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/ecp17142872Ingår 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 142:128, s. 872-877
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 and it is of interest to investigate new polygeneration solutions combining production of chemicals with the production of power and heat. Examples of such chemicals are methane, hydrogen, and methanol etc. Integration of gasification into chemical recovery systems in the pulp and paper production systems and into the combined heat and power (CHP) systems in power plant applications are among the possible polygeneration systems. It is also interesting to look at the potential to introduce combined cycles with gas turbines and steam turbines as a complement. To perform such analysis, it is important to have relevant input data on what gas composition we can expect from running different type of feed stock. In this paper, we focus on the wood pellets. Experimental results are correlated into partial least squares models to predict major composition of the synthesis gas produced under different operating conditions. The quality prediction models then are combined with physical models using Modelica for investigation of dynamic energy and material balances for large 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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