Novel thermodynamic efficiency indices for choosing an optimal location for large-scale photovoltaic power generation

Abstract Sustainable energy is a current key priority across the globe. Hence, renewable energy sources have been widely accepted as potential substitutes for fossil fuels in the existing energy infrastructures. A recent report showed that photovoltaic power generation constituted around 100 GW out of 2378 GW of the global renewable power capacity installed in 2018. Consequently, various researchers are investigating how the increasing utilisation of photovoltaics can be handled in order to reduce future environmental impacts; whilst leveraging their operational zero-emission. From a circular economic paradigm, recycling, reuse and reduction strategies are often adopted to improve the sustainability of systems. This study proposes novel thermodynamic efficiency indices as a resources reduction strategy. By selecting an optimal location for large-scale photovoltaic power generation (LSPPG), the same amount of resources (such as land space, materials, energy) will achieve higher utilisation efficiency. In this study, actual two-year solar radiation and temperature data were sourced from Nigerian Meteorological Agency, Abuja. A probability distribution modeling was used to generate statistical mean values for solar radiation and temperature based on the classical almost sure central limit theory. Then, Photovoltaic modeling and simulation code was used to simulate the power generation characteristics of the LSPPG. Comparative analyses of the results for a 5 MW (MW) LSPPG showed that statistical mean value of power generation, energy efficiency index and exergy efficiency index range from 0.76 to 0.99 MW, 1.315 to1.254 and 1.298 to1.237, respectively, across the locations studied. Overall, the thermodynamic efficiency indices can complement the current laboratory-based rating of the photovoltaic modules in order to establish the environmental, economic and policy rationales for sitting a LSPPG. This would ultimately improve the cradle-to-cradle management of LSPPG installations based on resources reduction strategy.