Analyses and Enhancement of Linear Kalman-Filter-Based Phase-Locked Loop

Linear Kalman-filter-based phase-locked loop (LKF-PLL) has been widely applied in grid synchronization and other power system fields. It receives considerable attention for its fast startup transient which is superior to the traditional PLL. However, when the KF reaches its steady state, the Kalman gains will converge to constant values, which makes it degrade into the traditional synchronous reference frame phase-locked loop. The main aim of this article is to analyze the steady state of LKF-PLL and make a good use of its adaptive process. Based on the analysis, a design guideline of the LKF is introduced, which can help tune the Kalman gains separately to meet the engineering requirements. Besides, to enhance the dynamic performance under phase jump condition, a dynamic tracking algorithm-based LKF is proposed in this article. Comparative tests about phase detection in power system are conducted, and the results show that the proposed algorithm can greatly improve the dynamic response under phase jump condition without degrading its steady-state performance inherited by the traditional PLL.

Automated summary

This article mainly analyzes the steady state of the Linear Kalman-filter-based phase-locked loop (LKF-PLL) and its adaptive process, introduces a design guideline, and proposes a dynamic tracking algorithm under phase jump condition. Comparative tests show that the proposed algorithm can greatly improve dynamic response while maintaining steady-state performance.