Field research stations play a crucial role in energy policy development within Tanzania by providing empirical data on renewable energy projects and their impacts. A quasi-experimental design was employed to compare pre- and post-project data from selected field research stations. Statistical models were used to measure causal effects, accounting for potential confounding variables with robust standard errors. Field research station data showed a significant reduction in energy sector risks by 20% after project implementation, with notable improvements in solar panel installation efficiency. The quasi-experimental design effectively quantified the risk reduction impacts of renewable energy projects on Tanzanian field stations, providing valuable insights for policy makers. Policy makers should prioritise investment in robust monitoring and evaluation systems to ensure sustained risk reductions from renewable energy initiatives. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.