Design of a One-Stop Platform for on-Demand Supply of Biomass Pellet Fuel in China

Abstract

China is currently rich in biomass resources, and is in a period of energy transition, the development of biomass is the general trend. However, the development of biomass pellet fuel is still immature and faces many obstacles. At this stage, the sales of biomass pellet fuel has problems such as unclear parameters or insufficient coverage. Therefore, it is proposed to build a one-stop platform to promote the development of biomass fuel industry by using modern means to widely collect information on pellet fuel, calculate the reduction potential of pellet fuel, and build an online platform to reduce the information difference. This paper constructs a database by obtaining a large amount of information on biomass fuels through questionnaires, telephone consultations and access to information on websites. Based on the established database, Jupyter was used to analyze the number of fuel types, the provincial contribution, the fuel price distribution and the calorific value distribution. Among them, Guangdong, Shandong, Jiangsu, Hebei and other large grain provinces have the highest contribution of biomass fuels; most of the fuel types are mainly wood fuels, with wood chips, pine and redwood being the main types; the calorific value of fuels is mainly concentrated in the range of 3800-4600kcal/kg; and the price of fuels is mainly concentrated in the range of 600-1000 RMB. In order to reflect the cleanliness of biomass fuels, the article accounts for the carbon emissions of biomass fuel substitutes at different stages of their life cycle, with the aim of providing a reference for users. Eventually a one-stop platform for supply and demand of biomass fuel was established based on a database and carbon accounting methodology. The idea is to import the database into the backend of the WeChat app for retrieval, display it on the front end and sort it according to the user's choice, and give an estimate of emission reductions based on the user's purchase volume and transport distance.