摘要
在我国“构建以新能源为主体的新型电力系统”的战略目标下,风电等新能源得到大力发展,实现风电功率的可调控性尤为重要。本文提出一种基于模型预测控制的风电场的有功功率优化分解方法,该方法基于风电场预测模型,以风电场风能损失最小为目标函数,综合考虑了风电场内各台风机的有功可调节能力、功率调节指令等约束条件。
Under the strategic goal of"building a new power system with new energy as the main body"in China,there has been a significant development of new energy,particularly wind power.In order to realize the adjustability of wind power,it is crucial to optimize the management of wind farms.Therefore,this paper proposes an optimal decomposition method of active power for wind farms based on model predictive control.The approach is founded on the wind farm prediction model and aims to minimize wind energy loss,considering the constraints such as the active adjustable capacity and power regulation instructions of each wind turbine in the wind farm.By using this approach,the wind power fluctuations can be better regulated and managed,thus contributing to a more stable and efficient power system.
作者
姜昊
JIANG Hao(New Energy Branch of Datang Shaanxi Power Generation Co.,Ltd.,Xi'an,Shanxi 710000,China)
出处
《自动化应用》
2023年第9期63-65,共3页
Automation Application
关键词
风电场
模型预测控制
有功功率
优化分解
wind farm
model predictive control
active power
optimization decomposition