SPIE Journal Paper | 13 September 2024
KEYWORDS: Electroluminescence, Solar energy, Solar cells, Photovoltaics, Monte Carlo methods, Nanooptomechanical systems, Renewable energy, Power consumption, Carbon monoxide, Mathematical optimization
Thermophotovoltaics (TPV) is a technology that converts heat to electricity using a thermal emitter and a matched photovoltaic (PV) cell. TPV is becoming increasingly popular due to its advantages of silent power generation, higher power density (>2.5 W/cm2), reduced cost, no moving parts (thus, low maintenance costs), reaching full power in less time as compared to turbines, operating at high temperatures, and suitability for long-duration energy storage applications. This study conducts a techno-economic analysis (TEA) of a solar energy conversion (using TPV) and storage system (using phase-change materials). We optimize the levelized cost of consumed energy (LCOE) and electricity (LCOEel) using the Nelder-Mead algorithm for four scenarios (as identified in the reference study). These scenarios differ in nominal-weighted average cost of capital (WACCnom), fuel and electricity inflation rate, and capital cost factor (CAPEX) of high-temperature energy storage (HTES), power generation unit (PGU), and PV systems. We perform a sensitivity analysis that predicts a modest decrease in LCOE and LCOEel from the mean values of $0.038/kWh and $0.128/kWh, respectively. We perform a Monte Carlo uncertainty assessment and fit a probability distribution based on input variables’ historical data from the literature. The fitted probability distribution for outputs (mean, the standard deviation in brackets) is LCOE ($/kWh)—general extreme value (0.035, 0.009), and LCOEel ($/kWh)—t (0.132, 0.016). The reduced mean values for the optimized system indicate a massive potential for TPV to be economically feasible; however, the LCOEel is higher than the current average electricity price of $0.124/kWh. The box plot shows that lifetime, PV CAPEX, inflation rate, natural gas price, and WACCnom significantly impact LCOE, and future research focused on them would lead to a better adoption of TPV technology.
