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arXiv · 2510.00744

Economic Bidding Strategy of Electric Vehicles in Real-Time Electricity Markets based on Marginal Opportunity Value

Zhen Zhu·Hongcai Zhang·Yonghua Song
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Abstract

The participation of electric vehicle (EV) aggregators in real-time electricity markets offers promising revenue opportunities through price-responsive energy arbitrage. A central challenge in economic bidding lies in quantifying the marginal opportunity value of EVs' charging and discharging decisions. This value is implicitly defined and dynamically shaped by uncertainties in electricity prices and availability of EV resources. In this paper, we propose an efficient bidding strategy that enables EV aggregators to generate market-compliant bids based on the underlying marginal value of energy. The approach first formulates the EV aggregator's power scheduling problem as a Markov decision process, linking the opportunity value of energy to the value function. Building on this formulation, we derive the probability distributions of marginal opportunity values across EVs' different energy states under stochastic electricity prices. These are then used to construct closed-form expressions for marginal charging values and discharging costs under both risk-neutral and risk-averse preferences. The resulting expressions support a fully analytical bid construction procedure that transforms marginal valuations into stepwise price-quantity bids without redundant computation. Case studies using real-world EV charging data and market prices demonstrate the effectiveness and adaptability of the proposed strategy.

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Zhen Zhu, Hongcai Zhang, Yonghua Song. 2025-10-01. Economic Bidding Strategy of Electric Vehicles in Real-Time Electricity Markets based on Marginal Opportunity Value. https://arxiv.org/abs/2510.00744

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