Optimization of feedstock and insulating strategies to enhance biogas production of solar-assisted biodigester system

Abstract

Assisted by solar greenhouse, the temperature of the digestion liquid can be increased by solar radiation to promote the biogas production rate in cold climate. Due to the dynamic characteristics of solar radiation, air temperature and other variable parameters jointly affect the digestion process. A novel dynamic biogas production prediction model for solar-assisted biogas digestion is developed in this study. The model integrates soil heat transfer, feeding process and covering/uncovering of greenhouse insulation quilt, and coupled with biogas anaerobic digestion kinetic model. After validated by experimental results of an actual biogas project in rural area of Xuzhou, China, the feedstock process and insulating strategies for biogas plants are optimized based on prediction model. The results show a significant increase of 55% average volumetric biogas production rate could be achieved, it indicates that optimizing operation strategy of solar assisted biogas plants has a great potential for enhancing gas production in cold winter climates with sufficient solar radiation resources, which can promote biogas applications in rural North China. The models could be used for predicting biogas production rate of passive solar-assisted biogas digester, and could also help for energy savings and renewable energy utilization in China and other countries.