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Multi-time scale dynamic operation optimization method for industrial park electricity-heat-gas integrated energy system considering demand elasticity

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  • Lin, Xiaojie
  • Lin, Xueru
  • Zhong, Wei
  • Zhou, Yi

Abstract

This study proposes a multi-time scale dynamic optimization (MSDO) method for ultra-short-term scheduling in industrial electricity-heat-gas integrated energy systems. The aim is to enhance the feasibility of scheduling schemes and to utilize flexibility potential. The MSDO method considers equipment response differences and demand fulfillment time disparities. The dynamic aspect is reflected in the supply-demand matching within the scheduling time window. A single-layer model with unified temporal granularity is constructed based on lag parameter identification. The study proposes various forms of energy demand elasticity, including steam networks and cumulative demand, and investigates the optimal minimum temporal granularity for scheduling. Case results demonstrate that the MSDO method effectively characterizes the multi-energy time lag of equipment. Compared with methods disregarding lag parameters, the MSDO method enhances total profit by ¥ 120711.42 and improves operation stability by 2.96%. The MSDO method outperforms baseline methods in cost and stability, accommodating a 160% increase in renewable energy growth. Under different elasticity spaces, the profit of the cumulative demand method exceeds that of the average method. The time lag of different equipment impacts scheduling profits. An optimal choice exists for the minimum temporal granularity to strike a balance between computational efficiency, economy, and feasibility.

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  • Lin, Xiaojie & Lin, Xueru & Zhong, Wei & Zhou, Yi, 2024. "Multi-time scale dynamic operation optimization method for industrial park electricity-heat-gas integrated energy system considering demand elasticity," Energy, Elsevier, vol. 293(C).
    • Handle: RePEc:eee:energy:v:293:y:2024:i:c:s0360544224004638
    DOI: 10.1016/j.energy.2024.130691
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    as
    1. Ahmadi, Seyed Ehsan & Sadeghi, Delnia & Marzband, Mousa & Abusorrah, Abdullah & Sedraoui, Khaled, 2022. "Decentralized bi-level stochastic optimization approach for multi-agent multi-energy networked micro-grids with multi-energy storage technologies," Energy, Elsevier, vol. 245(C).
    2. Mughees, Neelam & Jaffery, Mujtaba Hussain & Mughees, Anam & Ansari, Ejaz Ahmad & Mughees, Abdullah, 2023. "Reinforcement learning-based composite differential evolution for integrated demand response scheme in industrial microgrids," Applied Energy, Elsevier, vol. 342(C).
    3. Yang, Chao & Zhu, Yucai & Zhou, Jinming & Zhao, Jun & Bu, Ren & Feng, Guo, 2023. "Dynamic flexibility optimization of integrated energy system based on two-timescale model predictive control," Energy, Elsevier, vol. 276(C).
    4. Li, Jian & Jurasz, Jakub & Li, Hailong & Tao, Wen-Quan & Duan, Yuanyuan & Yan, Jinyue, 2020. "A new indicator for a fair comparison on the energy performance of data centers," Applied Energy, Elsevier, vol. 276(C).
    5. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2022. "Economic model predictive control of integrated energy systems: A multi-time-scale framework," Applied Energy, Elsevier, vol. 328(C).
    6. 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).
    7. Steinegger, Josef & Wallner, Stefan & Greiml, Matthias & Kienberger, Thomas, 2023. "A new quasi-dynamic load flow calculation for district heating networks," Energy, Elsevier, vol. 266(C).
    8. Zare Oskouei, Morteza & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Shafiee, Mahmood & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "A hybrid robust-stochastic approach to evaluate the profit of a multi-energy retailer in tri-layer energy markets," Energy, Elsevier, vol. 214(C).
    9. Elgamal, M. & Korovkin, Nikolay & Abdel Menaem, A. & Elmitwally, Akram, 2022. "Day-ahead complex power scheduling in a reconfigurable hybrid-energy islanded microgrid with responsive demand considering uncertainty and different load models," Applied Energy, Elsevier, vol. 309(C).
    10. Ma, Kai & Zhang, Rencai & Yang, Jie & Song, Debao, 2023. "Collaborative optimization scheduling of integrated energy system considering user dissatisfaction," Energy, Elsevier, vol. 274(C).
    11. Xi, Yufei & Fang, Jiakun & Chen, Zhe & Zeng, Qing & Lund, Henrik, 2021. "Optimal coordination of flexible resources in the gas-heat-electricity integrated energy system," Energy, Elsevier, vol. 223(C).
    12. Li, Peng & Wang, Zixuan & Wang, Jiahao & Guo, Tianyu & Yin, Yunxing, 2021. "A multi-time-space scale optimal operation strategy for a distributed integrated energy system," Applied Energy, Elsevier, vol. 289(C).
    13. Wei, Shangshang & Gao, Xianhua & Zhang, Yi & Li, Yiguo & Shen, Jiong & Li, Zuyi, 2021. "An improved stochastic model predictive control operation strategy of integrated energy system based on a single-layer multi-timescale framework," Energy, Elsevier, vol. 235(C).
    14. Lin, Xiaojie & Lin, Xueru & Zhong, Wei & Zhou, Yi, 2023. "Predictive operation optimization of multi-energy virtual power plant considering behavior uncertainty of diverse stakeholders," Energy, Elsevier, vol. 280(C).
    15. Troitzsch, Sebastian & Sreepathi, Bhargava Krishna & Huynh, Thanh Phong & Moine, Aurelie & Hanif, Sarmad & Fonseca, Jimeno & Hamacher, Thomas, 2020. "Optimal electric-distribution-grid planning considering the demand-side flexibility of thermal building systems for a test case in Singapore," Applied Energy, Elsevier, vol. 273(C).
    16. Ordoudis, Christos & Pinson, Pierre & Morales, Juan M., 2019. "An Integrated Market for Electricity and Natural Gas Systems with Stochastic Power Producers," European Journal of Operational Research, Elsevier, vol. 272(2), pages 642-654.
    17. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N. & Burmester, Daniel, 2021. "Strategic design optimisation of multi-energy-storage-technology micro-grids considering a two-stage game-theoretic market for demand response aggregation," Applied Energy, Elsevier, vol. 287(C).
    18. Merrick, James H., 2016. "On representation of temporal variability in electricity capacity planning models," Energy Economics, Elsevier, vol. 59(C), pages 261-274.
    19. Javanshir, Nima & Syri, Sanna & Tervo, Seela & Rosin, Argo, 2023. "Operation of district heat network in electricity and balancing markets with the power-to-heat sector coupling," Energy, Elsevier, vol. 266(C).
    20. Ma, Yiming & Wang, Haixin & Hong, Feng & Yang, Junyou & Chen, Zhe & Cui, Haoqian & Feng, Jiawei, 2021. "Modeling and optimization of combined heat and power with power-to-gas and carbon capture system in integrated energy system," Energy, Elsevier, vol. 236(C).
    21. Wang, Xiaojing & Han, Li & Wang, Chong & Yu, Hongbo & Yu, Xiaojiao, 2023. "A time-scale adaptive dispatching strategy considering the matching of time characteristics and dispatching periods of the integrated energy system," Energy, Elsevier, vol. 267(C).
    22. Aghdam, Farid Hamzeh & Mudiyanselage, Manthila Wijesooriya & Mohammadi-Ivatloo, Behnam & Marzband, Mousa, 2023. "Optimal scheduling of multi-energy type virtual energy storage system in reconfigurable distribution networks for congestion management," Applied Energy, Elsevier, vol. 333(C).
    23. Benzaama, M.H. & Rajaoarisoa, L.H. & Lekhal, M.C. & Menhoudj, S. & Mokhtari, A.M., 2021. "Thermal inertia and energy efficiency assessment of Direct Solar Floor system using a switching-linear model," Applied Energy, Elsevier, vol. 300(C).
    24. Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
    25. Shirizadeh, Behrang & Quirion, Philippe, 2022. "Do multi-sector energy system optimization models need hourly temporal resolution? A case study with an investment and dispatch model applied to France," Applied Energy, Elsevier, vol. 305(C).
    26. 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.
    27. Jani, Ali & Karimi, Hamid & Jadid, Shahram, 2022. "Two-layer stochastic day-ahead and real-time energy management of networked microgrids considering integration of renewable energy resources," Applied Energy, Elsevier, vol. 323(C).
    28. Tarragona, Joan & Fernández, Cèsar & de Gracia, Alvaro, 2020. "Model predictive control applied to a heating system with PV panels and thermal energy storage," Energy, Elsevier, vol. 197(C).
    29. Saletti, Costanza & Morini, Mirko & Gambarotta, Agostino, 2022. "Smart management of integrated energy systems through co-optimization with long and short horizons," Energy, Elsevier, vol. 250(C).
    30. Wei, Xintong & Qiu, Rui & Liang, Yongtu & Liao, Qi & Klemeš, Jiří Jaromír & Xue, Jinjun & Zhang, Haoran, 2022. "Roadmap to carbon emissions neutral industrial parks: Energy, economic and environmental analysis," Energy, Elsevier, vol. 238(PA).
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