CAJ | 학술논문

精确、快速的基波分量跟踪是对电网运行状态进行分析和评估的前提。提出一种基于移动窗口迭代修正策略的自适应无迹卡尔曼平滑算法(moving window based adaptive unscented Kalman smoother，MW_AUKS)。该方法兼顾稳态检测精度和动态检测速度，前者通过在前向无迹滤波过程中并行嵌入一个后向迭代修正的 Rauch-Tung-Striebel 平滑器实现，后者则先依据窗口内平均新息量在线判断是否有突变发生，再对状态估计协方差做自适应修正运算。利用建立的基波分量非线性状态估计模型对所提算法进行验证，结果表明所提算法可精确跟踪到基频、功率角、有功功率、视在功率等参数，并大幅提高初始收敛速度，同时准确判断和快速跟踪到状态突变。
정학、쾌속적기파분량근종시대전망운행상태진행분석화평고적전제。제출일충기우이동창구질대수정책략적자괄응무적잡이만평활산법(moving window based adaptive unscented Kalman smoother，MW_AUKS)。해방법겸고은태검측정도화동태검측속도，전자통과재전향무적려파과정중병행감입일개후향질대수정적 Rauch-Tung-Striebel 평활기실현，후자칙선의거창구내평균신식량재선판단시부유돌변발생，재대상태고계협방차주자괄응수정운산。이용건립적기파분량비선성상태고계모형대소제산법진행험증，결과표명소제산법가정학근종도기빈、공솔각、유공공솔、시재공솔등삼수，병대폭제고초시수렴속도，동시준학판단화쾌속근종도상태돌변。
Accurate and fast tracking of fundamental components is a precondition for analysis and estimation of the power grid. A novel moving window based adaptive unscented Kalman smoother (MW_AUKS) which adopts iterative correction strategy was proposed. This method gives consideration to both the steady-state detection accuracy and dynamic detection speed. The first objective is achieved by introducing a backward Rauch-Tung-Striebel smoother to the forward unscented Kalman filter simultaneously. Based on the mean value of innovation within the window, whether sudden change of the state has happened is judged online. Then, state estimation covariance would be reset adaptively once the change is confirmed. Finally, multigroup simulations are conducted by means of a presented nonlinear state space estimation model. Results show that the new algorithm can effectively estimate the fundamental components, such as frequency, power angle and active/apparent power, and greatly speedup the rate of initial convergence. Meanwhile, accurate detection and rapid tracking of the state sudden change could be achieved.