Data-driven distributionally robust joint chance-constrained energy management for multi-energy microgrid
نویسندگان
چکیده
Multi-energy microgrid (MEMG) has the potential to improve energy utilization efficiency. However, uncertainty caused by distributed renewable resources brings an urgent need for multi-energy co-optimization ensure secure operation. This paper focuses on distributionally robust management problem MEMG. Various flexible in different sectors are utilized mitigation, then, a data-driven Wasserstein distance-based joint chance-constrained (DRJCC) model is proposed. To make DRJCC tractable, optimized conditional value-at-risk (CVaR) approximation (OCA) formulation proposed transfer into tractable form. Then, iterative sequential convex optimization algorithm tailored reduce solution conservatism tuning OCA. Numerical result illustrates effectiveness of model. • Proposing handle spatial–temporal correlations among uncertainties. OCA tune
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ژورنال
عنوان ژورنال: Applied Energy
سال: 2022
ISSN: ['0306-2619', '1872-9118']
DOI: https://doi.org/10.1016/j.apenergy.2022.119939