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Multistage Economic Scheduling Model of Micro-Energy Grids Considering Flexible Capacity Allocation

Author

Listed:
  • Hang Liu

    (School of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou 450046, China)

  • Yongcheng Wang

    (School of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou 450046, China)

  • Shilin Nie

    (Zhangshu Development and Reform Commission, Zhangshu 331200, China)

  • Yi Wang

    (School of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou 450046, China)

  • Yu Chen

    (School of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou 450046, China)

Abstract

Micro-energy grids integrating multiple energy sources can realize the efficient use of renewable energy and accelerate the process of energy transition. However, due to the uncertainty of renewable energy, the stability and security of system operations should be taken into account with respect to multi-energy coupling economic operations. Thus, it is essential to make flexible capacity allocations in advance of the actual scheduling of production in the micro-energy grid. With this motivation, this paper constructs a three-stage scheduling model corresponding to the running stage of the spot market. Specifically, the capacity of flexible, active devices is configured in the day-ahead stage; then, the intraday economic operation dispatching scheme is provided according to the capacity configuration. Based on the day-ahead and intraday optimization results, the system power balance is realized through the dispatching process using the reserve capacity of flexible active devices for deviations generated in the real-time stage of renewable energy. For the uncertainty of renewable energy output, the clustering method is applied to realize the clustering analysis of renewable energy output scenarios. In addition, the conditional value at risk (CVaR) theory is introduced to modify the three-stage stochastic optimization model, and the risk values caused by uncertainty are quantitatively evaluated. Finally, we simulate a practical case to verify the effectiveness of the proposed model. The results show that day-ahead flexible capacity allocation enhances the autonomy of the micro-energy grid system, ensures a certain degree of system operational security, and reduces balancing costs in the real-time stage. The higher the risk aversion factor, the more operational costs the system operator pays to avoid the risk. In addition, if the carbon penalty coefficient is higher, the overall carbon emission level of the micro-energy grid will decrease, but it will gradually converge to a minimal level. This paper guides the development of micro-energy grids and has important constructional significance for the construction of multi-energy collaborative mechanisms.

Suggested Citation

  • Hang Liu & Yongcheng Wang & Shilin Nie & Yi Wang & Yu Chen, 2022. "Multistage Economic Scheduling Model of Micro-Energy Grids Considering Flexible Capacity Allocation," Sustainability, MDPI, vol. 14(15), pages 1-29, July.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9013-:d:869349
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    References listed on IDEAS

    as
    1. Wang, Yongli & Wang, Yudong & Huang, Yujing & Li, Fang & Zeng, Ming & Li, Jiapu & Wang, Xiaohai & Zhang, Fuwei, 2019. "Planning and operation method of the regional integrated energy system considering economy and environment," Energy, Elsevier, vol. 171(C), pages 731-750.
    2. Xin Zhang & Jianhua Yang & Weizhou Wang & Man Zhang & Tianjun Jing, 2018. "Integrated Optimal Dispatch of a Rural Micro-Energy-Grid with Multi-Energy Stream Based on Model Predictive Control," Energies, MDPI, vol. 11(12), pages 1-23, December.
    3. Wang, Haichao & Yin, Wusong & Abdollahi, Elnaz & Lahdelma, Risto & Jiao, Wenling, 2015. "Modelling and optimization of CHP based district heating system with renewable energy production and energy storage," Applied Energy, Elsevier, vol. 159(C), pages 401-421.
    4. Younès Dagdougui & Ahmed Ouammi & Rachid Benchrifa, 2020. "Energy Management-Based Predictive Controller for a Smart Building Powered by Renewable Energy," Sustainability, MDPI, vol. 12(10), pages 1-18, May.
    5. Li, Yanbin & Zhang, Feng & Li, Yun & Wang, Yuwei, 2021. "An improved two-stage robust optimization model for CCHP-P2G microgrid system considering multi-energy operation under wind power outputs uncertainties," Energy, Elsevier, vol. 223(C).
    6. Aboelsood Zidan & Hossam A. Gabbar, 2016. "DG Mix and Energy Storage Units for Optimal Planning of Self-Sufficient Micro Energy Grids," Energies, MDPI, vol. 9(8), pages 1-18, August.
    7. Jun Dong & Peiwen Yang & Shilin Nie, 2019. "Day-Ahead Scheduling Model of the Distributed Small Hydro-Wind-Energy Storage Power System Based on Two-Stage Stochastic Robust Optimization," Sustainability, MDPI, vol. 11(10), pages 1-27, May.
    8. Amiri, S. & Honarvar, M. & sadegheih, A., 2018. "Providing an integrated Model for Planning and Scheduling Energy Hubs and preventive maintenance," Energy, Elsevier, vol. 163(C), pages 1093-1114.
    9. Ihsan Ullah & Muhammad Babar Rasheed & Thamer Alquthami & Shahzadi Tayyaba, 2019. "A Residential Load Scheduling with the Integration of On-Site PV and Energy Storage Systems in Micro-Grid," Sustainability, MDPI, vol. 12(1), pages 1-36, December.
    10. Shariatkhah, Mohammad-Hossein & Haghifam, Mahmoud-Reza & Chicco, Gianfranco & Parsa-Moghaddam, Mohsen, 2016. "Adequacy modeling and evaluation of multi-carrier energy systems to supply energy services from different infrastructures," Energy, Elsevier, vol. 109(C), pages 1095-1106.
    11. Qiu, Jing & Zhao, Junhua & Yang, Hongming & Wang, Dongxiao & Dong, Zhao Yang, 2018. "Planning of solar photovoltaics, battery energy storage system and gas micro turbine for coupled micro energy grids," Applied Energy, Elsevier, vol. 219(C), pages 361-369.
    12. Jun Dong & Yaoyu Zhang & Yuanyuan Wang & Yao Liu, 2021. "A Two-Stage Optimal Dispatching Model for Micro Energy Grid Considering the Dual Goals of Economy and Environmental Protection under CVaR," Sustainability, MDPI, vol. 13(18), pages 1-28, September.
    13. Wang, Yuwei & Tang, Liu & Yang, Yuanjuan & Sun, Wei & Zhao, Huiru, 2020. "A stochastic-robust coordinated optimization model for CCHP micro-grid considering multi-energy operation and power trading with electricity markets under uncertainties," Energy, Elsevier, vol. 198(C).
    14. Wang, Jianhui & Liu, Cong & Ton, Dan & Zhou, Yan & Kim, Jinho & Vyas, Anantray, 2011. "Impact of plug-in hybrid electric vehicles on power systems with demand response and wind power," Energy Policy, Elsevier, vol. 39(7), pages 4016-4021, July.
    15. An, Su & Wang, Honglei & Leng, Xiaoxia, 2022. "Optimal operation of multi-micro energy grids under distribution network in Southwest China," Applied Energy, Elsevier, vol. 309(C).
    16. Ju, Liwei & Tan, Qinliang & Lin, Hongyu & Mei, Shufang & Li, Nan & Lu, Yan & Wang, Yao, 2020. "A two-stage optimal coordinated scheduling strategy for micro energy grid integrating intermittent renewable energy sources considering multi-energy flexible conversion," Energy, Elsevier, vol. 196(C).
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    1. Lucio Laureti & Alessandro Massaro & Alberto Costantiello & Angelo Leogrande, 2023. "The Impact of Renewable Electricity Output on Sustainability in the Context of Circular Economy: A Global Perspective," Sustainability, MDPI, vol. 15(3), pages 1-29, January.

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