Distributionally robust multi-period energy management for CCHP-based microgrids

To improve the overall energy utilisation efficiency, the research of combined cooling, heat, and power (CCHP)-based microgrids has become prevalent recently. However, the increasing penetration of uncertain renewable generation such as wind power brings new challenges to CCHP-based microgrids energy management. In this study, the authors propose a two-stage multi-period distributionally robust energy management model for CCHP-based microgrids, and this model considers the non-anticipativity of uncertainty in dispatch process. A second-order conic representable ambiguity set is designed to capture the uncertainty of wind power. Based on linear decision rule approximation, the proposed problem is transformed into a tractable mixed-integer second-order conic programme problem. Case studies and comparison experiments are conducted in the Matlab environment with real-world data to validate the performance of the proposed approach. Particularly, the proposed method achieves a less conservative solution and smaller cost compared with a robust optimisation method with the same reliability guarantee. In addition, it is more reliable than the deterministic method which does not consider uncertainty.