A stochastic approach to feasibility analysis of boiler replacement in educational buildings in Extremadura (Spain)

• Published in: Energy, sustainability and society Vol. 12; no. 1; pp. 1 - 14
• Main Authors: Garrido-Píriz, Pablo, Sánchez-Barroso, Gonzalo, García-Sanz-Calcedo, Justo
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 19-09-2022; Springer Nature B.V; BMC
• Subjects: Accuracy; Agricultural wastes; Agroforestry; Biomass; Biomass energy; Boilers; Buildings; Diesel fuels; Economic analysis; Economics and Management; Education; Educational buildings; Emissions; Empirical analysis; Energy; Energy demand; Energy efficiency; Energy Policy; Energy utilization; Environmental education; Feasibility studies; Fuel oils; Fuels; GHG emissions; Greenhouse effect; Greenhouse gases; Industrial wastes; Monte Carlo method; Monte Carlo simulation; Oil; Payback periods; Predictions; Regression analysis; Regression models; Renewable and Green Energy; Standard deviation; Statistical analysis; Stochastic processes; Stochasticity; Sustainability; Sustainable Development; Spain; GHG emissions; Monte Carlo method; Biomass; Educational buildings; Sustainability
• ISSN: 2192-0567; 2192-0567
• DOI: 10.1186/s13705-022-00367-z

Background
Energy efficiency in buildings must be increased in order to reduce both energy intensity and greenhouse gas emissions. This study proposed the replacement of existing diesel boilers with biomass boilers, using four fuels (bulk pellets, wood chip, olive kernel and milled nutshell) to meet the energy demands of educational buildings in the region of Extremadura (Spain). High uncertainty surrounds biomass price prediction affecting the accuracy of economic feasibility analyses; thus, stochastic processes are suitable to support an improvement in the accuracy of predictions. The objective of the study is to demonstrate the feasibility of replacing diesel boilers with biomass boilers in order to revalorize agroforestry residues.
Results
A stochastic simulation of the feasibility of replacing oil-fired boilers with biomass-fired boilers was carried out in this research. Up to 20 million possible scenarios of 10 years of fuel price evolution were simulated by Monte Carlo method based on empirical price trends data. Regression models were built to relate Net Present Values with discount rates, whose statistical dependency was significant. Predictions on financial indicators showed biomass fuels as the most profitable investment, rather than fuel oil. Specifically, in this study, milled nutshell was found the most profitable fuel in the simulation runs, with Net Present Value = 27,151.09 € (standard deviation = 7939.88 €) and Internal Rate of Return = 16.9% (standard deviation = 3.4%).
Conclusions
Continuing to use oil-fired boilers costs more than the purchase and operation of new biomass-fired boilers, since the latter produce a higher cumulative cash flow than the initial investment within the next years. The payback period lies within the range of 4 to 6 years depending on the type of biomass fuel. Getting on the path to sustainability in education buildings can reduce up to 94.4% GHG emissions. This research contributes to promoting the use of low-emission fuels to meet the energy demand of educational buildings. Its results will have a positive effect in the region of Extremadura (Spain), as it boosts the appreciation of agro-industrial waste and economically strengthens the sector.