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.
| Original language | English |
|---|---|
| Article number | 123546 |
| Journal | Applied Energy |
| Volume | 369 |
| Number of pages | 13 |
| ISSN | 0306-2619 |
| DOIs | |
| Publication status | Published - 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Active distribution network
- Coupled transportation and power networks
- Electric transport
- Electrified road systems
- Stochastic programming
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