Bidding strategy for wireless charging roads with energy storage in real-time electricity markets

Jie Shi, Nanpeng Yu and H. Oliver Gao

Applied Energy, 2022, vol. 327, issue C, No S0306261922012922

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.

Keywords: Electric vehicle; Energy storage system; Wireless charging road; Point queue model; Electricity market; Demand bid; Optimal power flow; Model predictive control; Locational marginal price forecasting (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.apenergy.2022.120035

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