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- W4302028286 abstract "The combination of wireless charging roads and energy storage systems is a promising option for electric vehicle charging because of their capabilities in mitigating range anxiety of electric vehicle drivers. Wireless charging road operators can purchase electric energy by submitting price-sensitive demand bids in real-time electricity markets. Efficient bidding strategies are crucial to minimizing the energy costs for providing wireless charging services. In this study, we first propose a composite statistical model based on graph signal processing and linear regression to forecast the future locational marginal prices (LMPs) in a power network. Then an estimate of future electric load on each wireless charging road is derived by simulating its traffic flow using a point queue-based traffic flow model. An efficient price-sensitive bidding strategy for each individual wireless charging road is developed based on its LMP forecast, wireless charging load estimate, and a model predictive control framework. Our numerical example shows that the proposed price-sensitive demand bidding strategy reduces the electric energy cost for operating a wireless charging road with an energy storage system by 6% compared to a baseline bidding strategy." @default.
- W4302028286 created "2022-10-06" @default.
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- W4302028286 date "2022-12-01" @default.
- W4302028286 modified "2023-09-29" @default.
- W4302028286 title "Bidding strategy for wireless charging roads with energy storage in real-time electricity markets" @default.
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- W4302028286 doi "https://doi.org/10.1016/j.apenergy.2022.120035" @default.
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