To reveal the performance of primary frequency regulation of the 600MW sub-critical thermal power units in a wide load range and accurately simulate the process, the primary frequency regulation performance of a 600MW sub-critical thermal power unit was studied with a wide load ranging from 20% to 90% under rated conditions. The model of steam turbine in BPA was modified in consideration of steam pressure and the valve throttling effect. The primary frequency regulation performance of the unit was simulated with the modified model. The research results show that the primary frequency regulation performance of the thermal power unit is poor at low load and the results of simulation with the modified model are highly consistent with the tested data due to consideration of steam pressure and valve throttling effect, meaning that the model can be used to simulate the primary frequency regulation of the thermal power unit with wide load operation accurately.

Against the backdrop of achieving the “dual carbon” reduction goals, the proportion of renewable energy consumption in China is gradually increasing, and more and more thermal power units are gradually being operated at the deep peak shaving states, which puts forward higher requirements for stable operation of the power grid system. In view of the current situation, this paper designs a new type of Python-based parameter modeling software for turbine control systems, including the load selection module, data pre-processing module, parameter identification module, and result output module. To solve the problem that the primary frequency regulation parameters of the units operated at the deep peak shaving states change with the load, the software is designed to set key model parameters of different load segments of the units. The actual measurement results of a unit operated at the deep peak shaving state show that this developed software is convenient and friendly to operate, creates accurate parameter identification results, and has a wider range of applicability.

The parameter identification of the steam turbine speed governing system needs to be realized by the fitting of the measured response curve of the steam turbine active power. The national standard puts forward strict requirements on the error of the identification result. At present, error calculation is often realized by manual punctuation, which is a complicated process and greatly influenced by human judgment. Hence it needs to be improved urgently. In this paper, polynomial fitting and improved sliding window method are used to optimize the error identification algorithm of the steam turbine active power response curve. The visualization of the program is realized based on the Python language. The algorithm improves the data processing efficiency and reduces the influence of human judgment. The calculation results meet the standard requirements.

No abstract

A simplified dynamic model of the rotor-bearing-support system is established considering the influence of pedestal flexibility. The vibration characteristics of the system with a flexible pedestal are analyzed. There are two resonance peaks during the run-up process for this kind of system. It is generally thought that the stiffness difference in the vertical and the horizontal direction is the main cause of the double resonance peak phenomenon. The results of the paper show that the flexible pedestal support also causes the double resonance peak phenomenon. The shaft relative vibration cannot reflect the influence of rotor unbalances well near the resonance zone. In this case, the bearing vibration should be preferred in the balance test. The vibration phenomenon on an actual unit is analyzed as an example.