IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v322y2025ics0360544225013337.html

Short-term and probability scenario-oriented energy management of integrated energy distribution systems with considering energy market interactions and end-user participation

Author

Listed:
  • Sepehrzad, Reza
  • Al-Durra, Ahmed
  • Anvari-Moghaddam, Amjad
  • Sadabadi, Mahdieh S.

Abstract

In this research, a scenario-oriented operational framework and an optimal tri-level energy management system within the energy hub (EH) architecture are introduced, considering the uncertainties associated with renewable energy resources and stochastic demand, particularly from electric vehicles, utilizing both central and local controller platforms. The devised model incorporates the variability of pricing for both electric and thermal energy carriers, informed by indicators from wholesale and retail markets. The scenario-oriented model for optimal power management and operation employs the K-means clustering technique alongside the development of probabilistic scenarios, which is subsequently addressed through the particle swarm optimization method. The K-means clustering technique is articulated to ascertain the array of multidimensional correlation scenarios that encompass power generation sources and varieties of consumption loads, temporal sequences, auto-correlation, and cross-correlation. To enhance the subscriber engagement, diminish operational expenditures, and also augment profitability as a consequence of subscriber involvement, the integrated demand response (IDR) program has been developed within the framework of the EH. The findings indicate a 24 % decrement in overall operation cost, a 24 % reduction in energy supply expenditures, and a 23.4 % increase in profitability attributable to the IDR programs execution and the engagement of energy storage units in the power supply chain.

Suggested Citation

  • Sepehrzad, Reza & Al-Durra, Ahmed & Anvari-Moghaddam, Amjad & Sadabadi, Mahdieh S., 2025. "Short-term and probability scenario-oriented energy management of integrated energy distribution systems with considering energy market interactions and end-user participation," Energy, Elsevier, vol. 322(C).
    • Handle: RePEc:eee:energy:v:322:y:2025:i:c:s0360544225013337
    DOI: 10.1016/j.energy.2025.135691
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225013337
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2025.135691?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Xu, Yijun & Zhang, Xuan & Li, Ji, 2024. "Multiple energy planning in the energy hub considering renewable sources, electric vehicles and management in the daily electricity market with wind multi-objective optimization algorithm," Energy, Elsevier, vol. 309(C).
    2. Sepehrzad, Reza & Khodadadi, Amin & Adinehpour, Sara & Karimi, Maede, 2024. "A multi-agent deep reinforcement learning paradigm to improve the robustness and resilience of grid connected electric vehicle charging stations against the destructive effects of cyber-attacks," Energy, Elsevier, vol. 307(C).
    3. Lorestani, Alireza & Gharehpetian, G.B. & Nazari, Mohammad Hassan, 2019. "Optimal sizing and techno-economic analysis of energy- and cost-efficient standalone multi-carrier microgrid," Energy, Elsevier, vol. 178(C), pages 751-764.
    4. Yang, Jie & Zhao, Boyuan & Ma, Kai & Zhong, Jiaqing & Xu, Wenya, 2024. "A carbon integrated energy pricing strategy based on non-cooperative game for energy hub in seaport energy system," Energy, Elsevier, vol. 309(C).
    5. Adewuyi, Oludamilare Bode & Aki, Hirohisa, 2024. "Optimal planning for high renewable energy integration considering demand response, uncertainties, and operational performance flexibility," Energy, Elsevier, vol. 313(C).
    6. Zhong, Shangpeng & Wang, Xiaoming & Wu, Hongbin & He, Ye & Xu, Bin & Ding, Ming, 2024. "Energy hub management for integrated energy systems: A multi-objective optimization control strategy based on distributed output and energy conversion characteristics," Energy, Elsevier, vol. 306(C).
    7. Noorollahi, Younes & Golshanfard, Aminabbas & Hashemi-Dezaki, Hamed, 2022. "A scenario-based approach for optimal operation of energy hub under different schemes and structures," Energy, Elsevier, vol. 251(C).
    8. Oskouei, Morteza Zare & Mohammadi-Ivatloo, Behnam & Abapour, Mehdi & Shafiee, Mahmood & Anvari-Moghaddam, Amjad, 2021. "Privacy-preserving mechanism for collaborative operation of high-renewable power systems and industrial energy hubs," Applied Energy, Elsevier, vol. 283(C).
    9. Shields, Michael D. & Zhang, Jiaxin, 2016. "The generalization of Latin hypercube sampling," Reliability Engineering and System Safety, Elsevier, vol. 148(C), pages 96-108.
    10. Peng, Hongyi & Yan, Mingyu & Zhou, Yijia, 2024. "Privacy-preserving non-iterative decentralized optimal energy flow for integrated hydrogen-electricity-heat system based on projection method," Applied Energy, Elsevier, vol. 368(C).
    11. Xu, Xiao & Hu, Weihao & Liu, Wen & Du, Yuefang & Huang, Rui & Huang, Qi & Chen, Zhe, 2021. "Look-ahead risk-constrained scheduling for an energy hub integrated with renewable energy," Applied Energy, Elsevier, vol. 297(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Shihai & Yang, Ruofei & Liu, Ying, 2026. "New distributionally robust optimization framework and algorithm for energy hub scheduling integrating demand response programs under ambiguous prices and loads," Applied Energy, Elsevier, vol. 405(C).
    2. Aslani, Mehrdad & Mashayekhi, Mehdi & Hashemi-Dezaki, Hamed & Ketabi, Abbas, 2022. "Robust optimal operation of energy hub incorporating integrated thermal and electrical demand response programs under various electric vehicle charging modes," Applied Energy, Elsevier, vol. 321(C).
    3. Tao, Jiaxin & Duan, Jiandong & Tuo, Lihao & Gao, Qi & Tian, Qinxing & Lu, Wenchao, 2025. "Exergy efficiency based multi-objective configuration optimization of energy hubs in the multi-energy distribution system," Energy, Elsevier, vol. 329(C).
    4. Han, Xiaojuan & Yang, Xiaoyan & Bai, Tianyang, 2025. "Double-layer optimal scheduling for wind-PV-hydro-hybrid energy storage system with multi-timescale coordination," Energy, Elsevier, vol. 336(C).
    5. Soheil Mohseni & Alan C. Brent, 2022. "A Metaheuristic-Based Micro-Grid Sizing Model with Integrated Arbitrage-Aware Multi-Day Battery Dispatching," Sustainability, MDPI, vol. 14(19), pages 1-24, October.
    6. Yu, Min Gyung & Pavlak, Gregory S., 2023. "Risk-aware sizing and transactive control of building portfolios with thermal energy storage," Applied Energy, Elsevier, vol. 332(C).
    7. Ziyu Li & Bangjun Wang, 2024. "A Bibliometric Analysis of Carbon Allowances in the Carbon Emissions Trading Market," Energies, MDPI, vol. 18(1), pages 1-18, December.
    8. Shi, Yunhong & Li, Chengjiang & Wang, Honglei & Wang, Xiaolin & Negnevitsky, Michael, 2025. "A novel scheduling strategy of a hybrid wind-solar-hydro system for smoothing energy and power fluctuations," Energy, Elsevier, vol. 320(C).
    9. Xu, Jing & Wang, Xiaoying & Gu, Yujiong & Ma, Suxia, 2023. "A data-based day-ahead scheduling optimization approach for regional integrated energy systems with varying operating conditions," Energy, Elsevier, vol. 283(C).
    10. Himakar Ganti & Manu Kamin & Prashant Khare, 2020. "Design Space Exploration of Turbulent Multiphase Flows Using Machine Learning-Based Surrogate Model," Energies, MDPI, vol. 13(17), pages 1-23, September.
    11. Bao, Minglei & Hui, Hengyu & Ding, Yi & Sun, Xiaocong & Zheng, Chenghang & Gao, Xiang, 2023. "An efficient framework for exploiting operational flexibility of load energy hubs in risk management of integrated electricity-gas systems," Applied Energy, Elsevier, vol. 338(C).
    12. Wang, Tianzhe & Chen, Zequan & Li, Guofa & He, Jialong & Liu, Chao & Du, Xuejiao, 2024. "A novel method for high-dimensional reliability analysis based on activity score and adaptive Kriging," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    13. Tan, Mao & Jiang, Hongwei & Kuang, Yi & Li, Kang & Wang, Rui & Li, Zibin, 2025. "Electricity–carbon dual response for energy-intensive enterprise: A co-optimization approach," Renewable Energy, Elsevier, vol. 251(C).
    14. Magda I. El-Afifi & Magdi M. Saadawi & Abdelfattah A. Eladl, 2022. "Cogeneration Systems Performance Analysis as a Sustainable Clean Energy and Water Source Based on Energy Hubs Using the Archimedes Optimization Algorithm," Sustainability, MDPI, vol. 14(22), pages 1-26, November.
    15. Yao, Zhenghong & Hao, Jin & Tan, Zhi & Li, Changyou & Zhao, Jinsong, 2025. "Ratcheting fatigue reliability and sensitivity analysis of hydraulic pipe under in-service loadings," Reliability Engineering and System Safety, Elsevier, vol. 264(PA).
    16. Hoseini, Naghi & Sheikholeslami, Abdolreza & Barforoushi, Taghi & Latify, Mohammad Amin, 2020. "Preventive maintenance mid-term scheduling of resources in multi-carrier energy systems," Energy, Elsevier, vol. 197(C).
    17. Rahmat Khezri & Amin Mahmoudi & Hirohisa Aki & S. M. Muyeen, 2021. "Optimal Planning of Remote Area Electricity Supply Systems: Comprehensive Review, Recent Developments and Future Scopes," Energies, MDPI, vol. 14(18), pages 1-29, September.
    18. Zhang, Zongnan & Shen, Xiaojun & Chang, Mingjiang, 2025. "Dual stochastic multi-stage robust optimization of integrated energy system considering long medium and short-term uncertainties," Applied Energy, Elsevier, vol. 400(C).
    19. Azimian, Mahdi & Amir, Vahid & Javadi, Saeid, 2020. "Economic and Environmental Policy Analysis for Emission-Neutral Multi-Carrier Microgrid Deployment," Applied Energy, Elsevier, vol. 277(C).
    20. Seyfi, Mohammad & Mehdinejad, Mehdi & Mohammadi-Ivatloo, Behnam & Shayanfar, Heidarali, 2022. "Deep learning-based scheduling of virtual energy hubs with plug-in hybrid compressed natural gas-electric vehicles," Applied Energy, Elsevier, vol. 321(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:322:y:2025:i:c:s0360544225013337. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.