Stochastic Decision Making for Sustainable Energy System Selection

A sustainability enhancement is generally measurable by its environmental, economic, and socio-cultural effects. To apply this concept, this study developed and empirically tested a risk-based method for evaluating renewable energy policy. The proposed graphical matrix approach coupled with Monte Carlo simulation identifies and measures critical performance indicators at an acceptance level of reliability when comparing alternative renewable energy schemes. The mathematical model reliably prioritizes alternatives by majority voting to address uncertainty in the multi-criteria decision making process. Compared to conventional deterministic method, the stochastic approach provides more reliable estimation accuracy, decision quality, and efficiency in sustainable renewable energy decision making.