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<p>When dispatchable biogas plants (DBPs), who operate on demand-oriented production mode, collaborate to compensate the disparity between wind/PV generation and actual demand, the overall probability of successful energy delivery for distributed energy system (DES) can be significantly enhanced. However, the mechanisms governing the aggregation of DBPs for effective load-balancing remain inadequately understood. This study combines an empirical investigation and an evolutionary game model, in which a questionnaire survey for key stakeholders identified the main factors affecting DBPs aggregation, and the game model was developed to predict DBPs diffusion dynamics within DES. Finally, a sensitivity backward deduction method is employed, in which the expected state variable values are used to infer the feasible ranges of key parameters through the established input–output relationships of the model. It indicates that the Kilowatt-hour cost of DBP, and its technical failure probability, imitation behavior coefficient exerts the most pronounced influences on the results. The proposed framework provides quantitative insights into how cost thresholds, technical reliability, and imitation effects jointly determine the large-scale adoption of DBPs within DES, offering decision support for policymakers and operators to optimize biogas-based load balancing strategies.</p> Graphical abstract <p></p>

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Revealing the Factors Affecting the Aggregation of Dispatchable Biogas Plants for Supplying Load-Balancing Power in Regional Distributed Energy Systems: A Combined Empirical Investigation and Evolutionary Game Approach

  • 期刊论文

  • 发表日期：

    2026年3月10日

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  • Yiyun Liu,
  • Yuanjie Zhang,
  • Jianjun Li,
  • Rongqi Wu,
  • Jingjing Huang

摘要

When dispatchable biogas plants (DBPs), who operate on demand-oriented production mode, collaborate to compensate the disparity between wind/PV generation and actual demand, the overall probability of successful energy delivery for distributed energy system (DES) can be significantly enhanced. However, the mechanisms governing the aggregation of DBPs for effective load-balancing remain inadequately understood. This study combines an empirical investigation and an evolutionary game model, in which a questionnaire survey for key stakeholders identified the main factors affecting DBPs aggregation, and the game model was developed to predict DBPs diffusion dynamics within DES. Finally, a sensitivity backward deduction method is employed, in which the expected state variable values are used to infer the feasible ranges of key parameters through the established input–output relationships of the model. It indicates that the Kilowatt-hour cost of DBP, and its technical failure probability, imitation behavior coefficient exerts the most pronounced influences on the results. The proposed framework provides quantitative insights into how cost thresholds, technical reliability, and imitation effects jointly determine the large-scale adoption of DBPs within DES, offering decision support for policymakers and operators to optimize biogas-based load balancing strategies.

Graphical abstract