Solar energy prediction in Cameroon

Accurate prediction of solar radiation and solar energy variables is essential for the design, operation, and performance analysis of photovoltaic systems, particularly in regions with high climatic variability such as Cameroon. Solar radiation prediction aims to estimate short-term or long-term solar availability using historical measurements, meteorological variables, and data-driven models. Reliable prediction supports improved energy yield estimation, system sizing, and operational planning, especially in locations with limited ground-based observations.

In this comparison, several solar energy prediction studies conducted in Cameroon are analyzed using a consistent set of properties. These include the prediction models employed (such as empirical formulations, machine learning methods, geospatial tools, and simulation software), the input variables used to drive the models (meteorological, geographic, or synthetic data), the length of the time series considered, and the evaluation metrics applied to quantify predictive accuracy. The comparison highlights how different modeling approaches perform across diverse locations and data conditions, providing a structured overview of solar radiation and solar energy prediction efforts in Cameroon.