互联电网负荷频率控制对保障电网安全可靠运行具有重要作用,适宜的控制器参数整定使得电网在各种随机扰动下维持系统频率稳定和联络线功率交换值恒定.针对两区域互联电网的负荷频率控制器参数优化整定问题,提出一种基于智能优化算法的控制器参数整定设计方案.该方案采用最小化时间乘误差绝对值积分作为目标函数,运用灰狼优化算法搜索获得最优化的负荷频率控制器参数.灰狼优化算法模拟了狼群的社会分层机制和群体狩猎行为,使得控制器参数优化整定过程具有快速、高效、自适应和精度高等优点.此外,重点考虑了控制器参数不确定性可能导致的控制器性能衰减,讨论了控制器的脆弱性问题.建立了两区域互联电网负荷频率控制系统仿真模型,采用所提优化算法获取PI/PID型负荷频率控制器参数,仿真结果显示所提算法设计PI/PID控制器相比于传统方法和其他的智能优化算法具有更好的寻优能力和控制性能,并且优化获得的控制器在系统参数和控制器参数不确定性下具有鲁棒性和非脆弱性.%Load frequency control (LFC) plays an important role in ensuring safe and reliable operation of the interconnected power grids.Appropriate controller parameter settings can maintain the system frequency stability and a constant tie line power exchange value under various random load disturbances.On the issue of tuning optimization of two-area interconnected power grid LFC controller parameters,this paper presents a controller parameter optimal design scheme based on intelligent optimization algorithm.The scheme adopted integral of time multiplied absolute error (ITAE) as the objective function and grey wolf optimizer (GWO) was employed for searching the optimal LFC controller parameters.GWO algorithm has the advantages of swiftness,efficiency,adaptivity and high accuracy during controller parameters optimization tuning process,because the algorithm imitates the features of leadership hierarchy and pack hunting behaviors of grey wolves.In addition,the possibility of controller performance degradation was also considered in this paper due to the parameter uncertainty of controller itself.And the fragility of the controller was investigated.First,a two-area interconnected power grid LFC control system simulation model was established;then,the proposed optimization algorithm was used to optimize the PI/PID type LFC controller parameters;finally,the simulation results validated that the proposed PI/PID design method has better optimization capability and control effectiveness in comparison to conventional design method and other intelligent optimization algorithms.And the optimized PI/PID controller can ensure robustness and non-fragility under system parameter uncertainty and the controller parameter uncertainty.
展开▼
