Presentations

Abstract

This presentation introduces a new open-source dataset from a large (>20 turbine) European onshore wind farm where upgrades worth 5% additional AEP have been installed. The data comprises 5 years of recent SCADA data during which two significant upgrades were deployed: aerodynamic upgrades in 2021 (RES AeroUp product) and controller parameter optimisations in 2024 (RES TuneUp product). The presentation will elaborate on the AEP uplift and uncertainty analysis of the open-source dataset using the publicly available wind-up tool [1]. The presentation aims to progress the industry’s ability to accurately measure AEP uplift with uncertainty quantification by making public both wind-up (also presented at the WindEurope Tech Workshop 2024) and a new unique dataset where wind-up and other tools can be applied to validate multiple wind turbine enhancement products. The open-source dataset will be a valuable resource to technical stakeholders in the wind industry. Containing all the original SCADA channels, the dataset is applicable to a wide range of research use cases. It can be used to validate pre-construction energy yield models (including wind flow and wake models), refine post-construction analysis techniques, and can be used for more general wind farm performance research. The process of creating an open-source wind farm dataset and ensuring it has good findability, accessibility, interoperability, and reusability (FAIR) will also be presented. The presentation will describe the latest RES method for measuring AEP uplift of wind farm enhancements, embodied in the open-source Python tool wind-up. The method can be used either with wind measurements (eg LiDARs) or side-by-side turbine analysis, where the performance of upgraded turbines is compared to unchanged reference turbines. This can be arranged as a before/after test or through toggling in the case of software-based enhancements. The measured uplift can then be extrapolated to long-term conditions to estimate AEP uplift. The RES method leverages techniques from the power performance standard IEC 61400-12-1:2022 and extends these techniques to meet the challenges of side-by-side AEP validation. Innovative aspects of the RES method include: * Ability to use multiple types of references including turbines, masts and LiDARs * Option to analyse the uplift using all wind directions combined (including waked sectors) by using directional detrending and accounting for the state of all upwind turbines * A reverse assessment, where the roles of the test and references are swapped, to identify and correct bias * Verification that all reference turbines measure 0% uplift for each other * AI and ML techniques are used to perform a sensitivity analysis, a key input into further product development. The benefits of the method include: * Robust AEP uplift validation is possible in reasonable timescales even if mast/LiDAR data is not available. * The sensitivity analysis reveals the conditions where the upgrade is most effective. The presentation will focus on the open-source dataset as a real-world case study and conclude with the uplift analysis results for the two upgrades: * AeroUp, installed 2021, added 4% AEP * TuneUp, installed 2024, added 1% AEP References [1] wind-up Python package v0.1.11, https://pypi.org/project/res-wind-up/0.1.11/, January 22, 2025