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Comparative Analysis of Typical Low Rank Coal Pyrolysis Technology Based on a Nonlinear Programming Model

Author:
Huang, Yi, Li, Wen-ying, Wu, Guo-sheng, Feng, Jie, Yi, Qun
Source:
Energy & Fuels 2017 v.31 no.11 pp. 12977-12987
ISSN:
1520-5029
Subject:
energy, feedstocks, furnaces, lignite, models, oils, pyrolysis
Abstract:
A nonlinear programming (NLP) model has been established to describe the process of low rank coal pyrolysis, and the model was validated through comparison with pilot or semi-industry technologies. Results showed good agreement with actual production values, suggesting that the model can be regarded as a general one for simulating low rank coal pyrolysis. On the basis of this model, the products’ distributions and energy penalties can be obtained from the coal pyrolysis process. In this study, the NLP model was used to simulate typical five pyrolysis processes such as the Toscoal process, Lurgi–Ruhrgas process, Char Oil Energy Development technology, Dalian University of Technology process, and Multistage Rotary Furnace technology from China Coal Research Institute, and Hulunbuir lignite was taken as a coal sample. Combined with the simulation results from the NLP model, effects of the key parameters on the performance of the pyrolysis technologies are investigated and a comprehensive evaluation in terms of techno-economic performance is completed, from which the most suitable pyrolysis technologies for the Hulunbuir lignite feedstock are the Toscoal and Lurgi–Ruhrgas processes. All of the above work is beneficial for assisting the selection of the optimal pyrolysis technology for a coal feedstock with different composition features.
Agid:
5860673