Parameter Identification Method for Steam Turbine Bodies under Wide-Load Operation

With the growing demand for flexible regulation in power systems, wide-load operation has become standard practice for thermal power units. However, conventional parameter identification methods often struggle to accurately model turbine body parameters under wide-load and full operating conditions. Moreover, they typically rely on manual intervention, leading to low efficiency and limited adaptability. To overcome these limitations, this paper presents a turbine body parameter identification method based on an Improved Grey Wolf Optimizer (IGWO) algorithm, which processes operational data from the unit. The proposed approach adaptively identifies turbine body parameters using the IGWO, enabling rapid construction of the governor system model under wide-load operation. Experimental results demonstrate that the method accurately establishes turbine parameter models covering the entire operating range, significantly enhancing both identification efficiency and accuracy.