Optimising quantile-based trading strategies in electricity arbitrage

Efficiently integrating renewable resources into electricity markets is vital for addressing the challenges of matching real-time supply and demand while mitigating revenue losses caused by curtailments. To address this challenge effectively, the incorporation of storage devices can enhance the reliability and efficiency of the grid, improving market liquidity and reducing price volatility. In short-term electricity markets, participants face numerous options, each presenting unique challenges and opportunities, with trading strategies fundamental towards maximising profits. This study explores the optimisation of day-ahead and balancing market trading in the Irish electricity market from 2019 to 2022, leveraging quantile-based forecasts. Employing three trading approaches with practical constraints, our research evaluates trading strategies, increases trading frequency, and employs flexible timestamp orders. Our findings underscore the profit potential of simultaneous participation in both day-ahead and balancing markets, especially with larger battery storage systems; despite increased costs and narrower profit margins associated with higher-volume trading, with the implementation of dynamic dual-market strategies playing a significant role in maximising profits and addressing market challenges. Finally, we evaluate the economic viability of four commercial battery storage systems through scenario analysis, showing that larger batteries achieve shorter returns on investment. • Proposing high-frequency quantile trading strategies for electricity markets. • Transparent framework for quantile forecast generation and trading implementation. • Simultaneous participation in Day-Ahead and Balancing Markets enhances profitability. • Scenario analysis of battery storage systems operating in the electricity markets.

Authors

Institutions

Publication Details

Journal
Energy and AI
Published
2025-01-27
DOI
https://doi.org/10.1016/j.egyai.2025.100476
Citations
5
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
15.66
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimising quantile-based trading strategies in electricity arbitrage

Steven Prestwich, Andrea Visentin, Ciaran O’Connor, Joseph Collins
5 citations
Energy and AI
Market Dynamics and Volatility
15.66
article

Optimising quantile-based trading strategies in electricity arbitrage

Steven Prestwich, Andrea Visentin, Ciaran O’Connor, Joseph Collins
article en
5 citations

Abstract

Efficiently integrating renewable resources into electricity markets is vital for addressing the challenges of matching real-time supply and demand while mitigating revenue losses caused by curtailments. To address this challenge effectively, the incorporation of storage devices can enhance the reliability and efficiency of the grid, improving market liquidity and reducing price volatility. In short-term electricity markets, participants face numerous options, each presenting unique challenges and opportunities, with trading strategies fundamental towards maximising profits. This study explores the optimisation of day-ahead and balancing market trading in the Irish electricity market from 2019 to 2022, leveraging quantile-based forecasts. Employing three trading approaches with practical constraints, our research evaluates trading strategies, increases trading frequency, and employs flexible timestamp orders. Our findings underscore the profit potential of simultaneous participation in both day-ahead and balancing markets, especially with larger battery storage systems; despite increased costs and narrower profit margins associated with higher-volume trading, with the implementation of dynamic dual-market strategies playing a significant role in maximising profits and addressing market challenges. Finally, we evaluate the economic viability of four commercial battery storage systems through scenario analysis, showing that larger batteries achieve shorter returns on investment. • Proposing high-frequency quantile trading strategies for electricity markets. • Transparent framework for quantile forecast generation and trading implementation. • Simultaneous participation in Day-Ahead and Balancing Markets enhances profitability. • Scenario analysis of battery storage systems operating in the electricity markets.

Energy and AIVol. 20
University College Cork (IE)
Openalex Percentile: Top 2%
Market Dynamics and Volatility
15.66
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.