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Multi-objective stochastic-robust based selection-allocation-operation cooperative optimization of rural integrated energy systems considering supply-demand multiple uncertainties

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  • Wang, Jiangjiang
  • Zhao, Lei
  • Lu, Hao
  • Wei, Changqi

Abstract

The carbon neutrality goal places greater demands on integrated energy system (IES) in rural areas. In line with this trend, a multi-objective stochastic-robust based selection-allocation-operation cooperative optimization model is established for planning of rural IES in this paper. Firstly, this paper construct three typical IESs at three levels (user, township and user-township interaction) and make economic selection. Secondly, in order to coordinate the objectives of technology-economy-environment and solve the multiple uncertainties existing in the system, a multi-objective stochastic-robust planning model is proposed. In the model, the objective function introduces indicators such as total cost, primary energy resource efficiency and renewable energy consumption rate. Then constructing stochastic hierarchical scenarios to characterize the stochastic uncertainty of parameters in the time dimension. And introducing typical scenarios into the box sets which characterize the supply-demand sides uncertainty. Finally, a sensitivity analysis is performed to discuss the influence of robustness parameters and biogas prices. The annual total cost of the user-township interaction system is 53.8 % and 8.4 % lower than that of the other two systems, respectively. And from the allocation results of selected system, primary energy resource efficiency is 0.57, total cost is 1.81 × 106 USD and renewable energy consumption rate is 99.46 %. In addition, from the operation results, it is analyzed that the output of the equipment is perfectly balanced with the user's load. Finally, it is obtained by sensitivity analysis that uncertainty budget and biogas price have an impact on the selection of discrete equipment, the capacity of continuous equipment and the total cost. And the optimal capacity of the system under different situations is given.

Suggested Citation

  • Wang, Jiangjiang & Zhao, Lei & Lu, Hao & Wei, Changqi, 2024. "Multi-objective stochastic-robust based selection-allocation-operation cooperative optimization of rural integrated energy systems considering supply-demand multiple uncertainties," Renewable Energy, Elsevier, vol. 233(C).
    • Handle: RePEc:eee:renene:v:233:y:2024:i:c:s0960148124012278
    DOI: 10.1016/j.renene.2024.121159
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    as
    1. Onishi, Viviani C. & Antunes, Carlos H. & Fraga, Eric S. & Cabezas, Heriberto, 2019. "Stochastic optimization of trigeneration systems for decision-making under long-term uncertainty in energy demands and prices," Energy, Elsevier, vol. 175(C), pages 781-797.
    2. Wang, Pengya & Wang, Jianxiao & Jin, Ruiyang & Li, Gengyin & Zhou, Ming & Xia, Qing, 2022. "Integrating biogas in regional energy systems to achieve near-zero carbon emissions," Applied Energy, Elsevier, vol. 322(C).
    3. Ahmed, Eihab E.E. & Demirci, Alpaslan & Tercan, Said Mirza, 2023. "Optimal sizing and techno-enviro-economic feasibility assessment of solar tracker-based hybrid energy systems for rural electrification in Sudan," Renewable Energy, Elsevier, vol. 205(C), pages 1057-1070.
    4. Lu, Qing & Lü, Shuaikang & Leng, Yajun & Zhang, Zhixin, 2020. "Optimal household energy management based on smart residential energy hub considering uncertain behaviors," Energy, Elsevier, vol. 195(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. Zhu, Xi & Zeng, Bo & Dong, Houqi & Liu, Jiaomin, 2020. "An interval-prediction based robust optimization approach for energy-hub operation scheduling considering flexible ramping products," Energy, Elsevier, vol. 194(C).
    7. Ma, Tengfei & Wu, Junyong & Hao, Liangliang & Lee, Wei-Jen & Yan, Huaguang & Li, Dezhi, 2018. "The optimal structure planning and energy management strategies of smart multi energy systems," Energy, Elsevier, vol. 160(C), pages 122-141.
    8. Tostado-Véliz, Marcos & Rezaee Jordehi, Ahmad & Amir Mansouri, Seyed & Jurado, Francisco, 2022. "Day-ahead scheduling of 100% isolated communities under uncertainties through a novel stochastic-robust model," Applied Energy, Elsevier, vol. 328(C).
    9. Li, Yang & Han, Meng & Shahidehpour, Mohammad & Li, Jiazheng & Long, Chao, 2023. "Data-driven distributionally robust scheduling of community integrated energy systems with uncertain renewable generations considering integrated demand response," Applied Energy, Elsevier, vol. 335(C).
    10. Anderson, Jeffrey & Rode, David & Zhai, Haibo & Fischbeck, Paul, 2021. "Reducing carbon dioxide emissions beyond 2030: Time to shift U.S. power-sector focus," Energy Policy, Elsevier, vol. 148(PA).
    11. Das, Saborni & Basu, Mousumi, 2020. "Day-ahead optimal bidding strategy of microgrid with demand response program considering uncertainties and outages of renewable energy resources," Energy, Elsevier, vol. 190(C).
    12. Najafi, Arsalan & Homaee, Omid & Jasiński, Michał & Pourakbari-Kasmaei, Mahdi & Lehtonen, Matti & Leonowicz, Zbigniew, 2023. "Participation of hydrogen-rich energy hubs in day-ahead and regulation markets: A hybrid stochastic-robust model," Applied Energy, Elsevier, vol. 339(C).
    13. Tan, Jin & Wu, Qiuwei & Hu, Qinran & Wei, Wei & Liu, Feng, 2020. "Adaptive robust energy and reserve co-optimization of integrated electricity and heating system considering wind uncertainty," Applied Energy, Elsevier, vol. 260(C).
    14. Yan, Rujing & Wang, Jiangjiang & Wang, Jiahao & Tian, Lei & Tang, Saiqiu & Wang, Yuwei & Zhang, Jing & Cheng, Youliang & Li, Yuan, 2022. "A two-stage stochastic-robust optimization for a hybrid renewable energy CCHP system considering multiple scenario-interval uncertainties," Energy, Elsevier, vol. 247(C).
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