Towards intelligent cooperation of urban electric-traffic coupling network: A distributionally robust hierarchical optimization method with dependency of uncertainties
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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en
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16
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Energy, Volume 338
Abstract
With a high proportion of renewable energy connected to the grid and large-scale traffic electrification, the impact of the uncertainty of renewable energy and electric vehicles on the power grid cannot be ignored. The distributionally robust optimization method considering Wasserstein metric has been attracted much attention because of its low conservatism and risk. In this paper, in order to more accurately generate an ambiguity set that takes into account the dependency of uncertainties between renewable energy generation and traffic flow, an extended ambiguity set is proposed, and the copula set of OD pairs on traffic flow, wind and solar output is constructed. Secondly, in the process of selecting fast charging stations, considering the waiting time in line and the uncertainty of wind and solar, the electricity price of fast charging stations is formulated to guide users to charge to assist thermal power units to stabilize the uncertainty of wind and solar. The enhanced user equilibrium is constructed to reflect the effective guidance of electricity price of fast charging stations to users. A bi-level distributionally robust optimization method is proposed to obtain the expected cost in the worst scenario of the extended Wasserstein ambiguity set. Finally, simulations are carried out in two simulation systems (IEEE 33-node distribution network and Nguyen–Dupuis traffic network) and (SCE-56 node distribution network and Sioux-Falls traffic network) respectively, which finally verifies the effectiveness of this method in dealing with uncertainty, saving energy and preventing node congestion.Description
Publisher Copyright: © 2025 Elsevier Ltd
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Hou, M, Liu, X, Li, M, Li, Y, Wang, R, Li, Z & Sun, Q 2025, 'Towards intelligent cooperation of urban electric-traffic coupling network: A distributionally robust hierarchical optimization method with dependency of uncertainties', Energy, vol. 338, 138977. https://doi.org/10.1016/j.energy.2025.138977