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Optimal Scheduling of Source–Load Synergy in Rural Integrated Energy Systems Considering Complementary Biogas–Wind–Solar Utilization

Author

Listed:
  • Xing Long

    (School of Electrical and Information Engineering, Southwest Petroleum University, Chengdu 610500, China)

  • Hongqi Liu

    (School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China)

  • Tao Wu

    (School of Electrical and Information Engineering, Southwest Petroleum University, Chengdu 610500, China)

  • Tongle Ma

    (School of Electrical and Information Engineering, Southwest Petroleum University, Chengdu 610500, China)

Abstract

To address the issues of the low usage efficiency and illogical structure in rural regions, this study builds a rural integrated energy system (RIES) that incorporates the complementary use of biogas, wind, and light. For resolving the RIES optimum-low-carbon-economic-dispatch problem, a source–load-cooperative optimal-dispatch strategy is proposed. Firstly, a multi-energy integrated demand response (IDR) model based on time-of-use tariffs and time-varying biogas costs is established on the demand side. Secondly, power-to-gas devices are added on the supply side to optimize the system’s electricity–gas-coupling relationship and increase the wind power output space. Thirdly, an RIES-oriented carbon-trading model is constructed by considering the actual carbon emissions of gas loads and the stepped-carbon-trading mechanism. Finally, an optimal-dispatch model is built with the objective function of reducing the total energy cost, wind abandonment cost, IDR cost, and carbon emission cost, while the problem is transformed into a mixed-integer linear problem and solved using CPLEX 12.9. By setting up four scenarios for example analysis, the results show that on typical days in spring, summer, autumn, and winter, the total operating costs of the stepped-carbon-trading system (Scenario 1), taking into account the source-side power-to-gas (P2G) device and the load-side IDR, are reduced by 12.25%, 11.25%, 12.42%, and 11.56%, respectively, compared to the system without the introduction of the IDR (Scenario 3). In contrast to the system that lacks a P2G device at the source end (Scenario 2), the overall costs are decreased by 4.97%, 3.07%, 5.02%, and 5.36%, but the wind power consumption rates are increased by 11.63%, 7.93%, 11.54%, and 11.65%, respectively. Stepped emission trading (Scenario 1) reduces the total operating costs by 5.12%, 3.15%, 5.21%, and 6.84%, respectively, while reducing the biogas costs by 9.75%, 7.74%, 9.67%, and 9.57%, respectively, in comparison to traditional emission trading (Scenario 4). The example results demonstrate the economics, effectiveness, and reliability of a stepped-carbon-trading system with an integrated P2G load-side energy demand response.

Suggested Citation

  • Xing Long & Hongqi Liu & Tao Wu & Tongle Ma, 2024. "Optimal Scheduling of Source–Load Synergy in Rural Integrated Energy Systems Considering Complementary Biogas–Wind–Solar Utilization," Energies, MDPI, vol. 17(13), pages 1-28, June.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:13:p:3066-:d:1419674
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    References listed on IDEAS

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    1. Nwulu, Nnamdi I. & Xia, Xiaohua, 2017. "Optimal dispatch for a microgrid incorporating renewables and demand response," Renewable Energy, Elsevier, vol. 101(C), pages 16-28.
    2. Han, Jiashi & Zhang, Lei & Li, Yang, 2022. "Spatiotemporal analysis of rural energy transition and upgrading in developing countries: The case of China," Applied Energy, Elsevier, vol. 307(C).
    3. Fambri, Gabriele & Diaz-Londono, Cesar & Mazza, Andrea & Badami, Marco & Sihvonen, Teemu & Weiss, Robert, 2022. "Techno-economic analysis of Power-to-Gas plants in a gas and electricity distribution network system with high renewable energy penetration," Applied Energy, Elsevier, vol. 312(C).
    4. Johnson, Nathan G. & Bryden, Kenneth M., 2012. "Energy supply and use in a rural West African village," Energy, Elsevier, vol. 43(1), pages 283-292.
    5. Liu, Wenxia & Huang, Yuchen & Li, Zhengzhou & Yang, Yue & Yi, Fang, 2020. "Optimal allocation for coupling device in an integrated energy system considering complex uncertainties of demand response," Energy, Elsevier, vol. 198(C).
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