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作 者:赵熙临[1] 李金星 ZHAO Xilin;LI Jinxing(School of Electrical and Electronic Engineering,Hubei University of Technology,Wuhan 430068,Hubei Province,China)
机构地区:[1]湖北工业大学电气与电子工程学院,湖北省武汉市430068
出 处:《现代电力》2025年第2期220-229,共10页Modern Electric Power
基 金:湖北省重点研发计划项目(2021BAA193)。
摘 要:高比例可再生能源并网增大了电力系统的供需不确定性,需要自动发电控制(automatic generation control,AGC)方法在应对不同的调频需求时更具针对性。文中以含风电电力系统为研究对象,首先,通过构建互联电网AGC模型,分析了基于模型预测控制(model predictive control,MPC)的系统控制流程;其次,针对传统MPC在线计算复杂度过高的问题,引入条件触发策略以降低MPC执行优化计算的频次;并考虑到系统不同状态下调频需求存在的差异,设计了能跟随系统状态进行动态调整的触发规则,以获得更好调频控制效果;最后,仿真验证了所提方法在保证控制性能的基础上能有效降低系统在线计算复杂度,并在面对不同的调频需求时具有更好的系统稳定性。The integration of a high proportion of renewable energy into the grid amplifies the uncertainty in supply and demand of the power system,which requires an more targeted automatic generation control(AGC)methods to meet different FM needs.In this paper,the wind power system is taken as the research object.The system control process based on model predictive control(MPC)is first analyzed by constructing the AGC model of interconnected power grid.Then,to address the issue of high computational complexity of traditional online MPCS,a conditional trigger strategy is introduced to reduce the frequency of optimal computation.Trigger rules and thresholds are designed to dynamically adjust the different frequency modulation requirements of various states within the system,so as to achieve optimal trigger and control effects.Finally,the simulation results demonstrate that the proposed method can effectively reduce the online computing complexity of the system while ensuring the control performance at the same time,and it exhibits better system stability in respond to various frequency modulation requirements.
关 键 词:自动发电控制 风电 模型预测控制 动态触发 不确定性
分 类 号:TM73[电气工程—电力系统及自动化]
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