An area gaining traction in the risk analysis world is the application of Monte Carlo simulation to environmental risk. There are numerous uncertainties in the natural world and they affect plans in any number of ways. Think of a typical construction project. What is the impact of weather, specifically inclement weather, on the progress of that project? Are the delays significant enough to trigger penalties? Could a risk assessment help determine that likelihood? Are there mitigating steps to take to better ensure the progress of the job? Could decision trees aid with the consequences and determining the best course of action? Statistical analysis would certainly provide useful data to support a well informed decision.
Specific to the area of renewable energy generation, climate plays a huge role. Variability around forecasting availability of wind or water translates to uncertainty when planning for power generation and delivery. Think of a hydro installation. What capacity should be planned? What is the minimum generation that can be guaranteed? What will long term changes yield in terms of climate shift, and the resulting impact on power generation?
Tools such as @RISK and PrecisionTree add the relevant analytical techniques to spreadsheet models which would allow you to explore these kinds of questions, develop plans around these issues and set policy for future decisions.
Palisade Training Team