Forecasting Solar Panel Electricity Generation for 50 Countries with Diffusion Models

The global shift toward renewable energy is not only a technical requirement, but also a social imperative in the face of climate change. Among the various renewable technologies, solar energy stands out as one of the most accessible and scalable. As countries intensify their efforts to decarbonize electricity systems, the ability to understand the patterns of solar adoption and project future solar generation has become increasingly important for policymakers, investors, and energy strategists. This thesis examines the diffusion of solar photovoltaic (PV) electricity generation in 50 countries during the 1980–2023. By applying innovation diffusion models, specifically the classical Bass Model (BM) and the Generalized Bass Model (GBM) with adjustments for external shocks, the aims are to forecast solar generation trajectories through 2040. These models are calibrated with empirical data and are structured to capture both gradual adoption processes and sudden accelerations caused by policy interventions or economic disruptions. Beyond forecasting, the study offers insight into how solar generation expands in diverse national contexts, highlighting the role of subsidies, technology costs, and political commitment. Such findings can inform the development of more adaptive policy frameworks and foster international cooperation to achieve a more balanced and accelerated global growth of solar energy. Ultimately, this research improves understanding of the dynamics of solar generation and highlights how its future development can be steered more deliberately to advance climate objectives, strengthen energy security, and improve economic resilience.