Identification for Nonlinear Flow Characteristics of Main Steam Regulating Valves in Power Plants by Mining Special Data Segments

Nonlinear flow characteristics of main steam regulating valves play an important role on the performance of primary frequency control in thermal power generation units. Manual testing is a traditional method to capture nonlinear flow characteristics by maintaining constant steam pressures, changing control valve openings, and observing power output changes; however, such a method disturbs normal operations of power generation units. This article proposes a new method to identify nonlinear flow characteristics of main steam regulating valves by exploiting special segments hidden in historical operating data. The special segments refer to steady-state segments with constant amplitudes and slope-response segments with large amplitude changes, both of which can be automatically extracted from historical operating data. Relationships between the special segments and a nonlinear model of flow characteristics are theoretically established, and unknown model parameters are estimated by a linear dynamic programming algorithm. These special segments can separate the nonlinear flow characteristics of regulating valves from dynamic effects of steam turbines and generators at different operating points. The necessity of such a separation is demonstrated by a comparison with the Hammerstein model identification method and the sparse identification method. The identified model can be visually verified by comparing measured outputs in the extracted special segments with simulated model outputs. Industrial case studies demonstrate the effectiveness of the proposed method.