the proposed methodology, a case study was conducted and evaluated. The case study concernsa windfarm with nominal capacity of 21MW in Kitheronas, Viotia county, Greece which has been operational sinceNovember 2014. The case study shows that the methodology is capable of determining potential energy and associatedlosses/underperformance events. Several questions were raised during the assessment and are discussed in this work, recommendationsfor optimization measures are presented at the end of the paper. It also contains a discussion on the limitationsand uncertainties associated with the presented methodology and case study.