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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
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
Distributionally robust multi-period energy management for CCHP-based microgrids
Shi, Zhichao (author) / Liang, Hao (author) / Dinavahi, Venkata (author)
2020-09-01
oai:zenodo.org:7693903
Article (Journal)
Electronic Resource
English
DDC:
690
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