Data-driven correlations of higher heating value for biomass, waste and their combination based on their elemental compositions

Energy Reports

Phuris Khunphakdee¹  Chaiwat Soanuch²  Benjapon Chalermsinsuwan²  Krittin Korkerd² 

[1] Boiler Department, Mechanical Maintenance Division, Electrical Generating Authority of Thailand (EGAT), 81 Moo 11, Bangkruai-Sainoi Road, Sainoi, Nonthaburi 11150, Thailand;Fuels Research Center, Department of Chemical Technology, Faculty of Science, Chulalongkorn University, 254 Phayathai Road, Wangmai, Pathumwan, Bangkok 10330, Thailand;

关键词: Artificial neural network;    Biomass;    Elemental composition;    Higher heating value;    Ultimate analysis;    Waste;   

DOI  :  

来源: DOAJ

【 摘 要 】

The biomass and waste solid fuel properties, higher heating value (HHV), are the important factor contributing to the optimization studies towards efficient thermochemical conversion processes. In this study, a new data-driven correlation models were developed for assessing the HHV of biomass and waste solid fuels as a function of the ultimate analysis or elemental compositions. An artificial neural network (ANN) method was used to connect the inputs and the outputs information thorough iterative training procedure. The models were developed and tested using 930 biomass datasets and 500 waste datasets obtained from the published literature. The commercial programming software was employed with the proper, 5-25-1 ANN architecture. The prediction ability of the obtained models was compared with those testing data with high accuracy. Accordingly, the obtained data-driven correlations were capable of predicting excellent results for all the biomass, waste and their combination datasets. In addition, the developed data-driven correlation model for the biomass-waste combination dataset was accurately enough for generally representing the solid fuel prediction. Finally, the values of weights and biases for the developed data-driven correlation model of biomass-waste combination dataset were summarized. The findings may help to provide an appropriate design and operation of the thermochemical conversion process.

【 授权许可】

Unknown