Forecasts Plus Assessments of Renewable Generation Performance, the Effect of Earth’s Geographic Location on Solar and Wind Generation

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Solar and wind resources are critical for the global transition to net-zero emission energy systems. However, their variability and unpredictability pose challenges for system reliability, often requiring fossil fuel-based backups or energy storage solutions. The mismatch between renewable energy generation and electricity demand necessitates analytical methods to ensure a reliable transition. Sole reliance on single-year data is insufficient, as it does not account for interannual variability or extreme conditions. This paper explores probabilistic modeling as a solution to more accurately assess renewable energy availability. A 22-year dataset is used to generate synthetic data for solar irradiance, wind speed, and temperature, modeled using statistical probability distributions. Monte Carlo simulations, run 93 times, achieve 95% confidence and confidence levels, providing reliable assessments of renewable energy potential. The analysis finds that during Dunkelflaute periods, in high-solar and high-wind areas, DF events average 20 h in the worst case, while low-resource regions may experience DF periods lasting up to 48 h. Optimal energy mixes for these regions should include 15–20% storage and interconnections to neighboring areas. Therefore, stochastic consideration and geographic differentiation are essential analyses to address these differences and ensure a reliable and resilient renewable energy system.