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Improvement of fuel sources and energy products flexibility in coal power plants via energy-cyber-physical-systems approach

Author

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  • Zhao, Haitao
  • Jiang, Peng
  • Chen, Zhe
  • Ezeh, Collins I.
  • Hong, Yuanda
  • Guo, Yishan
  • Zheng, Chenghang
  • Džapo, Hrvoje
  • Gao, Xiang
  • Wu, Tao

Abstract

The fluctuating energy requirement from time-varying demand changes require flexible power system to respond to the dynamic load balance. In certain scenarios, flexible power systems are necessary to provide high system efficiencies and increase the long-term economic benefits. Therefore, it is important to identify the relationship between energy requirement of a city and/or industrial zone with the dynamics of a flexible power system. In this paper, we evaluate the possible benefits of adopting the energy-cyber-physical-systems (e-CPSs) concept in realization of a flexible closed-loop control power system in case of coal-sewage sludge co-combustion. The case study performance analysis of flexibility, efficiency and economics (FEE) for a 356 MW coal-fired power plant was conducted by means of simulation in Aspen PLUS software. The analysis was based on a specific multifarious model of a dynamic power system with two energy sources and four energy products. The results confirmed that substantial advantages including a more flexible, efficient and economically viable system can be achieved by using e-CPSs based solution in different case scenarios. Moreover, following the analyzed data from the proposed case scenarios, a forecasting model for optimization of the power plant parameters based on the use of artificial neural network (ANN) was established. The results showed that ANN-based approach for predictive model is capable of modelling the complex process within an acceptable prediction accuracy. The study demonstrates that the proposed flexible closed-loop control power system based on e-CPSs concept is able to achieve higher efficiency and economic benefits compared to the traditional approaches.

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  • Zhao, Haitao & Jiang, Peng & Chen, Zhe & Ezeh, Collins I. & Hong, Yuanda & Guo, Yishan & Zheng, Chenghang & Džapo, Hrvoje & Gao, Xiang & Wu, Tao, 2019. "Improvement of fuel sources and energy products flexibility in coal power plants via energy-cyber-physical-systems approach," Applied Energy, Elsevier, vol. 254(C).
    • Handle: RePEc:eee:appene:v:254:y:2019:i:c:s0306261919312280
    DOI: 10.1016/j.apenergy.2019.113554
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    5. Ekata Kaushik & Vivek Prakash & Om Prakash Mahela & Baseem Khan & Almoataz Y. Abdelaziz & Junhee Hong & Zong Woo Geem, 2022. "Optimal Placement of Renewable Energy Generators Using Grid-Oriented Genetic Algorithm for Loss Reduction and Flexibility Improvement," Energies, MDPI, vol. 15(5), pages 1-20, March.
    6. Du, Dajun & Zhu, Minggao & Wu, Dakui & Li, Xue & Fei, Minrui & Hu, Yukun & Li, Kang, 2024. "Distributed security state estimation-based carbon emissions and economic cost analysis for cyber–physical power systems under hybrid attacks," Applied Energy, Elsevier, vol. 353(PA).
    7. Nowak, Grzegorz & Rusin, Andrzej & Łukowicz, Henryk & Tomala, Martyna, 2020. "Improving the power unit operation flexibility by the turbine start-up optimization," Energy, Elsevier, vol. 198(C).
    8. Maciej Dzikuć & Piotr Kuryło & Rafał Dudziak & Szymon Szufa & Maria Dzikuć & Karolina Godzisz, 2020. "Selected Aspects of Combustion Optimization of Coal in Power Plants," Energies, MDPI, vol. 13(9), pages 1-15, May.

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