Coordination of coupled electrified road systems and active power distribution networks with flexibility integration
Arsalan Najafi,
Georgios Tsaousoglou,
Kun Gao and
Omkar Parishwad
Applied Energy, 2024, vol. 369, issue C, No S0306261924009292
Abstract:
Electric road systems (ERS) constitute a promising technology for mobile charging and relieving mandatory stops to recharge electric vehicles. However, the ERS operation is constrained by the limitations of the Power Distribution Network (PDN) that provides electricity. This study proposes a integrated optimization of a coupled ERS-PDN system (including traffic assignment and power flow modeling), in the presence of self-interested electric vehicle drivers, diverse flexibility resources and uncertainty of energy supplies (e.g. uncertainty from renewable energy). The security of the PDN while supporting ERS can be ensured by using active and flexible energy storage and flexible power loads. A semi-dynamic model is adopted for the traffic assignment. A stochastic bi-level optimization based on Stackelberg game under uncertainty is proposed to model the joint optimization problem to minimize the general cost of coupled ERS-PDN system and maximize the profit of the energy flexibility provider. Then, the Karush Kuhn Tucker conditions are deployed to convert the bi-level model to the equivalent single level model. The results demonstrate the effectiveness and benefits of the proposed framework using numerical experiments. The results show that the proposed optimization can reduce the burden of an ERS on the underlying PDN in improving the violated voltage by 3.66%, demonstrating the effect of joint consideration of diverse sources of flexibility.
Keywords: Electric transport; Active distribution network; Coupled transportation and power networks; Electrified road systems; Stochastic programming (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:369:y:2024:i:c:s0306261924009292
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DOI: 10.1016/j.apenergy.2024.123546
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