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How electrical engine power load and feedstock moisture content affect the performance of a fixed bed gasification genset

descriptionPublicationkeyboard_double_arrow_right Article , Journal 01 Apr 2020 France Publisher:Elsevier BVJournal:Energy, volume 197, page 117,144 (issn: 0360-5442,

Authors: Huchon, Valentin; Pinta, François; Commandre, Jean-Michel; Van De Steene, Laurent;

doi: 10.1016/j.energy.2020.117144

How electrical engine power load and feedstock moisture content affect the performance of a fixed bed gasification genset

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Abstract

Abstract Performance of wood gasification genset is sensitive to the moisture content in the feedstock and the electrical load (demand of users). This study investigates the influence of these process parameters on the electrical efficiency of the genset (ηglobal), the electrical engine efficiency (ηengine), the cold gas efficiency (CGE), and the syngas composition. Experimental tests were carried out by varying the moisture content from 11% to 23% and the electrical power from 4.7 kW to 12.8 kW on a commercial gasifier equipped with precise measuring tools. The increase of the performance when the electrical load is increased or when the moisture content in the wood chips is decreased is both quantified and discussed. Such behaviour was mainly explained by differences in engine filling rates and reactor temperatures.

Country

France

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Keywords

Gazéification, P05 - Ressources énergétiques et leur gestion, P06 - Sources d'énergie renouvelable, Teneur en eau, Biomasse, Matière première, agrovoc: agrovoc:c_34000, agrovoc: agrovoc:c_24887, agrovoc: agrovoc:c_926, agrovoc: agrovoc:c_4886

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	11
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%