Electrification of Transportation: A Hybrid Benders/SDDP Algorithm for Optimal Charging Station Trading

TL;DR

This paper introduces a hybrid Benders/SDDP algorithm to optimize the operation and trading of comprehensive charging stations for electric and hydrogen vehicles, considering uncertain electricity prices in auction markets.

Contribution

It develops a novel two-stage stochastic programming model combined with a hybrid solution approach for efficient decision-making in charging station trading under price uncertainty.

Findings

The model effectively captures market price uncertainties and station operation dynamics.

The hybrid algorithm improves solution efficiency for complex stochastic problems.

Practical insights are provided for electricity market bidding strategies.

Abstract

This paper examines the electrification of transportation as a response to environmental challenges caused by fossil fuels, exploring the potential of battery electric vehicles and hydrogen fuel cell vehicles as alternative solutions. However, a significant barrier to their widespread adoption is the limited availability of charging infrastructure. Therefore, this study proposes the development of comprehensive charging stations capable of accommodating both battery and hydrogen vehicles to address this challenge. The energy is purchased from the day-ahead and intraday auction-based electricity markets, where the electricity price is subject to uncertainty. Therefore, a two-stage stochastic programming model is formulated while the price scenarios are generated utilizing a k-means clustering algorithm. Given the complexity of the proposed model, an efficient solution approach is developed through the hybridization of the Benders decomposition algorithm and stochastic dual dynamic programming. In the Benders master problem, day-ahead bidding variables are determined, whereas the Benders sub-problem addresses intraday bidding and charging station scheduling variables, employing stochastic dual dynamic programming to tackle its intractability. Additionally, we transform the mixed integer linear program model of the second stage problem into a linear program, confirming its validity through KKT conditions. Our model provides practical insights for making informed decisions in electricity markets based on sequential auctions. While the bidding curves submitted to the day-ahead market remain unaffected by scenarios, those submitted to the intra-day market show dependence on fluctuations in day-ahead market prices.