Multi-granularity source-load-storage cooperative dispatch based on combined robust optimization and stochastic optimization for a highway service area micro-energy grid

Yuguang Song, Mingchao Xia, Liu Yang, Qifang Chen and Su Su

Renewable Energy, 2023, vol. 205, issue C, 747-762

Abstract: Integrating renewable energy into planning and operation of transportation infrastructures can help to promote the various sector collaborative decarbonization. For the highway service area micro-energy grid (HSAMEG), its optimization lacks the source-load-storage cooperation and the modeling that considers both accuracy and complexity, and is hard to balance reliability and flexibility due to uncertainties in renewable energy and charging-demand. For these issues, a novel dispatch is proposed to balance the dispatch reliability and flexibility, and the model accuracy and complexity by combining advantages of robust and stochastic optimizations and applying the multi-granularity modeling. First, the source-load-storage configuration is established. Then the multi-granularity model is developed by fine-grained model based on the operating characteristics and coarse-grained model based on the equivalent energy storage characteristics. Finally, based on distribution characteristics of online-optimization forecast-errors, a multi-granularity source-load-storage cooperative dispatch combining robust optimization and stochastic optimization is proposed. The simulation results show that the source-load-storage collaboration increases the self-contained objective by 10%. Compared with robust optimization, the proposed strategy enhances the economic objective by 17% and the self-contained objective by 16.2%. Compared with stochastic optimization, the proposed strategy improves the computation efficiency by over 5 times and the self-contained objective by 8.8% without constraint violations.

Keywords: Decarbonization of transportation; Operation method optimization; Multi-granularity modeling; Uncertainty (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:205:y:2023:i:c:p:747-762

DOI: 10.1016/j.renene.2023.02.006

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