IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v190y2017icp222-231.html
   My bibliography  Save this article

Analysis of energy and control efficiencies of fuzzy logic and artificial neural network technologies in the heating energy supply system responding to the changes of user demands

Author

Listed:
  • Ahn, Jonghoon
  • Cho, Soolyeon
  • Chung, Dae Hun

Abstract

This paper presents hybrid control approaches for heating air supply in response to changes in demand by using the Fuzzy Inference System (FIS) and Artificial Neural Network (ANN) fitting models.

Suggested Citation

  • Ahn, Jonghoon & Cho, Soolyeon & Chung, Dae Hun, 2017. "Analysis of energy and control efficiencies of fuzzy logic and artificial neural network technologies in the heating energy supply system responding to the changes of user demands," Applied Energy, Elsevier, vol. 190(C), pages 222-231.
  • Handle: RePEc:eee:appene:v:190:y:2017:i:c:p:222-231
    DOI: 10.1016/j.apenergy.2016.12.155
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261916319353
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2016.12.155?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bianchini, Gianni & Casini, Marco & Vicino, Antonio & Zarrilli, Donato, 2016. "Demand-response in building heating systems: A Model Predictive Control approach," Applied Energy, Elsevier, vol. 168(C), pages 159-170.
    2. Yang, L. & Entchev, E., 2014. "Performance prediction of a hybrid microgeneration system using Adaptive Neuro-Fuzzy Inference System (ANFIS) technique," Applied Energy, Elsevier, vol. 134(C), pages 197-203.
    3. Li, Zhengqi & Liu, Guangkui & Zhu, Qunyi & Chen, Zhichao & Ren, Feng, 2011. "Combustion and NOx emission characteristics of a retrofitted down-fired 660Â MWe utility boiler at different loads," Applied Energy, Elsevier, vol. 88(7), pages 2400-2406, July.
    4. Široký, Jan & Oldewurtel, Frauke & Cigler, Jiří & Prívara, Samuel, 2011. "Experimental analysis of model predictive control for an energy efficient building heating system," Applied Energy, Elsevier, vol. 88(9), pages 3079-3087.
    5. Farzan, Farbod & Jafari, Mohsen A. & Gong, Jie & Farzan, Farnaz & Stryker, Andrew, 2015. "A multi-scale adaptive model of residential energy demand," Applied Energy, Elsevier, vol. 150(C), pages 258-273.
    6. Hepbasli, Arif, 2011. "A comparative investigation of various greenhouse heating options using exergy analysis method," Applied Energy, Elsevier, vol. 88(12), pages 4411-4423.
    7. Dounis, A. I. & Manolakis, D. E., 2001. "Design of a fuzzy system for living space thermal-comfort regulation," Applied Energy, Elsevier, vol. 69(2), pages 119-144, June.
    8. Gustafsson, Jonas & Delsing, Jerker & van Deventer, Jan, 2010. "Improved district heating substation efficiency with a new control strategy," Applied Energy, Elsevier, vol. 87(6), pages 1996-2004, June.
    9. Tanton, D. M. & Cohen, R. R. & Probert, S. D., 1987. "Improving the effectiveness of a domestic central-heating boiler by the use of heat storage," Applied Energy, Elsevier, vol. 27(1), pages 53-82.
    10. Blarke, Morten B., 2012. "Towards an intermittency-friendly energy system: Comparing electric boilers and heat pumps in distributed cogeneration," Applied Energy, Elsevier, vol. 91(1), pages 349-365.
    11. Fang, Jinghua & Li, Guanghai & Aunan, Kristin & Vennemo, Haakon & Seip, Hans M. & Oye, Kenneth A. & Beér, János M., 2002. "A proposed industrial-boiler efficiency program in Shanxi: potential CO2-mitigation, health benefits and associated costs," Applied Energy, Elsevier, vol. 71(4), pages 275-285, April.
    12. Kensby, Johan & Trüschel, Anders & Dalenbäck, Jan-Olof, 2015. "Potential of residential buildings as thermal energy storage in district heating systems – Results from a pilot test," Applied Energy, Elsevier, vol. 137(C), pages 773-781.
    13. Kalogirou, Soteris A., 2000. "Applications of artificial neural-networks for energy systems," Applied Energy, Elsevier, vol. 67(1-2), pages 17-35, September.
    14. Lundström, Lukas & Wallin, Fredrik, 2016. "Heat demand profiles of energy conservation measures in buildings and their impact on a district heating system," Applied Energy, Elsevier, vol. 161(C), pages 290-299.
    15. Brand, Lisa & Calvén, Alexandra & Englund, Jessica & Landersjö, Henrik & Lauenburg, Patrick, 2014. "Smart district heating networks – A simulation study of prosumers’ impact on technical parameters in distribution networks," Applied Energy, Elsevier, vol. 129(C), pages 39-48.
    16. Seijo, Sandra & del Campo, Inés & Echanobe, Javier & García-Sedano, Javier, 2016. "Modeling and multi-objective optimization of a complex CHP process," Applied Energy, Elsevier, vol. 161(C), pages 309-319.
    17. Chelemuge, & Namioka, Tomoaki & Yoshikawa, Kunio & Takeshita, Masanori & Fujiwara, Koichi, 2012. "Commercial-scale demonstration of pollutant emission reduction and energy saving for industrial boilers by employing water/oil emulsified fuel," Applied Energy, Elsevier, vol. 93(C), pages 517-522.
    18. Gruber, Mattias & Trüschel, Anders & Dalenbäck, Jan-Olof, 2015. "Energy efficient climate control in office buildings without giving up implementability," Applied Energy, Elsevier, vol. 154(C), pages 934-943.
    19. Maheshwari, G.P. & Al-Hadban, Y., 2001. "Energy-efficient operation strategy for industrial boilers," Energy, Elsevier, vol. 26(1), pages 91-99.
    20. Fang, Jinghua & Zeng, Taofang & Yang, Lynn I. Shen & Oye, Kenneth A. & Sarofim, Adel F. & Beér, János M., 1999. "Coal utilization in industrial boilers in China --a prospect for mitigating CO2 emissions," Applied Energy, Elsevier, vol. 63(1), pages 35-52, May.
    21. Dounis, A.I. & Caraiscos, C., 2009. "Advanced control systems engineering for energy and comfort management in a building environment--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1246-1261, August.
    22. Holmgren, Kristina, 2006. "Role of a district-heating network as a user of waste-heat supply from various sources - the case of Göteborg," Applied Energy, Elsevier, vol. 83(12), pages 1351-1367, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jonghoon Ahn, 2020. "Performance Analyses of Temperature Controls by a Network-Based Learning Controller for an Indoor Space in a Cold Area," Sustainability, MDPI, vol. 12(20), pages 1-17, October.
    2. Zhang, Le & Zhu, Jizhong & Zhang, Di & Liu, Yun, 2023. "An incremental photovoltaic power prediction method considering concept drift and privacy protection," Applied Energy, Elsevier, vol. 351(C).
    3. Abhinandana Boodi & Karim Beddiar & Malek Benamour & Yassine Amirat & Mohamed Benbouzid, 2018. "Intelligent Systems for Building Energy and Occupant Comfort Optimization: A State of the Art Review and Recommendations," Energies, MDPI, vol. 11(10), pages 1-26, September.
    4. Sahraei, Mohammad Ali & Duman, Hakan & Çodur, Muhammed Yasin & Eyduran, Ecevit, 2021. "Prediction of transportation energy demand: Multivariate Adaptive Regression Splines," Energy, Elsevier, vol. 224(C).
    5. Mahmoud Abdelkader Bashery Abbass & Mohamed Hamdy, 2021. "A Generic Pipeline for Machine Learning Users in Energy and Buildings Domain," Energies, MDPI, vol. 14(17), pages 1-30, August.
    6. Ahmad Esmaeilzadeh & Brian Deal & Aghil Yousefi-Koma & Mohammad Reza Zakerzadeh, 2022. "How Multi-Criterion Optimized Control Methods Improve Effectiveness of Multi-Zone Building Heating System Upgrading," Energies, MDPI, vol. 15(22), pages 1-27, November.
    7. Ahn, Jonghoon & Cho, Soolyeon, 2017. "Anti-logic or common sense that can hinder machine’s energy performance: Energy and comfort control models based on artificial intelligence responding to abnormal indoor environments," Applied Energy, Elsevier, vol. 204(C), pages 117-130.
    8. Mpho J. Lencwe & SP Daniel Chowdhury & Sipho Mahlangu & Maxwell Sibanyoni & Louwrance Ngoma, 2021. "An Efficient HVAC Network Control for Safety Enhancement of a Typical Uninterrupted Power Supply Battery Storage Room," Energies, MDPI, vol. 14(16), pages 1-23, August.
    9. Sung Hoon Yoon & Jonghoon Ahn, 2020. "Comparative Analysis of Energy Use and Human Comfort by an Intelligent Control Model at the Change of Season," Energies, MDPI, vol. 13(22), pages 1-15, November.
    10. Jonghoon Ahn, 2021. "Abatement of the Increases in Cooling Energy Use during a Period of Intense Heat by a Network-Based Adaptive Controller," Sustainability, MDPI, vol. 13(3), pages 1-17, January.
    11. Zhi Li & Yuemeng Ge & Jieying Guo & Mengyao Chen & Junwei Wang, 2022. "Security threat model under internet of things using deep learning and edge analysis of cyberspace governance," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(3), pages 1164-1176, December.
    12. Zheng, Xuyue & Wu, Guoce & Qiu, Yuwei & Zhan, Xiangyan & Shah, Nilay & Li, Ning & Zhao, Yingru, 2018. "A MINLP multi-objective optimization model for operational planning of a case study CCHP system in urban China," Applied Energy, Elsevier, vol. 210(C), pages 1126-1140.
    13. Elahi, Ehsan & Khalid, Zainab, 2022. "Estimating smart energy inputs packages using hybrid optimisation technique to mitigate environmental emissions of commercial fish farms," Applied Energy, Elsevier, vol. 326(C).
    14. Shunling Ruan & Haiyan Xie & Song Jiang, 2017. "Integrated Proactive Control Model for Energy Efficiency Processes in Facilities Management: Applying Dynamic Exponential Smoothing Optimization," Sustainability, MDPI, vol. 9(9), pages 1-22, September.
    15. Liang, Zheming & Bian, Desong & Zhang, Xiaohu & Shi, Di & Diao, Ruisheng & Wang, Zhiwei, 2019. "Optimal energy management for commercial buildings considering comprehensive comfort levels in a retail electricity market," Applied Energy, Elsevier, vol. 236(C), pages 916-926.
    16. Sana Iqbal & Mohammad Sarfraz & Mohammad Ayyub & Mohd Tariq & Ripon K. Chakrabortty & Michael J. Ryan & Basem Alamri, 2021. "A Comprehensive Review on Residential Demand Side Management Strategies in Smart Grid Environment," Sustainability, MDPI, vol. 13(13), pages 1-23, June.
    17. Jonghoon Ahn, 2020. "Improvement of the Performance Balance between Thermal Comfort and Energy Use for a Building Space in the Mid-Spring Season," Sustainability, MDPI, vol. 12(22), pages 1-14, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Antonio Martinez-Molina & Miltiadis Alamaniotis, 2020. "Enhancing Historic Building Performance with the Use of Fuzzy Inference System to Control the Electric Cooling System," Sustainability, MDPI, vol. 12(14), pages 1-14, July.
    2. Werner, Sven, 2017. "District heating and cooling in Sweden," Energy, Elsevier, vol. 126(C), pages 419-429.
    3. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    4. Yang, Lei & Nagy, Zoltan & Goffin, Philippe & Schlueter, Arno, 2015. "Reinforcement learning for optimal control of low exergy buildings," Applied Energy, Elsevier, vol. 156(C), pages 577-586.
    5. Barbeito, Inés & Zaragoza, Sonia & Tarrío-Saavedra, Javier & Naya, Salvador, 2017. "Assessing thermal comfort and energy efficiency in buildings by statistical quality control for autocorrelated data," Applied Energy, Elsevier, vol. 190(C), pages 1-17.
    6. Muhammad Fayaz & DoHyeun Kim, 2018. "Energy Consumption Optimization and User Comfort Management in Residential Buildings Using a Bat Algorithm and Fuzzy Logic," Energies, MDPI, vol. 11(1), pages 1-22, January.
    7. Muniak, Damian Piotr, 2014. "A new methodology to determine the pre-setting of the control valve in a heating installation. A general model," Applied Energy, Elsevier, vol. 135(C), pages 35-42.
    8. Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
    9. Tommy Rosén & Louise Ödlund, 2019. "Active Management of Heat Customers Towards Lower District Heating Return Water Temperature," Energies, MDPI, vol. 12(10), pages 1-20, May.
    10. Zheng, Jinfu & Zhou, Zhigang & Zhao, Jianing & Wang, Jinda, 2018. "Integrated heat and power dispatch truly utilizing thermal inertia of district heating network for wind power integration," Applied Energy, Elsevier, vol. 211(C), pages 865-874.
    11. Enescu, Diana, 2017. "A review of thermal comfort models and indicators for indoor environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1353-1379.
    12. Wang, Jinda & Zhou, Zhigang & Zhao, Jianing & Zheng, Jinfu, 2018. "Improving wind power integration by a novel short-term dispatch model based on free heat storage and exhaust heat recycling," Energy, Elsevier, vol. 160(C), pages 940-953.
    13. Wang, Zhu & Wang, Lingfeng & Dounis, Anastasios I. & Yang, Rui, 2012. "Multi-agent control system with information fusion based comfort model for smart buildings," Applied Energy, Elsevier, vol. 99(C), pages 247-254.
    14. Badami, Marco & Fonti, Antonio & Carpignano, Andrea & Grosso, Daniele, 2018. "Design of district heating networks through an integrated thermo-fluid dynamics and reliability modelling approach," Energy, Elsevier, vol. 144(C), pages 826-838.
    15. Azar, Elie & Nikolopoulou, Christina & Papadopoulos, Sokratis, 2016. "Integrating and optimizing metrics of sustainable building performance using human-focused agent-based modeling," Applied Energy, Elsevier, vol. 183(C), pages 926-937.
    16. Byung-Ki Jeon & Eui-Jong Kim, 2021. "LSTM-Based Model Predictive Control for Optimal Temperature Set-Point Planning," Sustainability, MDPI, vol. 13(2), pages 1-14, January.
    17. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    18. Sun, Jian & Fu, Lin & Sun, Fangtian & Zhang, Shigang, 2014. "Study on a heat recovery system for the thermal power plant utilizing air cooling island," Energy, Elsevier, vol. 74(C), pages 836-844.
    19. Zhang, Yang & Campana, Pietro Elia & Yang, Ying & Stridh, Bengt & Lundblad, Anders & Yan, Jinyue, 2018. "Energy flexibility from the consumer: Integrating local electricity and heat supplies in a building," Applied Energy, Elsevier, vol. 223(C), pages 430-442.
    20. Löhr, Yannik & Wolf, Daniel & Pollerberg, Clemens & Hörsting, Alexander & Mönnigmann, Martin, 2021. "Supervisory model predictive control for combined electrical and thermal supply with multiple sources and storages," Applied Energy, Elsevier, vol. 290(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:190:y:2017:i:c:p:222-231. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.