Solar Energy Location by Considering Uncertainty in Providing Energy

This paper investigates the challenge of selecting optimal locations for solar energy projects by incorporating uncertainty in energy production. Traditional approaches prioritize locations with high average solar irradiance. However, this neglects the inherent variability of solar resources due to weather conditions. This work proposes a novel methodology for solar energy location selection that factors in uncertainty. We review existing literature on solar resource assessment and uncertainty modeling. The methodology utilizes historical solar irradiance data and statistical techniques to quantify the variability and risk associated with different locations. A multi-objective optimization framework is employed to find the best location that balances high energy production potential with minimized uncertainty. Numerical results are presented using real-world solar irradiance data from various locations. The proposed methodology demonstrates its effectiveness in identifying locations that offer a reliable and predictable energy supply despite the inherent uncertainty of solar resources.