Energy cogeneration study of red mulberry (Morus rubra)-based biomass

ABSTRACT

Red mulberry (Morus rubra) tree is found in many parts of the globe but its dead branches are ineffectively used in many countries for cooking and heating purposes. The literature indicates that biomass gasification study derived from red mulberry (Morus rubra) wood is not yet investigated. With this objective, in the present work, gasification characteristics of dead red mulberry (Morus rubra) wood under dry and chopped condition is assessed. A downdraft biomass gasifier powering a 10 kW generator has been used to study the producer gas generated when dried branches of dead red mulberry (Morus rubra) wood is used as fuel. Further, provisions are also provided to produce flame for cooking and other heating applications. In the present study, various parameters such as producer gas content, calorific value (CV), cold gas efficiency, equivalence ratio, and flame profiles are studied to optimize the operation of the downdraft biomass gasifier. The present study reveals that maximum CV and cold gas efficiency of the present biomass are 5.846 MJ/m³ and 68.45%, respectively, corresponding to an optimum equivalence ratio 0.296. Performance comparison of the present biomass is done against other types of biomasses reported in various literatures. It is highlighted that the present source of biomass gasification offers competitive performance with the earlier biomass resources. The present resource can be efficiently used to produce power generation and cooking in remote areas where it is currently being utilized inefficiently.

KEYWORDS:

• Cogeneration
• red mulberry biomass
• cold gas efficiency
• equivalence ratio
• gasification

Nomenclature

AAFR	=	Actual air–fuel ratio
C	=	Carbon percentage in the solid biomass
CV	=	Calorific value of producer gas
db	=	Dry basis
H	=	Hydrogen percentage in the solid biomass
HHV	=	Higher heating value of solid biomass
k	=	Number of data points
$M$	=	Molecular mass, kg/kmol
m	=	Stoichiometric mass, kg/kg of fuel
min	=	Minutes
N	=	Nitrogen percentage in the solid biomass
n	=	Number of dependent variables
O	=	Oxygen percentage in the solid biomass
$p$	=	Measured value of a data point
$\bar{p}$	=	Mean of the k number of data points
PLC	=	Programmable logic controller
S	=	Sulfur percentage in the solid biomass
SAFR	=	Stoichiometric air–fuel ratio
$u$	=	Absolute uncertainty
W	=	Total weight of different samples, g
wb	=	Wet basis
$X$	=	Mass fraction of any component in solid biomass
$Y$	=	Volume fraction of any compound in the air
y	=	Dependent variable

Greek symbols

ϕ	=	Equivalence ratio
${\eta }_{cg}$	=	Cold gas efficiency
$\theta$	=	Final result of any parameter
$\sigma$	=	Estimated population standard deviation

Subscripts

AC	=	Ash content
ADSB	=	Air-dried sample biomass
$C$	=	Carbon in solid biomass
Cru	=	Crucible
FC	=	Fixed carbon
H	=	Hydrogen in solid biomass
MC	=	Moisture content
N2	=	Nitrogen compound
O	=	Oxygen in solid biomass
O2	=	Oxygen compound
ODSB	=	Oven-dried sample biomass
Res	=	Residue
S	=	Sulfur in solid biomass
SGP	=	Specific gas production
VM	=	Volatile matter

Acknowledgments

Authors acknowledge Department of Mechanical Engineering, IIT Ropar and Panjab University, Chandigarh for providing other necessary facilities and for carrying out some chemical tests.

Additional information

Funding

Authors thankfully acknowledge the financial support provided by Science & Engineering Research Board (SERB), Department of Science & Technology, Govt. of India for sponsored project [EEQ/2016/000073] titled “Design and Development of a Solar Pond and Biomass Driven Thermoelectric Unit for Domestic Power Generation using Inverse Method.”