Application of artificial neural network to exergy performance analysis of coal fired thermal power plant

被引:13
|
作者
Acir, Adem [1 ]
机构
[1] Gazi Univ, Fac Technol, Dept Energy Syst Engn, Ankara, Turkey
关键词
exergy; thermal power plant; ANN; artificial neural network; efficiency; ENERGY;
D O I
10.1504/IJEX.2013.054118
中图分类号
O414.1 [热力学];
学科分类号
摘要
This study presents an artificial neural network (ANN) model to predict the exergy efficiency in a thermal power plant. An ANN model based on back-propagation learning algorithm for prediction of exergy efficiency was developed. In the ANN model, the actual data set includes 27 values, of which 18 values were used for training the network and 9 values, were selected randomly to test the performance of the trained network. Three performance factors, namely, ambient temperature, condenser pressure and steam pressure were considered. ANN has been modelled by 'PHYTICA' software. This study showed that the ANN model is suitable to predict the values of the efficiency performance.
引用
收藏
页码:362 / 379
页数:18
相关论文
共 50 条
  • [1] Application of exergy and entransy concepts to analyses performance of coal fired thermal power plant: a case study
    Geete, Ankur
    [J]. INTERNATIONAL JOURNAL OF AMBIENT ENERGY, 2021, 42 (09) : 1032 - 1043
  • [2] Application of exergy and entransy concepts to analyses performance of coal fired thermal power plant: a case study
    [J]. Geete, Ankur (ankur_geete@yahoo.co.in), 1600, Taylor and Francis Ltd. (42):
  • [3] Energy and Exergy Analysis of a Coal Fired Power Plant
    Kumar, Sumeet
    Kumar, Dileep
    Memon, Rizwan Ahmed
    Wassan, Majid Ali
    Ali, Mir Skindar
    [J]. MEHRAN UNIVERSITY RESEARCH JOURNAL OF ENGINEERING AND TECHNOLOGY, 2018, 37 (04) : 611 - 624
  • [4] Prediction of power output of a coal-fired power plant by artificial neural network
    Smrekar, J.
    Pandit, D.
    Fast, M.
    Assadi, M.
    De, Sudipta
    [J]. NEURAL COMPUTING & APPLICATIONS, 2010, 19 (05): : 725 - 740
  • [5] Prediction of power output of a coal-fired power plant by artificial neural network
    J. Smrekar
    D. Pandit
    M. Fast
    M. Assadi
    Sudipta De
    [J]. Neural Computing and Applications, 2010, 19 : 725 - 740
  • [6] Exergy analysis of a coal-fired thermal power plant in Kangal District of Turkey
    Erzen, Sevgi
    Acar, Halil Ibrahim
    Pektezel, Oguzhan
    [J]. INTERNATIONAL JOURNAL OF EXERGY, 2022, 39 (03) : 262 - 279
  • [7] EXERGY DIAGNOSIS OF COAL FIRED COMBINED HEAT AND POWER PLANT WITH APPLICATION OF NEURAL AND REGRESSION MODELLING
    Stanek, Wojciech
    Budnik, Michal
    [J]. THERMAL SCIENCE, 2012, 16 (03): : 773 - 787
  • [8] Steady state modeling on energy and exergy analysis of a pulverized coal fired thermal power plant
    Pattanayak, Lalatendu
    Sahu, Jaya Narayan
    [J]. ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, 2015, 10 (06) : 876 - 884
  • [9] Energy, exergy, sustainability and environmental emission analysis of coal-fired thermal power plant
    Kumar, Vivek
    Saxena, Vinod Kumar
    Kumar, Rakesh
    Kumar, Shravan
    [J]. AIN SHAMS ENGINEERING JOURNAL, 2024, 15 (02)
  • [10] Modeling and analysis of optimal performance of a coal-fired power plant based on exergy evaluation
    Khaleel, Omar J.
    Ibrahim, Thamir Khalil
    Ismail, Firas Basim
    Al-Sammarraie, Ahmed T.
    bin Abu Hassan, Saiful Hasmady
    [J]. ENERGY REPORTS, 2022, 8 : 2179 - 2199