Linyue Gao, Christopher Milliren, Teja Dasari, Alexander A Knoll, Jiarong Hong
{"title":"Catch the wind: Optimizing wind turbine power generation by addressing wind veer effects.","authors":"Linyue Gao, Christopher Milliren, Teja Dasari, Alexander A Knoll, Jiarong Hong","doi":"10.1093/pnasnexus/pgae480","DOIUrl":null,"url":null,"abstract":"<p><p>Wind direction variability with height, known as \"wind veer,\" results in power losses for wind turbines (WTs) that rely on single-point wind measurements at the turbine nacelles. To address this challenge, we introduce a yaw control strategy designed to optimize turbine alignment by adjusting the yaw angle based on specific wind veer conditions, thereby boosting power generation efficiency. This strategy integrates modest yaw offset angles into the existing turbine control systems via a yaw-bias-look-up table, which correlates the adjustments with wind speed, and wind veer data. We evaluated the effectiveness of this control strategy through extensive month-long field campaigns for an individual utility-scale WT and at a commercial wind farm. This included controlling one turbine using our strategy against nine others in the vicinity using standard controls with LiDAR-derived wind veer data and a separate 2.5 MW instrumented research turbine continuously managed using our method with wind profiles provided by meteorological towers. Results from these campaigns demonstrated notable energy gains, with potential net gains exceeding 10% during extreme veering conditions. Our economic analysis, factoring in various elements, suggests an annual net gain of up to approximately $700 K for a 100-MW wind farm, requiring minimal additional investment, with potential for even larger gains in offshore settings with the power of individual turbines exceeding 10 MW nowadays. Overall, our findings underscore the considerable opportunities to improve individual turbine performance under realistic atmospheric conditions through advanced, cost-effective control strategies.</p>","PeriodicalId":74468,"journal":{"name":"PNAS nexus","volume":"3 11","pages":"pgae480"},"PeriodicalIF":2.2000,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11538590/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PNAS nexus","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/pnasnexus/pgae480","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Wind direction variability with height, known as "wind veer," results in power losses for wind turbines (WTs) that rely on single-point wind measurements at the turbine nacelles. To address this challenge, we introduce a yaw control strategy designed to optimize turbine alignment by adjusting the yaw angle based on specific wind veer conditions, thereby boosting power generation efficiency. This strategy integrates modest yaw offset angles into the existing turbine control systems via a yaw-bias-look-up table, which correlates the adjustments with wind speed, and wind veer data. We evaluated the effectiveness of this control strategy through extensive month-long field campaigns for an individual utility-scale WT and at a commercial wind farm. This included controlling one turbine using our strategy against nine others in the vicinity using standard controls with LiDAR-derived wind veer data and a separate 2.5 MW instrumented research turbine continuously managed using our method with wind profiles provided by meteorological towers. Results from these campaigns demonstrated notable energy gains, with potential net gains exceeding 10% during extreme veering conditions. Our economic analysis, factoring in various elements, suggests an annual net gain of up to approximately $700 K for a 100-MW wind farm, requiring minimal additional investment, with potential for even larger gains in offshore settings with the power of individual turbines exceeding 10 MW nowadays. Overall, our findings underscore the considerable opportunities to improve individual turbine performance under realistic atmospheric conditions through advanced, cost-effective control strategies.