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A new approach on quantification of flexibility index in multi-carrier energy systems towards optimally energy hub management

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  • Azimi, Maryam
  • Salami, Abolfazl

Abstract

Multi-carrier energy systems (MCESs) are identified as intermediate frameworks among different energy carriers aiming to optimally meet diverse energy demands. In this study, a novel robust-based flexibility evaluation method is proposed for MCESs to quantify the maximum potentiality of the energy hub to compensate for the maximum uncertainty. For this purpose, a singular flexibility index is first calculated via the definition of apposite corrective actions, including purchasing the supplementary input carriers and implementing the demand response programs (DRPs). Then, given various individual uncertainty sets, a new bi-level optimization framework is introduced to achieve the optimal and deterministic scheduling of MCESs in the upper-level and determining the largest uncertainty radiuses in the lower-level. The demonstrated method is formulated as a second-order cone programming and is solved through an iteration-based search algorithm. The presented structure is implemented for a sample energy hub to confirm its extensive capability to apply various flexible options as compared to the information gap decision theory (IGDT). The maximum uncertainty margin in the electrical load is averagely equal to 79% of the predicted demand. The proposed method could be also fruitful for the robust scheduling of the energy hub in a worst-case scenario while considering the maximum uncertainty.

Suggested Citation

  • Azimi, Maryam & Salami, Abolfazl, 2021. "A new approach on quantification of flexibility index in multi-carrier energy systems towards optimally energy hub management," Energy, Elsevier, vol. 232(C).
  • Handle: RePEc:eee:energy:v:232:y:2021:i:c:s0360544221012214
    DOI: 10.1016/j.energy.2021.120973
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    1. Abdin, Islam F. & Zio, Enrico, 2018. "An integrated framework for operational flexibility assessment in multi-period power system planning with renewable energy production," Applied Energy, Elsevier, vol. 222(C), pages 898-914.
    2. Alirezazadeh, Atefeh & Rashidinejad, Masoud & Abdollahi, Amir & Afzali, Peyman & Bakhshai, Alireza, 2020. "A new flexible model for generation scheduling in a smart grid," Energy, Elsevier, vol. 191(C).
    3. Ye, Liang-Cheng & Lin, Hai Xiang & Tukker, Arnold, 2019. "Future scenarios of variable renewable energies and flexibility requirements for thermal power plants in China," Energy, Elsevier, vol. 167(C), pages 708-714.
    4. Zhu, Xi & Zeng, Bo & Dong, Houqi & Liu, Jiaomin, 2020. "An interval-prediction based robust optimization approach for energy-hub operation scheduling considering flexible ramping products," Energy, Elsevier, vol. 194(C).
    5. Li, Jia & Liu, Feng & Li, Zuyi & Shao, Chengcheng & Liu, Xinyuan, 2018. "Grid-side flexibility of power systems in integrating large-scale renewable generations: A critical review on concepts, formulations and solution approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 272-284.
    6. Xiang, Yue & Cai, Hanhu & Gu, Chenghong & Shen, Xiaodong, 2020. "Cost-benefit analysis of integrated energy system planning considering demand response," Energy, Elsevier, vol. 192(C).
    7. Guo, Zheyu & Zheng, Yanan & Li, Gengyin, 2020. "Power system flexibility quantitative evaluation based on improved universal generating function method: A case study of Zhangjiakou," Energy, Elsevier, vol. 205(C).
    8. Wang, Yi & Cheng, Jiangnan & Zhang, Ning & Kang, Chongqing, 2018. "Automatic and linearized modeling of energy hub and its flexibility analysis," Applied Energy, Elsevier, vol. 211(C), pages 705-714.
    9. Heidari, A. & Mortazavi, S.S. & Bansal, R.C., 2020. "Stochastic effects of ice storage on improvement of an energy hub optimal operation including demand response and renewable energies," Applied Energy, Elsevier, vol. 261(C).
    10. Lu, Xinhui & Liu, Zhaoxi & Ma, Li & Wang, Lingfeng & Zhou, Kaile & Feng, Nanping, 2020. "A robust optimization approach for optimal load dispatch of community energy hub," Applied Energy, Elsevier, vol. 259(C).
    11. Jadidbonab, Mohammad & Babaei, Ebrahim & Mohammadi-ivatloo, Behnam, 2019. "CVaR-constrained scheduling strategy for smart multi carrier energy hub considering demand response and compressed air energy storage," Energy, Elsevier, vol. 174(C), pages 1238-1250.
    12. 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).
    13. Zafarani, Hamidreza & Taher, Seyed Abbas & Shahidehpour, Mohammad, 2020. "Robust operation of a multicarrier energy system considering EVs and CHP units," Energy, Elsevier, vol. 192(C).
    14. Bostan, Alireza & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2020. "Optimal scheduling of distribution systems considering multiple downward energy hubs and demand response programs," Energy, Elsevier, vol. 190(C).
    Full references (including those not matched with items on IDEAS)

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    2. Liu, Zhouding & Nazari-Heris, Morteza, 2023. "Optimal bidding strategy of multi-carrier systems in electricity markets using information gap decision theory," Energy, Elsevier, vol. 280(C).

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