IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v312y2024ics0360544224033048.html
   My bibliography  Save this article

Operational optimization of a rural multi-energy system supported by a joint biomass-solid-waste-energy conversion system and supply chain

Author

Listed:
  • Liu, Yi
  • Xu, Xiao
  • Liu, Youbo
  • Liu, Junyong
  • Hu, Weihao
  • Yang, Nan
  • Jawad, Shafqat
  • Wei, Zhaobin

Abstract

Biomass, as one of the most accessible renewable resources, could reduce dependency on fossil fuels and mitigate associated environmental impacts. With economic development and improved living standards, biomass in rural areas is converted into various forms of energy to meet high energy demands. However, existing studies on rural multi-energy system operations assume energy production from biomass is a given input parameter and consider it to be a fixed constant or subject to upper and lower bounds, independent of the biomass supply chain. Indeed, biomass energy production is significantly influenced by the collection, transportation, storage, and other processes within the supply chain. This work proposes a mixed integer linear program (MILP) for the joint optimization of an integrated rural multi-biomass-solid waste energy conversion system with a source-grid-demand-based biomass-solid waste supply chain (IRMBS-BSC system). The IRMBS-BSC system encompasses three sub-systems: the biomass-solid waste source sub-system, the biomass-solid waste grid sub-system, and the biomass-solid waste demand sub-system. Various biomass-solid wastes are classified, and a source model is established to evaluate their availability. Subsequently, a supply chain model is developed within the biomass-solid waste grid sub-system. Based on the available and transported quantity from the biomass-solid waste source sub-system and grid sub-system, a multi-energy system operation model, considering refined biomass conversion processes, is proposed. A case study involving a multi-energy system that integrates multiple rural community biomass-solid waste supplies is conducted. The results demonstrate that the proposed MILP, which considers the biomass-solid waste supply chain, can reduce energy imports during the load peak periods and can also decrease the overall operational costs of the multi-energy system.

Suggested Citation

  • Liu, Yi & Xu, Xiao & Liu, Youbo & Liu, Junyong & Hu, Weihao & Yang, Nan & Jawad, Shafqat & Wei, Zhaobin, 2024. "Operational optimization of a rural multi-energy system supported by a joint biomass-solid-waste-energy conversion system and supply chain," Energy, Elsevier, vol. 312(C).
    • Handle: RePEc:eee:energy:v:312:y:2024:i:c:s0360544224033048
    DOI: 10.1016/j.energy.2024.133528
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224033048
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.133528?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. Saidur, R. & Abdelaziz, E.A. & Demirbas, A. & Hossain, M.S. & Mekhilef, S., 2011. "A review on biomass as a fuel for boilers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(5), pages 2262-2289, June.
    2. Zhi, Yuan & Yang, Xudong, 2023. "Scenario-based multi-objective optimization strategy for rural PV-battery systems," Applied Energy, Elsevier, vol. 345(C).
    3. Siwal, Samarjeet Singh & Zhang, Qibo & Devi, Nishu & Saini, Adesh Kumar & Saini, Vipin & Pareek, Bhawna & Gaidukovs, Sergejs & Thakur, Vijay Kumar, 2021. "Recovery processes of sustainable energy using different biomass and wastes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    4. Qi, Jingwei & Wang, Yijie & Xu, Pengcheng & Hu, Ming & Huhe, Taoli & Ling, Xiang & Yuan, Haoran & Chen, Yong, 2024. "Study on the Co-gasification characteristics of biomass and municipal solid waste based on machine learning," Energy, Elsevier, vol. 290(C).
    5. Gital Durmaz, Yeşim & Bilgen, Bilge, 2020. "Multi-objective optimization of sustainable biomass supply chain network design," Applied Energy, Elsevier, vol. 272(C).
    6. Wu, Juanjuan & Zhang, Jian & Yi, Weiming & Cai, Hongzhen & Li, Yang & Su, Zhanpeng, 2022. "Agri-biomass supply chain optimization in north China: Model development and application," Energy, Elsevier, vol. 239(PD).
    7. Ma, Siyuan & Mi, Yang & Shi, Shuai & Li, Dongdong & Xing, Haijun & Wang, Peng, 2024. "Low-carbon economic operation of energy hub integrated with linearization model and nodal energy-carbon price," Energy, Elsevier, vol. 294(C).
    8. Nils Boysen & Joachim Scholl & Konrad Stephan, 2017. "When road trains supply freight trains: scheduling the container loading process by gantry crane between multi-trailer trucks and freight trains," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(1), pages 137-164, January.
    9. Dong, Zeyuan & Zhang, Zhao & Huang, Minghui & Yang, Shaorong & Zhu, Jun & Zhang, Meng & Chen, Dongjiu, 2024. "Research on day-ahead optimal dispatching of virtual power plants considering the coordinated operation of diverse flexible loads and new energy," Energy, Elsevier, vol. 297(C).
    10. Abdulnasser, Ghada & Ali, Abdelfatah & Shaaban, Mostafa F. & Mohamed, Essam E.M., 2024. "Optimal resource allocation and operation for smart energy hubs considering hydrogen storage systems and electric vehicles," Energy, Elsevier, vol. 295(C).
    11. Nunes, L.J.R. & Causer, T.P. & Ciolkosz, D., 2020. "Biomass for energy: A review on supply chain management models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    12. Ju, Liwei & Yin, Zhe & Zhou, Qingqing & Li, Qiaochu & Wang, Peng & Tian, Wenxu & Li, Peng & Tan, Zhongfu, 2022. "Nearly-zero carbon optimal operation model and benefit allocation strategy for a novel virtual power plant using carbon capture, power-to-gas, and waste incineration power in rural areas," Applied Energy, Elsevier, vol. 310(C).
    13. Shao, Zhentong & Cao, Xiaoyu & Zhai, Qiaozhu & Guan, Xiaohong, 2023. "Risk-constrained planning of rural-area hydrogen-based microgrid considering multiscale and multi-energy storage systems," Applied Energy, Elsevier, vol. 334(C).
    14. Carlos A. Moreno-Camacho & Jairo R. Montoya-Torres & Anicia Jaegler, 2023. "Sustainable supply chain network design: a study of the Colombian dairy sector," Annals of Operations Research, Springer, vol. 324(1), pages 573-599, May.
    15. Amandine Herbe & Zarah Estermann & Valentin Holzwarth & Jan vom Brocke, 2024. "How to effectively use distributed ledger technology in supply chain management?," International Journal of Production Research, Taylor & Francis Journals, vol. 62(7), pages 2522-2547, April.
    16. Tan, Hong & Yan, Wei & Ren, Zhouyang & Wang, Qiujie & Mohamed, Mohamed A., 2022. "Distributionally robust operation for integrated rural energy systems with broiler houses," Energy, Elsevier, vol. 254(PC).
    17. Vlachokostas, Ch. & Michailidou, A.V. & Achillas, Ch., 2021. "Multi-Criteria Decision Analysis towards promoting Waste-to-Energy Management Strategies: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    18. Tan, Hong & Li, Zhenxing & Wang, Qiujie & Mohamed, Mohamed A., 2023. "A novel forecast scenario-based robust energy management method for integrated rural energy systems with greenhouses," Applied Energy, Elsevier, vol. 330(PB).
    19. Ju, Liwei & Lu, Xiaolong & Yang, Shenbo & Li, Gen & Fan, Wei & Pan, Yushu & Qiao, Huiting, 2022. "A multi-time scale dispatching optimal model for rural biomass waste energy conversion system-based micro-energy grid considering multi-energy demand response," Applied Energy, Elsevier, vol. 327(C).
    20. Muniyappan, Dineshkumar & Pereira Junior, Amaro Olimpio & M, Angkayarkan Vinayakaselvi & Ramanathan, Anand, 2023. "Synergistic recovery of renewable hydrocarbon resources via microwave co-pyrolysis of biomass residue and plastic waste over spent toner catalyst towards sustainable solid waste management," Energy, Elsevier, vol. 278(C).
    21. Guo, Changqiang & Hu, Hao & Wang, Shaowen & Rodriguez, Luis F. & Ting, K.C. & Lin, Tao, 2022. "Multiperiod stochastic programming for biomass supply chain design under spatiotemporal variability of feedstock supply," Renewable Energy, Elsevier, vol. 186(C), pages 378-393.
    22. O'Shea, Richard & Lin, Richen & Wall, David M. & Browne, James D. & Murphy, Jerry D, 2020. "Using biogas to reduce natural gas consumption and greenhouse gas emissions at a large distillery," Applied Energy, Elsevier, vol. 279(C).
    23. Wu, Shu, 2020. "The evolution of rural energy policies in China: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    24. Hu, Yisheng & Pang, Kang & Cai, Longhao & Liu, Zhibin, 2021. "A multi-stage co-gasification system of biomass and municipal solid waste (MSW) for high quality syngas production," Energy, Elsevier, vol. 221(C).
    25. Wang, Xinlin & Wang, Hao & Ahn, Sung-Hoon, 2021. "Demand-side management for off-grid solar-powered microgrids: A case study of rural electrification in Tanzania," Energy, Elsevier, vol. 224(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. Wang, Yongli & Guo, Lu & Wang, Yanan & Zhang, Yunfei & Zhang, Siwen & Liu, Zeqiang & Xing, Juntai & Liu, Ximei, 2024. "Bi-level programming optimization method of rural integrated energy system based on coupling coordination degree of energy equipment," Energy, Elsevier, vol. 298(C).
    2. Peiran Liang & Honghang Zhang & Rui Liang, 2025. "Cooperative Game Enabled Low-Carbon Energy Dispatching of Multi-Regional Integrated Energy Systems Considering Carbon Market," Energies, MDPI, vol. 18(4), pages 1-18, February.
    3. Hugo Guzmán-Bello & Iosvani López-Díaz & Miguel Aybar-Mejía & Jose Atilio de Frias, 2022. "A Review of Trends in the Energy Use of Biomass: The Case of the Dominican Republic," Sustainability, MDPI, vol. 14(7), pages 1-27, March.
    4. Liu, Yi & Xu, Xiao & Xu, Lixiong & Liu, Youbo & Yang, Nan & Jawad, Shafqat & Luo, Yichen & Liu, Junyong & Hu, Weihao, 2024. "Collaborative water-electricity operation optimization of a photovoltaic/pumped storage-based aquaculture energy system considering water evaporation effects," Renewable Energy, Elsevier, vol. 237(PD).
    5. Zailan, Roziah & Lim, Jeng Shiun & Manan, Zainuddin Abdul & Alwi, Sharifah Rafidah Wan & Mohammadi-ivatloo, Behnam & Jamaluddin, Khairulnadzmi, 2021. "Malaysia scenario of biomass supply chain-cogeneration system and optimization modeling development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    6. Sadeghi Darvazeh, Saeed & Mansoori Mooseloo, Farzaneh & Gholian-Jouybari, Fatemeh & Amiri, Maghsoud & Bonakdari, Hossein & Hajiaghaei-Keshteli, Mostafa, 2024. "Data-driven robust optimization to design an integrated sustainable forest biomass-to-electricity network under disjunctive uncertainties," Applied Energy, Elsevier, vol. 356(C).
    7. Zhang, Y.Q. & Chen, J.J. & Wang, Y.X. & Feng, L., 2024. "Enhancing resilience of agricultural microgrid through electricity–heat–water based multi-energy hub considering irradiation intensity uncertainty," Renewable Energy, Elsevier, vol. 220(C).
    8. Guo, Jian-Xin & Tan, Xianchun & Gu, Baihe & Zhu, Kaiwei, 2022. "Integration of supply chain management of hybrid biomass power plant with carbon capture and storage operation," Renewable Energy, Elsevier, vol. 190(C), pages 1055-1065.
    9. Han, Fengwu & Zhao, Yunlong & Zeng, Jianfeng & Zhang, Shengnan & Wu, Tianyu, 2024. "Uncertain parameters adjustable two-stage robust optimization of a rural housing integrated energy system considering biomass on-site utilization," Energy, Elsevier, vol. 296(C).
    10. Wang, Qiujie & Leng, Zihao & Tan, Hong & Mohamed, Mohamed A. & Jin, Tao, 2024. "Optimal scheduling of virtual power plants with reversible solid oxide cells in the electricity market," Renewable Energy, Elsevier, vol. 237(PC).
    11. Gao, Hongjun & Wang, Wenqin & He, Shuaijia & Tang, Zhiyuan & Liu, Junyong, 2024. "Low-carbon economic scheduling for AIES considering flexible load coordination and multiple uncertainties," Renewable Energy, Elsevier, vol. 228(C).
    12. Zhang, Huan & Duan, Xianglei & Jiang, Jianli, 2024. "Fixed rebate subsidy vs. unit price subsidy: Incentive effect on the biomass power supply chain," Energy Policy, Elsevier, vol. 187(C).
    13. Yunusoglu, Pinar & Ozsoydan, Fehmi Burcin & Bilgen, Bilge, 2024. "A machine learning-based two-stage approach for the location of undesirable facilities in the biomass-to-bioenergy supply chain," Applied Energy, Elsevier, vol. 362(C).
    14. Islam Hassanin & Matjaz Knez, 2022. "Managing Supply Chain Activities in the Field of Energy Production Focusing on Renewables," Sustainability, MDPI, vol. 14(12), pages 1-33, June.
    15. Gafti, Morteza & Sabouhi, Fatemeh & Bozorgi-Amiri, Ali & Jamili, Amin, 2023. "A multi-period location-routing model for waste-to-energy supply chain: A case study," Applied Energy, Elsevier, vol. 337(C).
    16. Tan, Hong & Wang, Yuwei & Wang, Qiujie & Lin, Zhenjia & Mohamed, Mohamed A., 2024. "Day-ahead dispatch of electricity-hydrogen systems under solid-state transportation mode of hydrogen energy via FV-IGDT approach," Energy, Elsevier, vol. 300(C).
    17. Ju, Liwei & Lv, ShuoShuo & Zhang, Zheyu & Li, Gen & Gan, Wei & Fang, Jiangpeng, 2024. "Data-driven two-stage robust optimization dispatching model and benefit allocation strategy for a novel virtual power plant considering carbon-green certificate equivalence conversion mechanism," Applied Energy, Elsevier, vol. 362(C).
    18. Senocak, Ahmet Alp & Guner Goren, Hacer, 2023. "Three-phase artificial intelligence-geographic information systems-based biomass network design approach: A case study in Denizli," Applied Energy, Elsevier, vol. 343(C).
    19. Kong, Feng & Zhang, Dongyue & Song, Minghao & Zhou, Xuecong & Wang, Yuwei, 2024. "Collaborative scheduling and benefit allocation for waste-to-energy, hydrogen storage, and power-to-gas under uncertainties with temporal relevance," Energy, Elsevier, vol. 307(C).
    20. Leonel J. R. Nunes & Sandra Silva, 2023. "Optimization of the Residual Biomass Supply Chain: Process Characterization and Cost Analysis," Logistics, MDPI, vol. 7(3), pages 1-21, August.

    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:312:y:2024:i:c:s0360544224033048. 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.