Energies (Sep 2022)

Simulation Tool for the Development of a Staged Combustion Pellet Stove Controller

  • Daniel Lustenberger,
  • Joris Strassburg,
  • Tom Strebel,
  • Fabienne Mangold,
  • Timothy Griffin

DOI
https://doi.org/10.3390/en15196969
Journal volume & issue
Vol. 15, no. 19
p. 6969

Abstract

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Optimizing the combustion control concepts on a pellet stove with very low heat output is time-consuming and costly. In order to shorten the required laboratory test time, a 0-D transient tool was developed within the ERA-NET project “LowEmi-MicroStove”, which simulates a 4 kW pellet stove with staged combustion and heat transfer. This approach was chosen in order to greatly simplify the description of the combustion processes and so reduce the computational complexity and simulation time. The combustion of a bed of pellets is modeled as a superposition of the combustion cycles of individual pellets, assuming no interactions between pellets. A test setup was developed and used to determine the ignition and burning cycle of individual pellets. The description of the CO emissions behavior is based upon an empirically grounded relation which is in turn based on the air/fuel ratio and the combustion chamber temperature. For the validation of the 0-D simulation results, a test rig for a 4 kW pellet stove was built. Despite its simplistic approach, good agreement was found between the simulation and 4 kW pellet stove test results for the mean values and temporal fluctuations of flue gas temperature and oxygen and carbon monoxide content during start up, stable operation and load changes. The simulation could thus be used to quantify the effect of air flow rates and distribution as well as load changes on performance and draw conclusions regarding different process control strategies. A control strategy which can operate the stove at high temperatures near the air stoichiometric limit with acceptable CO emissions has been proven to be the most promising. Additionally, the model can be used to quantify the effects of variations in other process parameters, for example the impact of fluctuations in the pellet feed. Due to its effectiveness and simplicity, this model approach can be applied for the development of control strategies for other staged, pellet combustion systems.

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