Erik Dahlquist
School of Sustainable Development of Society and Technology, Mälardalen University (MDH), Sweden
Muhammad Naqvi
School of Sustainable Development of Society and Technology, Mälardalen University (MDH), Sweden
Eva Thorin
School of Sustainable Development of Society and Technology, Mälardalen University (MDH), Sweden
Jinyue Yan
School of Sustainable Development of Society and Technology, Mälardalen University (MDH), Sweden
Konstantinos Kyprianidis
School of Sustainable Development of Society and Technology, Mälardalen University (MDH), Sweden
Philip Hartwell
BioRegional MiniMills (UK) Ltd., United Kingdom
Ladda ner artikelhttp://dx.doi.org/10.3384/ecp17142885Ingår i: Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016
Linköping Electronic Conference Proceedings 142:130, s. 885-889
Publicerad: 2018-12-19
ISBN: 978-91-7685-399-3
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
The energy situation in both process industries and power plants is changing. It is becoming interesting to perform system analysis on how to integrate gasification into chemical recovery systems in the pulp & paper industry and into the CHP systems in power plant applications to complement with production of chemicals aside of heat and power. The potential chemicals are methane, hydrogen, and methanol. It is also interesting to estimate the potential to introduce combined cycles with gas turbines and steam turbines using both black liquors and other type of biomass like pellets, wood chips etc. To perform such type of analysis, it is vital to have relevant input data on what gas composition we can expect from running different types of feedstock. In this paper, we focus on black liquors as feedstock for integrated gasification systems. The experimental results are correlated into partial least squares models to predict major composition of the synthesis gas produced under different conditions. These quality prediction models are then combined with physical models using Modelica for the investigation of dynamic energy and material balances for complete plants. The data can also be used as input to analysis using e.g. ASPEN plus and similar system analysis tools.
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