Interval Fuzzy Robust Dynamic Programming for Nonrenewable Energy Resources Management with Chance Constraints

This study introduces a chance constrained interval fuzzy robust dynamic programming (CCIFRDP) approach, which can effectively reflect uncertain, dynamic and interactive features of energy-environmental management systems, as well as assist in examining the reliability of satisfying (or risk of violating) system constraints under uncertainty. Within a multi-stage context, the CCIFRDP can facilitate dynamic analysis for capacity-expansion planning under different constraint-violation risk levels. The developed method has been applied to the planning for facility expansion and energy-flow allocation within a regional energy-environment system. The results indicate that reasonable solutions for both binary and continuous variables have been generated under different levels of constraint-violation risk. The obtained interval solutions are useful in generating decision alternatives, which represent various options for environmental-economic tradeoffs. The results can be used to generate decision alternatives and help managers to identify desired energy policies under various environmental, economic, and system-reliability conditions.