| 引用本文: | 陈 晨,李平康,贾智州.基于鲁棒方差优化的电力系统频率控制研究[J].电力系统保护与控制,2016,44(11):53-60.[点击复制] |
| CHEN Chen,LI Pingkang,JIA Zhizhou.Frequency control for power systems based on robust variance optimization[J].Power System Protection and Control,2016,44(11):53-60[点击复制] |
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| 摘要: |
| 随着新能源发电大规模并网，随机负荷扰动给电力系统稳定优化运行提出了新的挑战。针对自动发电控制过程中存在的随机扰动和参数摄动的问题，提出了一种基于鲁棒方差约束的状态反馈控制器的参数优化方法。根据鲁棒方差控制(Robust Variance Control，RVC)中不等式约束条件，分析了闭环系统在抑制随机扰动和提高阶跃扰动响应动态性能之间的博弈关系。构造了融合稳态状态方差和控制能量输出约束的优化问题，利用线性矩阵不等式(Linear Matrix Inequality，LMI)获得了鲁棒方差控制器参数。在此基础上，对配置的区域极点圆心坐标值和正标量两个参数进行遗传优化，得到性能指标最优的控制策略。以两区域电力系统模型为例，表明该方法能够有效抑制随机扰动并保持良好的控制性能和鲁棒性能。 |
| 关键词: 负荷扰动 频率控制 鲁棒方差约束 参数摄动 遗传优化 |
| DOI：10.7667/PSPC151408 |
| 投稿时间：2015-08-11修订日期：2016-02-21 |
| 基金项目: |
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| Frequency control for power systems based on robust variance optimization |
| CHEN Chen,LI Pingkang,JIA Zhizhou |
| (School of Mechanical and Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China) |
| Abstract: |
| With the large-scale grid interconnection of the new energy power generation, stochastic load disturbance gives the new challenges about how to maintain the stability and optimization operation of power systems. For the problems of stochastic load disturbance and parameter uncertainties in automatic generation control process, a parameter optimization algorithm of the state feedback controller based on robust variance constraint is proposed. Based on the inequality constraints of robust variance control principles, the game relationship between stochastic disturbance rejection and dynamic performance improvement of step disturbance response of closed loop system is analyzed. The constrained optimization problems considering steady state variance and control energy output constraint is constructed and LMI is used to design the controller parameters. Using genetic algorithm, closed loop poles circle center and positive scalar are optimized to design the control strategy with the optimal performance index. Two-area power system model is provided to demonstrate that the presented method can effectively restrain stochastic load disturbance and have good control performance and robustness. |
| Key words: load disturbance frequency control robust variance constraint parameter perturbations genetic optimization |
