Weight Calculation and Operation Adjustment of Factors that Influence Boiler Efficiency

Abstract:

For the problem that factors influencing boiler efficiency are complex and have strong coupling, Firstly, artificial neural network was used to establish the model of boiler efficiency, sensitivity analysis based on the model was introduced to calculate the sensitivity coefficient ,which reflecting the weights of input parameters on output indicators. According to the orders of weights, the main factors were chosen to be paid more attention and adjusted. Secondly, considering the effects of power and ambient temperature, the target-value of parameters in various conditions were obtained based on fuzzy c-means clustering algorithm, and were introduced as accordance for operation adjustment . The boiler efficiency of 600MW coal-fired boiler in Tashan plant was studied, the results indicate that the method can improve the economy of boiler effectively, guide operators to improve the pertinence of operation adjustment and have a certain significance in making the direction of operation adjustment clear.

• Periodical: Applied Mechanics and Materials (Volume 723)
• Pages: 996-1002
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.723.996
• Online since: January 2015
• Authors: Fen Fen Gao*, Yu Jiong Gu, Ping Zhu, Lei Song
• Keywords: Boiler Efficiency, Fuzzy C-Means Clustering, Neural Network, Operation Adjustment, Sensitivity Analysis, Target-Value

References

[1] Yang Guoqi, Qu Xiang. Influence Actor of Boiler Efficiency & Its Improvement Measure in Power Plant[J]. Shaanxi Electric Power, 2009, 37(4): 24-27.

[2] XU Lefei, Li Shaohua, Meng Lixin. Online boiler efficiency measurement based on BP neural network[J]. Heilongjiang Electric Power, 2012, 34(1): 33-36.

[3] Wu Haiji, Zhang Lei, Xu Zhigao. Quantitative Analysis for Influence of Operation Oxygen on Boiler Efficiency[J]. Boiler Technology, 2009, 40(6): 17-20.

[4] Tashan Power co. ltd . Atlas of the Boiler Systerm[Z]. 2011-12-01.

[5] Reinschmidt K F. Neural networks：next step for simulation and control [J]．Power Engineering , 1991, 11: 41-45.

[6] Liu Zhengyu, Yang Junbin, Zhang Qing, et al. Estimation for SOC of lithium battery based on QPSO-BP neural network[J]. Journal of Electronic Measurement and Instrument, 2013, 27(3).

[7] Cai Yi, Xing Yan, Hu Dan, et al. On Sensitivity Analysis [J]. Journal of Beijing Normal University(Natural Science) , 2008, 44(1): 9-16.

[8] Qian Wenjiang, Li Tongchun, Ding Lin. Sensitivity Analysis of Reservoirs Seepage Discharge Based on Improved BP Network[J]. Journal of China Three Gorges University(Natural Sciences), 2012, 34 (6): 23-27.

[9] Wu Zhiqun, Wang Dinghui, Huang Tinghui, et al. Study on Calculation Method for Target Value of Boiler Operation Optimization in Thermal Power Plant[J]. Thermal Power Grneration, 2006, 35(9): 27-29.

[10] Kusiak A, Song Z. Clustering-based performance optimization of the boiler-turbine system[J]. IEEE Transactions on Energy Conversion , 2008, 23(2): 651-657.

DOI: 10.1109/tec.2007.914183

[11] WANG Ningling, Yang Yongping, Yang Zhiping. Energy-consumption Benchmark Diagnosis of Thermal Power Units Under Varying Operation Boundary[J]. Proceedings of the CSEE, 2013, (26): 1-7.