Ciaran O’Connor (CRT AI), Andrea Visentin (Insight UCC), Steve Prestwich (Insight UCC)

Leveraging Machine Learning to Optimise Electricity Trading and Curtailment Reduction

As renewable energy continues to grow in importance, managing the real-time balance of electricity supply and demand has become increasingly challenging. Ciaran’s research focuses on developing statistical and machine learning models for electricity price forecasting in the Irish electricity markets, particularly the Day-Ahead Market and the Balancing Market, where the Balancing Market poses great potential to address the issues surrounding curtailments of renewable energy.

Under the guidance of Dr Steve Prestwich and Dr Andrea Visentin, Ciaran explores how accurate price forecasting and optimised trading strategies can incentivise operators of energy storage systems (ESS) to reduce curtailments. By storing excess renewable energy during low-demand periods, ESS can help improve grid efficiency while reducing economic losses caused by curtailment. Collaborating with Joseph Collins from UCC’s School of Mathematical Sciences, Dr Mohamed Bahloul from Tyndall National Institute and Prof. Roberto Rossi from the University of Edinburgh, the team has been improving both point and probabilistic forecasting, integrating them with trading strategies to improve participants’ operations in the Balancing Market.

By integrating quantile-based forecasting with high-frequency trading strategies, the research demonstrates how ESS operators can maximise arbitrage opportunities, increasing profitability while minimising the curtailment of renewable energy. Larger battery storage systems, in particular, show the potential to mitigate market volatility and ensure that surplus renewable energy is effectively used. This research has significant implications for improving renewable energy integration, increasing market liquidity and supporting the economic viability of ESS. Ultimately, the work aims to align financial incentives with grid reliability, contributing to a more sustainable and efficient energy system.