Posters

Abstract

Wind energy generation often exhibits significant discrepancies between financial model expectations and actual energy production. Despite thorough analysis of potential causes, a gap persists between operational reality and preconstruction projections. This gap is partly attributed to the underperformance of the power curve. Due to the inherent nature of production data, analyzing causes related to power curve performance in absolute terms becomes very challenging and a common practice is to evaluate power curve performance in relation to nearby turbines.  This study examines the various factors that can individually impact the performance of the power curve and attempts to quantify their actual effects using SCADA data from operational wind farms. After analyzing the real power curves, DNV proposes an exhaustive list of possible causes affecting turbine performance, their impact on production, and potential preventive measures, which can explain part of this gap. Due to the inherent nature of some causes, accurately quantifying losses is challenging. However, identifying if a wind farm is affected by these conditions can influence decisions before commissioning, such as contractual safeguards, chosen wind technology, or future energy production expectations of the asset.  Similarly, once the wind farm is operational, corrective measures like adjusting turbine configuration parameters can minimize the impact. This study benefits wind energy developers by providing a more accurate understanding of wind turbine performance, enabling informed decisions regarding the development and operation of wind projects.