Group for Research in Decision Analysis

G-2020-33

Decision tree-based optimization for flexibility management for sustainable energy microgrids

, , and

In this paper, we apply a flexibility based operational planning paradigm to microgrid (MG) energy dispatch. The classic energy dispatch problem with energy storage and dispatchable thermal generation assets requires the solution of mixed-integer optimization problems. Such approaches are not amenable to most remote MG and practical field MG implementations, where controls are rule-based and typically implemented by programmable logic controllers (PLC). Albeit such rule-based dispatch controls are always feasible, they cannot optimize fully over the availability of renewable generation and asset capacities of microgrids, especially energy storage. In this paper we propose a systematic method to generate the MG dispatch rule base with the objective of matching as much as possible the control performance obtained by full mixed-integer optimization. To achieve this we develop a rigorous control mapping method based on decision trees. Its computational efficiency is very high, a feature promising for real time in field implementation.

, 19 pages