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Genetic algorithms and non-intrusive energy management system based economic dispatch for cogeneration units

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  • Chang, Hsueh-Hsien

Abstract

By integrating neural networks (NNs) with turn-on transient energy analysis, this work attempts to recognize demand load, including the buyers’ load on the power systems and the internal load on the cogeneration systems, thereby increasing the recognition accuracy in a non-intrusive energy management (NIEM) system. Analysis results reveal that an NIEM system and a new method that is based on genetic algorithms (GA) can effectively manage energy demand in an optimal economic dispatch for cogeneration systems with multiple cogenerators, which generate power for buyers. Furthermore, the global optimum of economic dispatch under typical environmental and operating constraints of cogeneration systems is found using the proposed approach, which is based on genetic algorithms. Moreover, the use of the proposed GA-based method for economic dispatch can substantially reduce computational time, fuel cost, power cost and air pollution.

Suggested Citation

  • Chang, Hsueh-Hsien, 2011. "Genetic algorithms and non-intrusive energy management system based economic dispatch for cogeneration units," Energy, Elsevier, vol. 36(1), pages 181-190.
    • Handle: RePEc:eee:energy:v:36:y:2011:i:1:p:181-190
    DOI: 10.1016/j.energy.2010.10.054
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    References listed on IDEAS

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    1. Chang, Hsueh-Hsien & Yang, Hong-Tzer, 2009. "Applying a non-intrusive energy-management system to economic dispatch for a cogeneration system and power utility," Applied Energy, Elsevier, vol. 86(11), pages 2335-2343, November.
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    Cited by:

    1. Paweł Ziółkowski & Marta Drosińska-Komor & Jerzy Głuch & Łukasz Breńkacz, 2023. "Review of Methods for Diagnosing the Degradation Process in Power Units Cooperating with Renewable Energy Sources Using Artificial Intelligence," Energies, MDPI, vol. 16(17), pages 1-28, August.
    2. Cai, Jiejin & Li, Qiong & Li, Lixiang & Peng, Haipeng & Yang, Yixian, 2012. "A hybrid FCASO-SQP method for solving the economic dispatch problems with valve-point effects," Energy, Elsevier, vol. 38(1), pages 346-353.
    3. Whei-Min Lin & Chung-Yuen Yang & Chia-Sheng Tu & Hsi-Shan Huang & Ming-Tang Tsai, 2019. "The Optimal Energy Dispatch of Cogeneration Systems in a Liberty Market," Energies, MDPI, vol. 12(15), pages 1-15, July.
    4. de Athayde Costa e Silva, Marsil & Klein, Carlos Eduardo & Mariani, Viviana Cocco & dos Santos Coelho, Leandro, 2013. "Multiobjective scatter search approach with new combination scheme applied to solve environmental/economic dispatch problem," Energy, Elsevier, vol. 53(C), pages 14-21.
    5. Hsueh-Hsien Chang, 2012. "Non-Intrusive Demand Monitoring and Load Identification for Energy Management Systems Based on Transient Feature Analyses," Energies, MDPI, vol. 5(11), pages 1-21, November.
    6. Christos-Spyridon Karavas & Konstantinos Arvanitis & George Papadakis, 2017. "A Game Theory Approach to Multi-Agent Decentralized Energy Management of Autonomous Polygeneration Microgrids," Energies, MDPI, vol. 10(11), pages 1-22, November.
    7. Wu, Xin & Jiao, Dian & Liang, Kaixin & Han, Xiao, 2019. "A fast online load identification algorithm based on V-I characteristics of high-frequency data under user operational constraints," Energy, Elsevier, vol. 188(C).
    8. Moradi, Mohammad H. & Hajinazari, Mehdi & Jamasb, Shahriar & Paripour, Mahmoud, 2013. "An energy management system (EMS) strategy for combined heat and power (CHP) systems based on a hybrid optimization method employing fuzzy programming," Energy, Elsevier, vol. 49(C), pages 86-101.
    9. Hsueh-Hsien Chang & Nguyen Viet Linh, 2017. "Statistical Feature Extraction for Fault Locations in Nonintrusive Fault Detection of Low Voltage Distribution Systems," Energies, MDPI, vol. 10(5), pages 1-20, April.
    10. Cho, Woojin & Lee, Kwan-Soo, 2014. "A simple sizing method for combined heat and power units," Energy, Elsevier, vol. 65(C), pages 123-133.
    11. Parvizimosaed, M. & Farmani, F. & Monsef, H. & Rahimi-Kian, A., 2017. "A multi-stage Smart Energy Management System under multiple uncertainties: A data mining approach," Renewable Energy, Elsevier, vol. 102(PA), pages 178-189.
    12. Bhowmik, Chiranjib & Bhowmik, Sumit & Ray, Amitava & Pandey, Krishna Murari, 2017. "Optimal green energy planning for sustainable development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 796-813.
    13. Rastgou, Abdollah & Moshtagh, Jamal & Bahramara, Salah, 2018. "Improved harmony search algorithm for electrical distribution network expansion planning in the presence of distributed generators," Energy, Elsevier, vol. 151(C), pages 178-202.

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