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Optimum exploitation of an integrated energy system considering renewable sources and power-heat system and energy storage

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Listed:
  • Hou, Rui
  • Deng, Guangzhi
  • Wu, Minrong
  • Wang, Wei
  • Gao, Wei
  • Chen, Kang
  • Liu, Lijun
  • Dehan, Sim

Abstract

The increasing population and energy consumption have led to a greater emphasis on managing and storing different energy sources. Researchers are now focusing on integrating renewable energy into energy systems and improving efficiency through accurate modeling and calculations. This article presents the optimal operation of an integrated energy system that incorporates wind energy as a renewable source. The study focuses on enhancing the modeling accuracy of equipment such as combined heat and power units and storage devices to align the obtained results with real-world scenarios. To effectively manage electrical and thermal loads, a load management program is implemented. Furthermore, the uncertainty of wind speed is addressed using the interval-valued grey decision Theory method. Two sensitivity analyses are conducted to further investigate the system's performance. Firstly, the impact of incorporating storage resources and load management programs on the overall operating cost is examined. The results demonstrate a significant 22.87% improvement in the objective function when both storage devices and load management programs are employed simultaneously. Secondly, a sensitivity analysis is performed to evaluate the objective function's response to changes in the uncertainty budget parameters and wind speed deviation. The findings highlight the greater impact of wind speed deviation on the objective function compared to changes in the uncertainty budget. The problem is formulated as a mixed integer linear programming problem, and the GAMS software and CPLEX solver are utilized to obtain the relevant results. The findings emphasize the potential of integrating wind energy into an integrated energy system and underscore the importance of accurate modeling, load management, and the consideration of storage resources. These insights contribute to the optimization of energy system operations and the advancement of sustainable energy practices.

Suggested Citation

  • Hou, Rui & Deng, Guangzhi & Wu, Minrong & Wang, Wei & Gao, Wei & Chen, Kang & Liu, Lijun & Dehan, Sim, 2023. "Optimum exploitation of an integrated energy system considering renewable sources and power-heat system and energy storage," Energy, Elsevier, vol. 282(C).
    • Handle: RePEc:eee:energy:v:282:y:2023:i:c:s0360544223017760
    DOI: 10.1016/j.energy.2023.128382
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    References listed on IDEAS

    as
    1. Zhu, Yilin & Xu, Yujie & Chen, Haisheng & Guo, Huan & Zhang, Hualiang & Zhou, Xuezhi & Shen, Haotian, 2023. "Optimal dispatch of a novel integrated energy system combined with multi-output organic Rankine cycle and hybrid energy storage," Applied Energy, Elsevier, vol. 343(C).
    2. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Optimal design of multi-energy systems with seasonal storage," Applied Energy, Elsevier, vol. 219(C), pages 408-424.
    3. Fabrizio, Enrico & Corrado, Vincenzo & Filippi, Marco, 2010. "A model to design and optimize multi-energy systems in buildings at the design concept stage," Renewable Energy, Elsevier, vol. 35(3), pages 644-655.
    4. Wang, Yong & Li, Lin, 2013. "Time-of-use based electricity demand response for sustainable manufacturing systems," Energy, Elsevier, vol. 63(C), pages 233-244.
    5. Baziar, Aliasghar & Kavousi-Fard, Abdollah, 2013. "Considering uncertainty in the optimal energy management of renewable micro-grids including storage devices," Renewable Energy, Elsevier, vol. 59(C), pages 158-166.
    6. Ma, Tengfei & Wu, Junyong & Hao, Liangliang & Lee, Wei-Jen & Yan, Huaguang & Li, Dezhi, 2018. "The optimal structure planning and energy management strategies of smart multi energy systems," Energy, Elsevier, vol. 160(C), pages 122-141.
    7. Chen, Maozhi & Lu, Hao & Chang, Xiqiang & Liao, Haiyan, 2023. "An optimization on an integrated energy system of combined heat and power, carbon capture system and power to gas by considering flexible load," Energy, Elsevier, vol. 273(C).
    8. Wang, Liying & Lin, Jialin & Dong, Houqi & Wang, Yuqing & Zeng, Ming, 2023. "Demand response comprehensive incentive mechanism-based multi-time scale optimization scheduling for park integrated energy system," Energy, Elsevier, vol. 270(C).
    9. Mahyar Lasemi Imeni & Mohammad Sadegh Ghazizadeh & Mohammad Ali Lasemi & Zhenyu Yang, 2023. "Optimal Scheduling of a Hydrogen-Based Energy Hub Considering a Stochastic Multi-Attribute Decision-Making Approach," Energies, MDPI, vol. 16(2), pages 1-23, January.
    10. Ricardo Bessa & Carlos Moreira & Bernardo Silva & Manuel Matos, 2014. "Handling renewable energy variability and uncertainty in power systems operation," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 3(2), pages 156-178, March.
    11. Soroudi, Alireza & Amraee, Turaj, 2013. "Decision making under uncertainty in energy systems: State of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 376-384.
    12. Zatti, Matteo & Gabba, Marco & Freschini, Marco & Rossi, Michele & Gambarotta, Agostino & Morini, Mirko & Martelli, Emanuele, 2019. "k-MILP: A novel clustering approach to select typical and extreme days for multi-energy systems design optimization," Energy, Elsevier, vol. 181(C), pages 1051-1063.
    13. Li, Y.P. & Huang, G.H. & Chen, X., 2011. "Planning regional energy system in association with greenhouse gas mitigation under uncertainty," Applied Energy, Elsevier, vol. 88(3), pages 599-611, March.
    14. Chi, Lixun & Su, Huai & Zio, Enrico & Qadrdan, Meysam & Zhou, Jing & Zhang, Li & Fan, Lin & Yang, Zhaoming & Xie, Fei & Zuo, Lili & Zhang, Jinjun, 2023. "A systematic framework for the assessment of the reliability of energy supply in Integrated Energy Systems based on a quasi-steady-state model," Energy, Elsevier, vol. 263(PB).
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