Department of Technology, University of Applied Sciences Emden/Leer, Constantiaplatz 4, 26723, Emden, Germany.
Centre for Ecology and Andean Peoples, Avenida España 1550, 0401, Oruro, Bolivia.
Bioprocess Biosyst Eng. 2019 Nov;42(11):1829-1841. doi: 10.1007/s00449-019-02179-6. Epub 2019 Aug 2.
The development of systems for energy storage and demand-driven energy production will be essential to enable the switch from fossil to renewable energy sources in future. To cover the residual load rises, a rigorous dynamic process model based on the Anaerobic Digestion Model No. 1 (ADM1) was applied to analyse the flexible operation of biogas plants. For this, the model was optimised and an operational concept for a demand-driven energy production was worked out. Different substrates were analysed, both by batch fermentation and Weende analysis with van Soest method, to determine the input data of the model. The lab results show that the substrates have got different degradation kinetics and biogas potentials. Finally, the ADM1 was extended with a feeding algorithm which is based on a PI controller. Essential feeding times and quantities of available substrates were calculated so that a biogas plant can cover a defined energy demand. The results prove that a flexible operation of biogas plants with a feeding strategy is possible.
未来，从化石能源向可再生能源的转变，能源存储和需求驱动型能源生产系统的发展将是必不可少的。为了覆盖剩余的负荷增长，应用了基于厌氧消化模型 No.1（ADM1）的严格动态过程模型来分析沼气厂的灵活运行。为此，对模型进行了优化，并制定了需求驱动型能源生产的运行方案。通过分批发酵和范索斯特法的威恩分析，对不同的基质进行了分析，以确定模型的输入数据。实验室结果表明，这些基质具有不同的降解动力学和沼气潜力。最后，ADM1 扩展了一个基于 PI 控制器的进料算法。计算出了可用基质的基本进料时间和数量，以便沼气厂能够满足规定的能源需求。结果证明，采用进料策略的沼气厂的灵活运行是可行的。
