A Monte Carlo based approach for exergo-economic modeling of solar water heater

Abstract

ABSTRACT In life-cycle costing of thermal energy systems, the basis of costing could be mass or exergy and the approach followed could be deterministic or stochastics. In thermal energy systems with end products/services such as hot air, hot water, steam etc. the value addition is due to higher exergy content; therefore, exergy is a logical basis of costing and stochastics is a practical approach capturing uncertainties of input variables. This paper proposes a novel framework named as stochastic Monte Carlo-based exergy costing (SMXC) for assessment of solar hot water systems. The annual hours of operation, maintenance cost, service life, and capital cost have been identified as highly sensitive input variables. The costs based on mass and exergy content of hot water in deterministic life-cycle costing method are estimated at 0.296 and 0.304 US cent/kg, respectively. The mean values of mass and exergy costs of hot water using Monte Carlo-based stochastics life-cycle costing method are 0.302 and 0.310 US cent/kg. A very low value (i.e. 2.4%) of the exergo-economic factor (f) for the solar water heater indicates the poor exergetic efficiency; therefore, capital investment to improve its efficiency is justified. The methodological approach can be extended to examine the probabilistic exergo-economic cost of array of thermal energy products when the parametric uncertainties play a key role.