Online Energy Storage Arbitrage under Imperfect Predictions: A Conformal Risk-Aware Approach

Fuente: arXiv
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Hauptverfasser: Wu, Yiqian, Yi, Ming, Xu, Bolun, Anderson, James
Format: Preprint
Veröffentlicht: 2025
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author Wu, Yiqian
Yi, Ming
Xu, Bolun
Anderson, James
author_facet Wu, Yiqian
Yi, Ming
Xu, Bolun
Anderson, James
contents This work proposes a conformal approach for energy storage arbitrage to control the downside risk arising from imperfect price forecasts. Energy storage arbitrage relies solely on predictions of future market prices, while inaccurate price predictions may lead to significant profit losses. Based on conformal decision theory, we describe a controller that dynamically adjusts decision conservativeness through prediction sets without distributional assumptions. To enable online calibration when online profit loss feedback is unobservable, we establish that a temporal difference error serves as a measurable proxy. Building on this insight, we develop two online calibration strategies: prediction error-based adaptation targeting forecast accuracy, and value error-based calibration focusing on decision quality. Analysis of the conformal controller proves bounded long-term risk with convergence guarantees in temporal difference error, which further effectively manages risk exposure in potential profit losses. Case studies demonstrate superior performance in balancing risk and opportunity compared to benchmarks under varying forecast conditions.
format Preprint
id arxiv_https___arxiv_org_abs_2511_01032
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Online Energy Storage Arbitrage under Imperfect Predictions: A Conformal Risk-Aware Approach
Wu, Yiqian
Yi, Ming
Xu, Bolun
Anderson, James
Systems and Control
Optimization and Control
This work proposes a conformal approach for energy storage arbitrage to control the downside risk arising from imperfect price forecasts. Energy storage arbitrage relies solely on predictions of future market prices, while inaccurate price predictions may lead to significant profit losses. Based on conformal decision theory, we describe a controller that dynamically adjusts decision conservativeness through prediction sets without distributional assumptions. To enable online calibration when online profit loss feedback is unobservable, we establish that a temporal difference error serves as a measurable proxy. Building on this insight, we develop two online calibration strategies: prediction error-based adaptation targeting forecast accuracy, and value error-based calibration focusing on decision quality. Analysis of the conformal controller proves bounded long-term risk with convergence guarantees in temporal difference error, which further effectively manages risk exposure in potential profit losses. Case studies demonstrate superior performance in balancing risk and opportunity compared to benchmarks under varying forecast conditions.
title Online Energy Storage Arbitrage under Imperfect Predictions: A Conformal Risk-Aware Approach
topic Systems and Control
Optimization and Control
url https://arxiv.org/abs/2511.01032