Dittmer Celina, Ohnmacht Benjamin, Krümpel Johannes, Lemmer Andreas
State Institute of Agricultural Engineering and Bioenergy, University of Hohenheim, Garbenstrasse 9, 70599 Stuttgart, Germany.
Microorganisms. 2022 Apr 12;10(4):804. doi: 10.3390/microorganisms10040804.
Biogas plants have the great advantage that they produce electricity according to demand and can thus compensate for fluctuating production from weather-dependent sources such as wind power and photovoltaics. A prerequisite for flexible biogas plant operation is a suitable feeding strategy for an adjusted conversion of biomass into biogas. This research work is the first to demonstrate a practical, integrated model predictive control (MPC) for load-flexible, demand-orientated biogas production and the results show promising options for practical application on almost all full-scale biogas plants with no or only minor adjustments to the standardly existing measurement technology. Over an experimental period of 36 days, the biogas production of a full-scale plant was adjusted to the predicted electricity demand of a "real-world laboratory". Results with a mean absolute percentage error (MAPE) of less than 20% when comparing biogas demand and production were consistently obtained.
沼气厂具有很大的优势，即它们能够根据需求发电，从而弥补风力发电和光伏发电等依赖天气的能源生产的波动。沼气厂灵活运行的一个先决条件是要有合适的进料策略，以便将生物质转化为沼气的过程得到调整。这项研究工作首次展示了一种用于负荷灵活、需求导向型沼气生产的实用集成模型预测控制（MPC），结果表明，几乎所有全规模沼气厂在对现有标准测量技术进行极少调整或不调整的情况下，都有很有前景的实际应用选项。在36天的试验期内，一座全规模工厂的沼气产量被调整到一个“真实世界实验室”的预测电力需求。在比较沼气需求和产量时，始终获得平均绝对百分比误差（MAPE）小于20%的结果。
