The use of solar photovoltaic (PV) systems have expanded rapidly the last decade and today’s market includes several different solar utilizations, where floating PV is one of them. Previous studies have shown how floating PV systems increase the PV efficiency and at the same time reduce the water evaporation. The purpose of this study is to evaluate and optimize energy solutions using floating PV systems for a shrimp farm cultivation in Thailand, where the technical, environmental and economic aspects will be included. The optimizations have been done in the open source model OptiCE, where genetic algorithm (AG) have been used to maximize the renewable reliability and minimize the Levelized Costs of Electricity (LCOE). In order to find the optimal renewable solution for the investigated shrimp farm, four scenarios have been compared considering different PV system combinations. The simulated results showed how the scenarios considering floating PV system generated a higher reliability than the scenarios considering ground-mounted PV system. The scenario considered tracking PV system increased the system´s renewable reliability compared to fixed PV system. However the shrimp farm is connected to the national electric grid or not will have a huge impact on the LCOE due to the low electric price and the implemented feed-in-tariff (FIT) program. The size of the installed PV capacity significantly affects the reliability results were the capacity of 200 kWp reaches a reliability of almost 100%. The optimal solution for the investigated shrimp farm to become independent is therefore to install a combined floating PV and battery storage system.

This study aims to develop a simulation and optimisation tool for bifacial photovoltaic (PV) modules based on the open-source code OptiCE and evaluate dynamic and static albedo impact on a bifacial PV system. Further, a review of the market price development of bifacial PVs' and an optimisation to maximise energy output was conducted. Two case studies with bifacial PV modules, a single-axis tracker in Denver, USA, and a vertical and a tilted system installed at a farm outside Västerås, Sweden, were analysed in this study. The results showed that an hourly dynamic albedo value could provide more accurate simulation results of the rear side irradiance for the bifacial single-axis tracker than a static albedo value. The developed model showed an R2 accuracy of 93% and 91% for the front and rear sides, respectively, when simulated with an hourly albedo value for the bifacial single-axis tracker system. The optimisation was based on weather data from 2020. The results showed that the tilted reference system could increase its energy output by 8.5% by adjusting its tilt from 30° to 54° and its azimuth angle from 0 to -39°. In contrast, the vertical system would increase its energy output by 2.1% by rotating the azimuth angle from -90° to -66°. Conclusions that could be drawn are that bifacial PV price has closed in on the high-performance monofacial PV price the last five years and may continue to decrease in the coming years. Further, it was concluded that detailed dynamic albedo values lead to more accurate simulations of the ground-reflected irradiance. The availability of measured albedo data at the location is essential when the ground-reflected irradiance stands for a significant share of the irradiance. It was determined that during 2020 the optimal configurations of a vertical and tilted bifacial PV system in Västerås would save 11 300 SEK by consuming self-produced electricity and earn 11 600 SEK from selling the surplus of electricity for the farm outside Västerås.