IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v274y2023ics0360544223007053.html
   My bibliography  Save this article

Collaborative optimization scheduling of integrated energy system considering user dissatisfaction

Author

Listed:
  • Ma, Kai
  • Zhang, Rencai
  • Yang, Jie
  • Song, Debao

Abstract

Traditional industrial parks generally have the problem of energy waste and low energy utilization. In this paper, we study a multi-energy collaborative optimization problem between integrated energy system (IES) energy scheduling and production control of plant, which considers the change of user dissatisfaction caused by load adjustment after industrial users participate in multi-energy demand response (MEDR). The collaborative optimization problem is described as a quadratic programming (QP) problem, including energy equipment output and production equipment operation load under constraints. The QP problem is solved by Cplex solver. An IES framework is constructed and its components are modeled separately. Then, based on Taguchi loss function and Fanger thermal comfort model, a collaborative optimization model of plant IES considering the user dissatisfaction is proposed. Furthermore, the collaborative optimization model is applied to control the IES and plant production. Simulation results show that the proposed optimization model can reduce the energy cost and user dissatisfaction, and improve the energy efficiency.

Suggested Citation

  • Ma, Kai & Zhang, Rencai & Yang, Jie & Song, Debao, 2023. "Collaborative optimization scheduling of integrated energy system considering user dissatisfaction," Energy, Elsevier, vol. 274(C).
    • Handle: RePEc:eee:energy:v:274:y:2023:i:c:s0360544223007053
    DOI: 10.1016/j.energy.2023.127311
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223007053
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.127311?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    2. Good, Nicholas, 2019. "Using behavioural economic theory in modelling of demand response," Applied Energy, Elsevier, vol. 239(C), pages 107-116.
    3. Acuña, Luceny Guzmán & Padilla, Ricardo Vasquez & Mercado, Alcides Santander, 2017. "Measuring reliability of hybrid photovoltaic-wind energy systems: A new indicator," Renewable Energy, Elsevier, vol. 106(C), pages 68-77.
    4. Ekren, Orhan & Ekren, Banu Y., 2010. "Size optimization of a PV/wind hybrid energy conversion system with battery storage using simulated annealing," Applied Energy, Elsevier, vol. 87(2), pages 592-598, February.
    5. Derakhshan, Ghasem & Shayanfar, Heidar Ali & Kazemi, Ahad, 2016. "The optimization of demand response programs in smart grids," Energy Policy, Elsevier, vol. 94(C), pages 295-306.
    6. Ma, Tao & Yang, Hongxing & Lu, Lin, 2014. "A feasibility study of a stand-alone hybrid solar–wind–battery system for a remote island," Applied Energy, Elsevier, vol. 121(C), pages 149-158.
    7. Haider, Haider Tarish & See, Ong Hang & Elmenreich, Wilfried, 2016. "A review of residential demand response of smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 166-178.
    8. Cho, Heejin & Mago, Pedro J. & Luck, Rogelio & Chamra, Louay M., 2009. "Evaluation of CCHP systems performance based on operational cost, primary energy consumption, and carbon dioxide emission by utilizing an optimal operation scheme," Applied Energy, Elsevier, vol. 86(12), pages 2540-2549, December.
    9. Kourkoumpas, Dimitrios-Sotirios & Benekos, Georgios & Nikolopoulos, Nikolaos & Karellas, Sotirios & Grammelis, Panagiotis & Kakaras, Emmanouel, 2018. "A review of key environmental and energy performance indicators for the case of renewable energy systems when integrated with storage solutions," Applied Energy, Elsevier, vol. 231(C), pages 380-398.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hasanien, Hany M. & Alsaleh, Ibrahim & Tostado-Véliz, Marcos & Zhang, Miao & Alateeq, Ayoob & Jurado, Francisco & Alassaf, Abdullah, 2024. "Hybrid particle swarm and sea horse optimization algorithm-based optimal reactive power dispatch of power systems comprising electric vehicles," Energy, Elsevier, vol. 286(C).
    2. Jia, Zhiyang & Jin, Xinqiao & Lyu, Yuan & Xue, Qi & Du, Zhimin, 2023. "A robust capacity configuration selection method of multiple-chiller system concerned with the uncertainty of annual hourly load profile," Energy, Elsevier, vol. 282(C).
    3. 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).
    4. Lili Mo & Zeyu Deng & Haoyong Chen & Junkun Lan, 2023. "Multi-Objective Co-Operative Game-Based Optimization for Park-Level Integrated Energy System Based on Exergy-Economic Analysis," Energies, MDPI, vol. 16(24), pages 1-19, December.
    5. Yang, Meng & Liu, Yisheng, 2023. "Research on multi-energy collaborative operation optimization of integrated energy system considering carbon trading and demand response," Energy, Elsevier, vol. 283(C).
    6. Zhao, Wenna & Ma, Kai & Yang, Jie & Guo, Shiliang, 2024. "A multi-time scale demand response scheme based on noncooperative game for economic operation of industrial park," Energy, Elsevier, vol. 302(C).

    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. Houssem R. E. H. Bouchekara & Yusuf A. Sha’aban & Mohammad S. Shahriar & Saad M. Abdullah & Makbul A. Ramli, 2023. "Sizing of Hybrid PV/Battery/Wind/Diesel Microgrid System Using an Improved Decomposition Multi-Objective Evolutionary Algorithm Considering Uncertainties and Battery Degradation," Sustainability, MDPI, vol. 15(14), pages 1-38, July.
    2. Mazzeo, Domenico & Matera, Nicoletta & De Luca, Pierangelo & Baglivo, Cristina & Maria Congedo, Paolo & Oliveti, Giuseppe, 2020. "Worldwide geographical mapping and optimization of stand-alone and grid-connected hybrid renewable system techno-economic performance across Köppen-Geiger climates," Applied Energy, Elsevier, vol. 276(C).
    3. Jordehi, A. Rezaee, 2019. "Optimisation of demand response in electric power systems, a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 308-319.
    4. Qi Huang & Aihua Jiang & Yu Zeng & Jianan Xu, 2022. "Community Flexible Load Dispatching Model Based on Herd Mentality," Energies, MDPI, vol. 15(13), pages 1-18, June.
    5. Tüysüz, Metin & Okumuş, Halil Ibrahim & Aymaz, Şeyma & Çavdar, Bora, 2024. "Real-time application of a demand-side management strategy using optimization algorithms," Applied Energy, Elsevier, vol. 368(C).
    6. Yuehong Lu & Mohammed Alghassab & Manuel S. Alvarez-Alvarado & Hasan Gunduz & Zafar A. Khan & Muhammad Imran, 2020. "Optimal Distribution of Renewable Energy Systems Considering Aging and Long-Term Weather Effect in Net-Zero Energy Building Design," Sustainability, MDPI, vol. 12(14), pages 1-20, July.
    7. Sara Ghaem Sigarchian & Anders Malmquist & Viktoria Martin, 2018. "Design Optimization of a Small-Scale Polygeneration Energy System in Different Climate Zones in Iran," Energies, MDPI, vol. 11(5), pages 1-19, May.
    8. Ogunjuyigbe, A.S.O. & Ayodele, T.R. & Akinola, O.A., 2016. "Optimal allocation and sizing of PV/Wind/Split-diesel/Battery hybrid energy system for minimizing life cycle cost, carbon emission and dump energy of remote residential building," Applied Energy, Elsevier, vol. 171(C), pages 153-171.
    9. Mahesh, Aeidapu & Sandhu, Kanwarjit Singh, 2015. "Hybrid wind/photovoltaic energy system developments: Critical review and findings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1135-1147.
    10. Ying-Yi Hong & Yong-Zhen Lai & Yung-Ruei Chang & Yih-Der Lee & Chia-Hui Lin, 2018. "Optimizing Energy Storage Capacity in Islanded Microgrids Using Immunity-Based Multiobjective Planning," Energies, MDPI, vol. 11(3), pages 1-15, March.
    11. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    12. Darcovich, K. & Kenney, B. & MacNeil, D.D. & Armstrong, M.M., 2015. "Control strategies and cycling demands for Li-ion storage batteries in residential micro-cogeneration systems," Applied Energy, Elsevier, vol. 141(C), pages 32-41.
    13. Oh, Ki-Yong & Epureanu, Bogdan I., 2016. "Characterization and modeling of the thermal mechanics of lithium-ion battery cells," Applied Energy, Elsevier, vol. 178(C), pages 633-646.
    14. Heendeniya, Charitha Buddhika & Sumper, Andreas & Eicker, Ursula, 2020. "The multi-energy system co-planning of nearly zero-energy districts – Status-quo and future research potential," Applied Energy, Elsevier, vol. 267(C).
    15. Nosratabadi, Seyyed Mostafa & Hooshmand, Rahmat-Allah & Gholipour, Eskandar, 2017. "A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 341-363.
    16. Cortés-Arcos, Tomás & Bernal-Agustín, José L. & Dufo-López, Rodolfo & Lujano-Rojas, Juan M. & Contreras, Javier, 2017. "Multi-objective demand response to real-time prices (RTP) using a task scheduling methodology," Energy, Elsevier, vol. 138(C), pages 19-31.
    17. Li, Zhengmao & Xu, Yan, 2018. "Optimal coordinated energy dispatch of a multi-energy microgrid in grid-connected and islanded modes," Applied Energy, Elsevier, vol. 210(C), pages 974-986.
    18. Lim, Keumju & Lee, Jongsu & Lee, Hyunjoo, 2021. "Implementing automated residential demand response in South Korea: Consumer preferences and market potential," Utilities Policy, Elsevier, vol. 70(C).
    19. Ioannis Panapakidis & Nikolaos Asimopoulos & Athanasios Dagoumas & Georgios C. Christoforidis, 2017. "An Improved Fuzzy C-Means Algorithm for the Implementation of Demand Side Management Measures," Energies, MDPI, vol. 10(9), pages 1-42, September.
    20. Das, Barun K. & Al-Abdeli, Yasir M. & Kothapalli, Ganesh, 2017. "Optimisation of stand-alone hybrid energy systems supplemented by combustion-based prime movers," Applied Energy, Elsevier, vol. 196(C), pages 18-33.

    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:274:y:2023:i:c:s0360544223007053. 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.