{"title":"利用唤醒重定向控制优化风电场功率输出","authors":"","doi":"10.1016/j.renene.2024.121357","DOIUrl":null,"url":null,"abstract":"<div><p>The wake effect, which is caused by the upstream turbines in a wind farm, adversely affects the efficiency of downstream turbines, leading to reduced energy generation and increased turbine fatigue loading. To mitigate this effect, a real-time wind farm control technique, i.e., wake redirection control (WRC), employing teaching learning-based optimization (TLBO) is introduced. This technique redirects the wakes away from the downstream turbines in real time, allowing them to generate more power by sacrificing some of the power generated by the upstream turbines. As a result, the total power generated by the wind farm is maximized. A low-fidelity 20-turbine real-life offshore wind farm is modeled and simulated in FLORISSE_M, the MATLAB version of the FLORIS (FLOw Redirection and Induction in Steady-state). The power produced by the wind farm model is maximized in real time by employing TLBO. The optimization results (i.e., the optimized yaw angles) are validated using the corresponding high-fidelity wind farm model developed in SOWFA (Simulator fOr Wind Farm Applications). Various results are presented to demonstrate that the TLBO-based WRC positively affects the power generated by the wind farm.</p></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":null,"pages":null},"PeriodicalIF":9.0000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization of wind farm power output using wake redirection control\",\"authors\":\"\",\"doi\":\"10.1016/j.renene.2024.121357\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The wake effect, which is caused by the upstream turbines in a wind farm, adversely affects the efficiency of downstream turbines, leading to reduced energy generation and increased turbine fatigue loading. To mitigate this effect, a real-time wind farm control technique, i.e., wake redirection control (WRC), employing teaching learning-based optimization (TLBO) is introduced. This technique redirects the wakes away from the downstream turbines in real time, allowing them to generate more power by sacrificing some of the power generated by the upstream turbines. As a result, the total power generated by the wind farm is maximized. A low-fidelity 20-turbine real-life offshore wind farm is modeled and simulated in FLORISSE_M, the MATLAB version of the FLORIS (FLOw Redirection and Induction in Steady-state). The power produced by the wind farm model is maximized in real time by employing TLBO. The optimization results (i.e., the optimized yaw angles) are validated using the corresponding high-fidelity wind farm model developed in SOWFA (Simulator fOr Wind Farm Applications). Various results are presented to demonstrate that the TLBO-based WRC positively affects the power generated by the wind farm.</p></div>\",\"PeriodicalId\":419,\"journal\":{\"name\":\"Renewable Energy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":9.0000,\"publicationDate\":\"2024-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Renewable Energy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0960148124014253\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Renewable Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0960148124014253","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
摘要
风电场上游涡轮机产生的尾流效应会对下游涡轮机的效率产生不利影响,从而导致发电量减少和涡轮机疲劳负荷增加。为了减轻这种影响,引入了一种实时风场控制技术,即采用基于教学学习的优化(TLBO)的唤醒重定向控制(WRC)。该技术可实时将湍流重新导向下游涡轮机,通过牺牲上游涡轮机产生的部分电能,使其产生更多电能。因此,风电场的总发电量达到最大。FLORISSE_M 是 FLORIS(FLOw Redirection and Induction in Steady-state)的 MATLAB 版本。通过使用 TLBO,风电场模型产生的功率实时达到最大。优化结果(即优化偏航角)通过在 SOWFA(风电场应用模拟器)中开发的相应高保真风电场模型进行了验证。各种结果表明,基于 TLBO 的 WRC 对风电场的发电量产生了积极影响。
Optimization of wind farm power output using wake redirection control
The wake effect, which is caused by the upstream turbines in a wind farm, adversely affects the efficiency of downstream turbines, leading to reduced energy generation and increased turbine fatigue loading. To mitigate this effect, a real-time wind farm control technique, i.e., wake redirection control (WRC), employing teaching learning-based optimization (TLBO) is introduced. This technique redirects the wakes away from the downstream turbines in real time, allowing them to generate more power by sacrificing some of the power generated by the upstream turbines. As a result, the total power generated by the wind farm is maximized. A low-fidelity 20-turbine real-life offshore wind farm is modeled and simulated in FLORISSE_M, the MATLAB version of the FLORIS (FLOw Redirection and Induction in Steady-state). The power produced by the wind farm model is maximized in real time by employing TLBO. The optimization results (i.e., the optimized yaw angles) are validated using the corresponding high-fidelity wind farm model developed in SOWFA (Simulator fOr Wind Farm Applications). Various results are presented to demonstrate that the TLBO-based WRC positively affects the power generated by the wind farm.
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