Soft Sensor of Heating Extraction Steam Flow Rate Based on Frequency Complementary Information Fusion for CHP Plant

Heating extraction steam (HEXTR) flow rate is the key parameter to determine the heat load of a combined heat and power (CHP) plant and the safe operation area of the steam turbine of CHP plant. Due to the difficulty of direct measurement, a soft measurement method of this flow rate is proposed. First, three calculation methods based on different principles are given: the Flugel formula of the steam turbine method, the butterfly valve flow characteristics method, and the improvement of heat balance characteristic of the turbine method. Then, a soft-sensing method through frequency complementary information fusion is proposed to combine the advantages of the three methods. The specific fusion algorithm uses Flugel formula of the turbine as a static model, the heat balance characteristic of the turbine to correct the coefficient in the model, and the butterfly valve characteristic to realize dynamic compensation. Finally, the proposed soft sensor is applied in the monitoring system of a typical 330 MW CHP plant. The actual operating data shows that the relative static measurement error of the soft sensor is less than 1% and the dynamic response is as fast as power load change.

[1]  Min Xie,et al.  Rebooting data-driven soft-sensors in process industries: A review of kernel methods , 2020 .

[2]  Liu Xin-ping Simplified Model and Characteristic Analysis of Load-Pressure Object in Heat Supply Units , 2012 .

[3]  Hui Li,et al.  Increasing the Flexibility of Combined Heat and Power for Wind Power Integration in China: Modeling and Implications , 2015, IEEE Transactions on Power Systems.

[4]  Sirkka-Liisa Jämsä-Jounela,et al.  Model predictive control utilizing fuel and moisture soft-sensors for the BioPower 5 combined heat and power (CHP) plant , 2014 .

[5]  Francesco Corona,et al.  Data-derived soft-sensors for biological wastewater treatment plants: An overview , 2013, Environ. Model. Softw..

[6]  Liu Xinpin A Control Method of Rapid Load Change for Heat Supply Units Compensating Wind Power Disturbance , 2014 .

[7]  Liu Jizhen A Guidance Differential Coordinated Control System Based on Air-Oxygen Heat Release Signals , 2011 .

[8]  G. Paul,et al.  Ultrasonic-Based Sensor Fusion Approach to Measure Flow Rate in Partially Filled Pipes , 2020, IEEE Sensors Journal.

[9]  Jialin Liu,et al.  Developing a soft sensor based on sparse partial least squares with variable selection , 2014 .

[10]  Xie Xie A Soft-sensor Method of Reheat Steam Flow Based on Simplified Heat-balance Equation , 2011 .

[11]  Xu Zhi-qiang A METHOD FOR FUSING RADIATION SIGNAL AND HEAT RELEASE SIGNAL INSIDE FURNACE , 2003 .

[12]  R. Hanus,et al.  Uncertainty of mass flow measurement using centric and eccentric orifice for Reynolds number in the range 10,000 ≤ Re ≤ 20,000 , 2020 .

[13]  S. Zarrouk,et al.  Comparative CFD modelling of pressure differential flow meters for measuring two-phase geothermal fluid flow , 2020 .

[14]  Shifei Zhao,et al.  Comparative study of flexibility enhancement technologies for the coal-fired combined heat and power plant , 2019, Energy Conversion and Management.

[15]  Xinping Liu,et al.  A Deep Peak Regulation Auxiliary Service Bidding Strategy for CHP Units Based on a Risk-Averse Model and District Heating Network Energy Storage , 2019, Energies.

[16]  Dawid Taler,et al.  The use of pressure hot water storage tanks to improve the energy flexibility of the steam power unit , 2019, Energy.

[17]  Deliang Zeng,et al.  Soft sensing of coal quality , 2015 .

[18]  Mingzhe Liu,et al.  A soft measurement approach of wastewater treatment process by lion swarm optimizer-based extreme learning machine , 2021, Measurement.

[19]  Brane Širok,et al.  Turbine flowmeter response to transitional flow regimes , 2018 .

[20]  Liu Xinpin Simplified Nonlinear Dynamic Model of Generating Load-Throttle Pressure-Extraction Pressure for Heating Units , 2014 .