Energy Storage Arbitrage in Two-settlement Markets: A Transformer-Based Approach
<|reference_start|>Energy Storage Arbitrage in Two-settlement Markets: A Transformer-Based Approach: This paper presents an integrated model for bidding energy storage in day-ahead and real-time markets to maximize profits. We show that in integrated two-stage bidding, the real-time bids are independent of day-ahead settlements, while the day-ahead bids should be based on predicted real-time prices. We utilize a transformer-based model for real-time price prediction, which captures complex dynamical patterns of real-time prices, and use the result for day-ahead bidding design. For real-time bidding, we utilize a long short-term memory-dynamic programming hybrid real-time bidding model. We train and test our model with historical data from New York State, and our results showed that the integrated system achieved promising results of almost a 20\% increase in profit compared to only bidding in real-time markets, and at the same time reducing the risk in terms of the number of days with negative profits.<|reference_end|>
@article{alghumayjan2024energy,
    title={Energy Storage Arbitrage in Two-settlement Markets: A Transformer-Based
  Approach},
    author={Saud Alghumayjan, Jiajun Han, Ningkun Zheng, Ming Yi, Bolun Xu},
    journal={arXiv preprint arXiv:2404.17683},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.17683},
    primaryClass={math.OC cs.GT cs.LG cs.SY eess.SY}
}