IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i23p5995-d1531911.html
   My bibliography  Save this article

Multi-Time Optimization Scheduling Strategy for Integrated Energy Systems Considering Multiple Controllable Loads and Carbon Capture Plants

Author

Listed:
  • Zhe Han

    (Inner Mongolia Huomei Hongjun Aluminum and Electricity Co., Ltd., Holingol 029200, China)

  • Zehua Li

    (Inner Mongolia Huomei Hongjun Aluminum and Electricity Co., Ltd., Holingol 029200, China)

  • Wenbo Wang

    (Inner Mongolia Huomei Hongjun Aluminum and Electricity Co., Ltd., Holingol 029200, China)

  • Wei Liu

    (Inner Mongolia Huomei Hongjun Aluminum and Electricity Co., Ltd., Holingol 029200, China)

  • Qiang Ma

    (Inner Mongolia Huomei Hongjun Aluminum and Electricity Co., Ltd., Holingol 029200, China)

  • Sidong Sun

    (Inner Mongolia Huomei Hongjun Aluminum and Electricity Co., Ltd., Holingol 029200, China)

  • Haiyang Liu

    (Inner Mongolia Huomei Hongjun Aluminum and Electricity Co., Ltd., Holingol 029200, China)

  • Qiang Zhang

    (Shanghai Power Equipment Research Institute Co., Ltd., Shanghai 200240, China)

  • Yue Cao

    (Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China)

Abstract

In response to the dual carbon targets, it is necessary not only to reduce carbon emissions but also to increase the proportion of renewable energy generation capacity, thereby exacerbating the scarcity of flexible resources in the power system. Addressing these challenges, this study proposes an operational optimization framework for an integrated energy system. This system encompasses wind/solar power plants, coal-fired power plants, carbon capture power plants, gas turbines, energy storage systems, and controllable loads, including reducible power loads, transferable power loads, electrolytic aluminum loads, transferable heat loads, and reducible loads. This study employs a system combining carbon capture plants with thermal power stations to supply flexible resources to the integrated energy system while reducing carbon emissions during the generation process of the thermal power units. A multi-timescale optimization scheduling approach is adopted to manage the uncertainties in wind, photovoltaic, and electric/thermal loads within the integrated energy system. The operational costs of the integrated energy system consider the capacity degradation costs of energy storage systems, the solvent degradation costs of carbon capture, and carbon costs. Finally, the cplex solver was used to solve the above model. The simulation results show that the consideration of five controllable loads leads to an increase of 7.22% in the interactive benefits with the power grid; the difference between the complete cost model and the incomplete overall benefits is 94.35%. It can be seen that the dispatching method proposed in this study can take advantage of the dispatching advantages of source-load adjustable resources and achieve the goal of low-carbon economic dispatching of the power system.

Suggested Citation

  • Zhe Han & Zehua Li & Wenbo Wang & Wei Liu & Qiang Ma & Sidong Sun & Haiyang Liu & Qiang Zhang & Yue Cao, 2024. "Multi-Time Optimization Scheduling Strategy for Integrated Energy Systems Considering Multiple Controllable Loads and Carbon Capture Plants," Energies, MDPI, vol. 17(23), pages 1-18, November.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:23:p:5995-:d:1531911
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/23/5995/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/23/5995/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Safdarnejad, Seyed Mostafa & Hedengren, John D. & Powell, Kody M., 2018. "Performance comparison of low temperature and chemical absorption carbon capture processes in response to dynamic electricity demand and price profiles," Applied Energy, Elsevier, vol. 228(C), pages 577-592.
    2. Li, Qiang & Zhou, Yongcheng & Wei, Fanchao & Li, Shuangxiu & Wang, Zhonghao & Li, Jiajia & Zhou, Guowen & Liu, Jinfu & Yan, Peigang & Yu, Daren, 2024. "Multi-time scale scheduling for virtual power plants: Integrating the flexibility of power generation and multi-user loads while considering the capacity degradation of energy storage systems," Applied Energy, Elsevier, vol. 362(C).
    3. Li, Qiang & Wei, Fanchao & Zhou, Yongcheng & Li, Jiajia & Zhou, Guowen & Wang, Zhonghao & Liu, Jinfu & Yan, Peigang & Yu, Daren, 2023. "A scheduling framework for VPP considering multiple uncertainties and flexible resources," Energy, Elsevier, vol. 282(C).
    4. Li, Xue & Zhang, Rufeng & Bai, Linquan & Li, Guoqing & Jiang, Tao & Chen, Houhe, 2018. "Stochastic low-carbon scheduling with carbon capture power plants and coupon-based demand response," Applied Energy, Elsevier, vol. 210(C), pages 1219-1228.
    5. Lucia F. Pérez Garcés & Karol Sztekler & Leonardo Azevedo & Piotr Boruta & Tomasz Bujok & Ewelina Radomska & Agata Mlonka-Mędrala & Łukasz Mika & Tomasz Chmielniak, 2024. "Assessment of the Use of Carbon Capture and Storage Technology to Reduce CO 2 Emissions from a Natural Gas Combined Cycle Power Plant in a Polish Context," Energies, MDPI, vol. 17(13), pages 1-16, July.
    6. Yue, Xiaoyu & Liao, Siyang & Xu, Jian & Ke, Deping & Wang, Huiji & Yang, Jiaquan & He, Xuehao, 2024. "Collaborative optimization of renewable energy power systems integrating electrolytic aluminum load regulation and thermal power deep peak shaving," Applied Energy, Elsevier, vol. 373(C).
    7. Li, Qiang & Dong, Fuxiang & Zhou, Guowen & Mu, Chunjin & Wang, Zhonghao & Liu, Jinfu & Yan, Peigang & Yu, Daren, 2025. "Co-optimization of virtual power plants and distribution grids: Emphasizing flexible resource aggregation and battery capacity degradation," Applied Energy, Elsevier, vol. 377(PB).
    8. Aalami, H.A. & Moghaddam, M. Parsa & Yousefi, G.R., 2010. "Demand response modeling considering Interruptible/Curtailable loads and capacity market programs," Applied Energy, Elsevier, vol. 87(1), pages 243-250, January.
    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. Li, Qiang & Zhou, Yongcheng & Wei, Fanchao & Li, Shuangxiu & Wang, Zhonghao & Li, Jiajia & Zhou, Guowen & Liu, Jinfu & Yan, Peigang & Yu, Daren, 2024. "Multi-time scale scheduling for virtual power plants: Integrating the flexibility of power generation and multi-user loads while considering the capacity degradation of energy storage systems," Applied Energy, Elsevier, vol. 362(C).
    2. Yiqi Dong & Zuoji Dong, 2023. "Bibliometric Analysis of Game Theory on Energy and Natural Resource," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    3. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    4. Abdul Conteh & Mohammed Elsayed Lotfy & Kiptoo Mark Kipngetich & Tomonobu Senjyu & Paras Mandal & Shantanu Chakraborty, 2019. "An Economic Analysis of Demand Side Management Considering Interruptible Load and Renewable Energy Integration: A Case Study of Freetown Sierra Leone," Sustainability, MDPI, vol. 11(10), pages 1-19, May.
    5. Pang, Simian & Xu, Qingshan & Yang, Yongbiao & Cheng, Aoxue & Shi, Zhengkun & Shi, Yun, 2024. "Robust decomposition and tracking strategy for demand response enhanced virtual power plants," Applied Energy, Elsevier, vol. 373(C).
    6. Dehnavi, Ehsan & Abdi, Hamdi, 2016. "Optimal pricing in time of use demand response by integrating with dynamic economic dispatch problem," Energy, Elsevier, vol. 109(C), pages 1086-1094.
    7. Neda Hajibandeh & Mehdi Ehsan & Soodabeh Soleymani & Miadreza Shafie-khah & João P. S. Catalão, 2017. "The Mutual Impact of Demand Response Programs and Renewable Energies: A Survey," Energies, MDPI, vol. 10(9), pages 1-18, September.
    8. Davarzani, Sima & Pisica, Ioana & Taylor, Gareth A. & Munisami, Kevin J., 2021. "Residential Demand Response Strategies and Applications in Active Distribution Network Management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    9. Shaukat, N. & Ali, S.M. & Mehmood, C.A. & Khan, B. & Jawad, M. & Farid, U. & Ullah, Z. & Anwar, S.M. & Majid, M., 2018. "A survey on consumers empowerment, communication technologies, and renewable generation penetration within Smart Grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1453-1475.
    10. Botelho, D.F. & de Oliveira, L.W. & Dias, B.H. & Soares, T.A. & Moraes, C.A., 2022. "Prosumer integration into the Brazilian energy sector: An overview of innovative business models and regulatory challenges," Energy Policy, Elsevier, vol. 161(C).
    11. Andruszkiewicz, Jerzy & Lorenc, Józef & Weychan, Agnieszka, 2020. "Seasonal variability of price elasticity of demand of households using zonal tariffs and its impact on hourly load of the power system," Energy, Elsevier, vol. 196(C).
    12. Alahäivälä, Antti & Heß, Tobias & Cao, Sunliang & Lehtonen, Matti, 2015. "Analyzing the optimal coordination of a residential micro-CHP system with a power sink," Applied Energy, Elsevier, vol. 149(C), pages 326-337.
    13. Wei, Congying & Xu, Jian & Liao, Siyang & Sun, Yuanzhang & Jiang, Yibo & Ke, Deping & Zhang, Zhen & Wang, Jing, 2018. "A bi-level scheduling model for virtual power plants with aggregated thermostatically controlled loads and renewable energy," Applied Energy, Elsevier, vol. 224(C), pages 659-670.
    14. Sheikhi Fini, A. & Parsa Moghaddam, M. & Sheikh-El-Eslami, M.K., 2013. "An investigation on the impacts of regulatory support schemes on distributed energy resource expansion planning," Renewable Energy, Elsevier, vol. 53(C), pages 339-349.
    15. Wang, Yong & Li, Lin, 2015. "Time-of-use electricity pricing for industrial customers: A survey of U.S. utilities," Applied Energy, Elsevier, vol. 149(C), pages 89-103.
    16. Marian Kampik & Marcin Fice & Adam Pilśniak & Krzysztof Bodzek & Anna Piaskowy, 2023. "An Analysis of Energy Consumption in Small- and Medium-Sized Buildings," Energies, MDPI, vol. 16(3), pages 1-21, February.
    17. Schreiber, Michael & Wainstein, Martin E. & Hochloff, Patrick & Dargaville, Roger, 2015. "Flexible electricity tariffs: Power and energy price signals designed for a smarter grid," Energy, Elsevier, vol. 93(P2), pages 2568-2581.
    18. Shuo Yin & Yang He & Zhiheng Li & Senmao Li & Peng Wang & Ziyi Chen, 2024. "A Novel Multi-Timescale Optimal Scheduling Model for a Power–Gas Mutual Transformation Virtual Power Plant with Power-to-Gas Conversion and Comprehensive Demand Response," Energies, MDPI, vol. 17(15), pages 1-19, August.
    19. Woo, C.K. & Li, R. & Shiu, A. & Horowitz, I., 2013. "Residential winter kWh responsiveness under optional time-varying pricing in British Columbia," Applied Energy, Elsevier, vol. 108(C), pages 288-297.
    20. Adhikari, Rajendra & Pipattanasomporn, M. & Rahman, S., 2018. "An algorithm for optimal management of aggregated HVAC power demand using smart thermostats," Applied Energy, Elsevier, vol. 217(C), pages 166-177.

    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:gam:jeners:v:17:y:2024:i:23:p:5995-:d:1531911. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.