Thermodynamic analysis and multi-objective optimization of a new biomass-driven multi-generation system for zero energy buildings

Abstract

The current study presents and evaluates a new biomass-driven multi-generation system for zero energy building (ZEB) purpose. The system is aimed at providing a sample building’s electric power, hot water, heating, and cooling requirements throughout the year. The presented system is comprised of a biomass gasifier, an internal combustion engine, a water-lithium bromide double-effect absorption chiller, a backup boiler for hot water production, gas and hot water storage tanks, and heat exchangers. After introducing a pair of objective functions (namely, annual actual benefit, and loss of building requirements supply probability), the proposed system is optimized by using the modified non-dominated sorting Genetic Algorithm (NSGA-II). The results reveal that the proposed system is able to fully satisfy the building’s requirements and reach ZEB goal with the levelized cost of energy (LCOE) of about 0.19 $/kWh. A cost breakdown analysis shows that the highest and the lowest costs of the system are related to the purchase of the internal combustion engine (about 50% of total cost) and the purchase of heat exchangers (about 1% of total cost), respectively. Furthermore, a comprehensive sensitivity analysis is carried out to figure out the influence of some major economic factors on the systems annual benefit and LCOE. This analysis identifies generated electricity price conversion factors as the most influential parameters, and buying electricity cost as the least influential factor.

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Abbreviations

AAB:

Annual actual benefit, $

C :

Equipment investment cost, $

COP :

Chiller operational factor

E:

Electricity, W

GS tank:

Gas storage tank

H:

Enthalpy, \(kJ/kg\)

HHV:

Higher heating value, MJ/kg

i :

Interest rate, %

LCOE:

Levelized cost of energy, $/kWh

LHV:

Lower heating value, MJ/kg

M :

Molar mass, \(g/mol\)

MC :

Moisture, %

NSGA-II:

Modified non-dominated sorting Genetic Algorithm

SV :

Salvage value, $

ny :

Lifetime

r :

Number of moles

V :

Volume, \(m^{3}\)

Q :

Heating, J

c :

Cooling

es :

Selling electricity

eb :

Buying electricity

f :

Fuel

h :

Heating

HW :

Hot water

ICE :

Internal combustion engine

n :

Number of hour

Nch :

Chiller nominal power

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Correspondence to Kourosh Javaherdeh.

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Mohammadikhah, F., Javaherdeh, K. & Mahmoudimehr, J. Thermodynamic analysis and multi-objective optimization of a new biomass-driven multi-generation system for zero energy buildings. Energy Syst 12, 157–180 (2021). https://doi.org/10.1007/s12667-020-00379-8

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Keywords

  • Zero energy building
  • Multi-generation system
  • Optimization
  • Economic analysis