摘要
该文以复杂山地风电场机组尾流后发电量最优为目标函数,以单个机组的发电量和安全性为个体适应度,创新性地提出一种基于尾流后发电量最优兼顾安全性的复杂山地风电场微观选址方法。经实际复杂山地风电场的应用分析发现,全场年净发电量相比于传统人工经验排布方法提升1.6%,各机组安全性识别指标均处于高风险阈值之下,降低机组运行风险。研究表明,该方法在复杂山地风电场的微观选址中具有较强的指导性和实用性,可用于实际风电场微观选址机组排布优化及安全保障。
The interaction of wake effects and complex topography in mountainous wind farms poses challenges to power generation and escalates the risk of turbine failure.This paper proposes a novel micro-siting method designed for complex mountainous wind farms,which takes maximizing energy yield and ensuring turbine safety as the objective function.The proposed methodology takes power generation and safety performance of each turbine as the individual fitness.A case study on an actual operational wind farm reveals that the implementation of this method obtains a 1.6%increase in annual net power generation compared to conventional empirical approaches.Furthermore,the method ensures that safety identification indicators for each turbine remain beneath established high-risk thresholds,affirming the comprehensive safety status of the wind farm.The demonstrated results indicate that the method can serve as an instructive and practical tool for micro-siting optimization and risk mitigation in complex mountainous wind environments.
作者
李金缀
姜宏超
Li Jinzhui;Jiang Hongchao(Beijing Goldwind Science&Creation Windpower Equipment Co.,Ltd.,Beijing 100176,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2024年第8期486-493,共8页
Acta Energiae Solaris Sinica
关键词
风电场
微观选址
遗传算法
山地
安全性
CFD仿真
叶轮面
wind farm
micro sitting
genetic algorithm
mountainous
security
CFD simulation
rotor plane