Abstract
The solar energy share in Sweden will grow up significantly in next a few decades. Such transition offers not only great opportunity but also uncertainties for the emerging solar photovoltaic/thermal (PV/T) technologies. This chapter therefore aims to conduct a techno-economic evaluation of a reference solar PV/T concentrator in Sweden for building application. An analytical model is developed based on the combinations of Monte Carlo simulation techniques and multi energy-balance/financial equations, which takes into account of the integrated uncertainties and risks of various variables. In the model, 11 essential input variables, i.e. average daily solar irradiance, electrical/thermal efficiency, prices of electricity/heating, operation & management (OM) cost, PV/T capital cost, debt to equity ratio, interest rate, discount rate, and inflation rate, are considered, while the economic evaluation metrics, such as levelized cost of energy (LCOE), net present value (NPV), and payback period (PP), are primarily assessed. According to the analytical results, the mean values of LCOE, NPV and PP of the reference PV/T connector are observed at 1.27 SEK/kW h (0.127 €/kW h), 18,812.55 SEK (1881.255 €) and 10 years during its 25 years lifespan, given the project size at 10.37 m2 and capital cost at 4482–5378 SEK/m2 (448.2–537.8 €/m2). The positive NPV indicates that the investment on the selected PV/T concentrator will be profitable as the projected earnings exceeds the anticipated costs, depending on the NPV decision rule. The sensitivity analysis and the parametric study illustrate that the economic performance of the reference PV/T concentrator in Sweden is mostly proportional to solar irradiance, debt to equity ratio and heating price, but disproportionate to capital cost and discount rate. Together with additional market analysis of PV/T technologies in Sweden, it is expected that this chapter could clarify the economic situation of PV/T technologies in Sweden and provide a useful model for their further investment decisions, in order to achieve sustainable and low-carbon economics, with an expanded quantitative discussion of the real economic or policy scenarios that may lead to those outcomes.
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