In order to realize the cold end optimization of direct air-cooled units, a cold end operation optimization method of air-cooled units is proposed based on the historical operation data of units and combined with data mining and deep learning algorithm. Firstly, the obtained historical operation data are screened in steady state and divided into working conditions. Combined with the Gaussian mixture model algorithm, the back pressure reference interval of the unit under multiple working conditions is determined. Then, the Spearman coefficient method is used to select the characteristic variables, and the back pressure prediction model of the direct air cooling unit is constructed in combination with the gated circulation unit. The back pressure optimization suggestions and early warning information are given by comparing the back pressure reference interval with the back pressure prediction value. Finally, the method is applied to a subcritical 300 MW air-cooled condensing steam unit. The results show that the back pressure optimization method proposed in this paper can give effective back pressure early warning information and realize optimal operation of cold end of the air-cooled unit.

During signal sampling process of steam turbine digital electric hydraulic control system (DEH) tests, situations that the instrument can not meet the requirements of Nyquist sampling due to the frequency of the primary components is over high may occur. To solve this problem, the envelope of the signal is calculated through Hilbert transform, and the valve closing time is calculated according to the envelope signal. However, the calculation accuracy is limited due to the time interval of the peak points. To improve the calculation accuracy, the undersampled signal is reconstructed, the primary frequency is analyzed by using fast Fourie transform (FFT), and the primary frequency of the signal is determined based on the nature of the frequency domain. On this basis, the initial phase of the AC signals is calculated using the initial value, and the undersampled signals is reconstructed according to the frequency and initial phase. The closing time is calculated according to the difference between the reconstructed and sampled signals based on Akaike information criterion (AIC). In comparison with the Hilbert transform method, the reconstruction method can improve the calculation accuracy. The reconstruction and analysis method can be used in all kinds of undersampled periodic signals, which can make up the shortcomings of hardware in DEH tests.

Frequency conversion condensate pump is easy to produce structural resonance because of insufficient support stiffness of vertical structure and increased working frequency range. According to the problem of excessive vibration in two resonance zones of a 350 MW vertical variable-frequency condensate pump, this paper introduces the principle and influencing factors of structural resonance, the judgment method of vibration fault and the treatment process. Theoretical calculation and actual treatment results show that, when there is unbalance on the shafting, dynamic balancing can effectively reduce the vibration amplitude in the resonance area of the condensate pump. However, when there are multiple resonance zones at the same time and the counterweight schemes corresponding to different resonance zones are contradictory, the dynamic balance mode cannot be considered at the same time. The angle of the counterweight determines the dynamic balance effect. Due to the limitation of the reserved counterweight angle, the rapid change of the vibration phase near the resonance point, inaccurate measurement and other factors, it is difficult to achieve on-site fine dynamic balance. Increasing the support to improve the system stiffness can change the natural frequency of the structure and reduce the vibration amplitude in the resonance area, which is an effective measure to solve the resonance problem. The vibration reduction effect of radial support is better than that of axial support.

The effects of different heat transfer fluid (HTF) parameters on charging and mechanical performance of the thermal energy storage (TES) tank using phase change material (PCM) capsules are studied by employing the fluid-solid coupling calculation. The results show that, with the inlet HTF flow velocity increased from 0.000 7 m/s to 0.000 9 m/s, the total heat storage quantity is basically unchanged, the average charging power increases from 5.33 MW to 6.79 MW, and the peak maximum mechanical stress (MMS) of the tank wall decreases. When the initial cold HTF temperature decreases from 610 K to 530 K, the total heat storage quantity increases, the average charging power increases from 5.29 MW to 6.81 MW, but the peak MMS of the tank wall also increases. With the initial hot HTF temperature increases from 730 K to 810 K, the total heat storage quantity increases obviously, the average charging power increases from 3.81 MW to 7.97 MW, but the peak MMS also increases to 159.6 MPa. Hence, to improve the charging performance of the TES tank, on the premise of ensuring the structural safety of steel wall of the TES tank, the inlet HTF flow velocity and initial hot HTF temperature should be increased properly, and the initial cold HTF temperature should be reduced properly.

The operating parameters of coal mills directly affect the safety and combustion performance of coal-fired units. Therefore, it is of great significance to carry out real-time monitoring of CO volume fraction at the outlet of coal mills and accordingly have safety early warning based on the monitored data. In this work, the measurement accuracy and detection limit of wavelength modulation direct absorption spectroscopy(WM-DAS) method were verified based on tunable diode laser absorption spectroscopy(TDLAS) and Herriott multi-pass cell. The experimental results showed that the measured CO volume fraction agree very well with the preset values in the range of 1 to 10 μL/L, and the detection limit can be as low as 5.2×10^–3 μL/L(300 s), which suggests the extremely high measurement sensitivity and accuracy of this method. Subsequently, based on this prototype experiment, an on-line monitoring system for the trace CO volume fraction was developed. Then, combined with the high-fidelity pretreatment technology of fuel gas based on the principle of constant-flow dilution, an on-line monitoring system for trace CO volume fraction was developed and applied to the outlet of coal mill of thermal power unit. The on-line CO monitoring and safety warning at the outlet of 5 coal mills of a single thermal power unit were realized by using multi-point alternating measurement strategy. With the monitored CO volume fraction and temperature of the coal mill outlet, the temperature of the primary air is adjusted to improve the boiler efficiency while ensuring safe operation of coal mill.

In order to improve the cooling performance of cooling tower, this study takes a 300 MW unit cooling tower in the north as an example, establishes a 3D numerical calculation model of cooling tower, compares the effect of non-equal packing in two and three zones on the outlet tower water temperature, determines the optimal radius dividing point, and cooperates with non-uniform water distribution for optimization, analyzes the effect of different optimization schemes on the air flow rate, tower water temperature and ventilation volume in the outlet tower. The results show that the cooling performance is improved with the exit tower water temperature of 31.798 ℃and 31.696 ℃ under the non-equally spaced packing in the second and third divisions, respectively. The coupling optimization of non-equally spaced packing with non-uniform water distribution significantly improves the uniformity of aerodynamic and temperature fields. With the increase of water distribution in the inner zone, the outlet water temperature and ventilation volume both show a trend of first increase and then decrease, and the optimal water distribution in the inner zone is 50%, and the outlet tower water temperature is 31.36 ℃ and ventilation volume is 7 122.8 kg/s. Compared with 26 mm and 30 mm equidistant packing arrangement, after collaborative optimization, the water temperature of the tower is reduced by 0.768 ℃ and 0.83 ℃, respectively, and the cooling performance is significantly improved.

Turbine cooling system is one of the cores of modern heavy-duty gas turbines. How to consider the influence of cold gas admixture is one of the first problems to be solved in gas turbine thermodynamic modeling and analysis of the influence of key parameters. With the continuous deepening of overall design of the gas turbine, a more detailed thermal performance calculation model is required to coordinate and match key components and the whole and ensure the final realization of the design performance. A calculation method of step-by-step blending and overall thermal performance of gas turbine based on one-dimensional aerodynamic analysis of turbine is proposed, and a thermal performance model of heavy-duty gas turbine is established. Moreover, the influence and key parameters and thermodynamic performance scheme of G/H class gas turbine is investigated. The analysis shows that, the turbine initial temperature, pressure ratio and cooling air volume are the key parameters affecting the overall thermal performance of the gas turbine, and the three should be coordinated in the overall design. While improving the turbine initial temperature, the minimum cooling air amount required to reach the temperature level should be studied, the optimal pressure ratio should be analyzed, and the iterative calculation and thorough research should be confirmed after combining the component design. The research results can provide a reference for the overall performance design of autonomous heavy-duty gas turbines.

At present, the self-provided power plant has a large generating power, which can not be ignored in the future new energy grid-connected peak regulation. According to the selected factory-owned power plant with power and heat supply, there are the low-pressure cylinder zero output scheme, high back pressure extraction combined exhaust steam heating scheme, absorption heat pump and compression heat pump scheme. four thermo-electrolytic coupling schemes are quantitatively calculated and evaluated to provide guidance for the selection of decoupling schemes for factory-owned power plants. Four schemes were used to optimize the case unit, and the calculation results showed that after decoupling, the heat supply of the heating extraction stage can be separately increase 174.00 MW, 136.18 MW, 168.37 MW and 38.00 MW. The minimum electric load rate was reduced to 44.29%, 73.29%, 73.70% and 80.57%. The maximum heat-to-electricity ratio reached 2.00, 1.50, 1.50 and 1.15. The zero-output decoupling effect of the low-pressure cylinder is the most obvious, the maximum heat supply increases the most, and the electric load rate decreases the most. Economic analysis shows that the absorption heat pump scheme has the most increased investment cost compared to other schemes.

In order to avoid disrepair and overrepair, improve the reliability and availability of gas turbine, reduce operation and maintenance cost, and ensure its safe, stable, green and efficient operation, a novel approach is proposed for fault diagnosis of gas turbine in power plants under transient operating condition with variable geometry compressor. The mathematical relationship of the influence of the compressor inlet guide vane position on compressor flow and efficiency characteristics is deduced. A high-precision thermodynamic model for the purpose of performance analysis and gas-path fault diagnosis is established. Moreover, the gas path fault diagnosis strategy of power plant gas turbine, which is suitable for transient and variable conditions and includes variable geometry, is proposed. Through actual operation test, it is verified that the proposed method has high diagnostic accuracy and good real-time performance, and the fault identification under transient and variable conditions is realized.

As the proportion of new energy power generation continues to increase, the stability of grid frequency is severely challenged, and the role of conventional thermal power units in grid frequency regulation has become increasingly prominent. However, the adjustment rate and accuracy of some thermal power units are difficult to meet the demand of grid load fluctuations. Therefore, a response performance optimization strategy for flywheel-thermal power system automatic generation control based on load forecasting was proposed. Firstly, the load is predicted, using the tree-based pipeline optimization tool TPOT library to automatically machine learning to match and train the load regression prediction model, and the automatic generation control day-ahead planned value is introduced into the training data to reduce the prediction error. Then, according to the load prediction value and the current flywheel system, with the optimization goal of minimizing the regulation rate of thermal power units, the flywheel energy storage system is acted firstly in load distribution, and the state of charge of the flywheel is adjusted meanwhile. Finally, a simulation experiment is carried out based on the actual operation data of a power plant in Hubei, and the experimental results prove that the proposed method can effectively improve the frequency modulation performance of thermal power units.