Predicting Electricity Imbalance Prices and Volumes: Capabilities and Opportunities

Jethro Browell and Ciaran Gilbert
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Jethro Browell: School of Mathematics and Statistics, University of Glasgow, Glasgow G12 8TA, UK
Ciaran Gilbert: Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XQ, UK

Energies, 2022, vol. 15, issue 10, 1-7

Abstract: Electricity imbalance pricing provides the ultimate incentive for generators and suppliers to contract with one another ahead of time and deliver against their obligations. As delivery time approaches, traders must judge whether to trade-out a position or settle it in the balancing market at the as-yet-unknown imbalance price. Forecasting the imbalance price (and related volumes) is therefore a necessity in short-term markets. However, this topic has received surprisingly little attention in the academic literature despite clear need by practitioners. Furthermore, the emergence of algorithmic trading demands automated forecasting and decision-making, with those best able to extract predictive information from available data gaining a competitive advantage. Here we present the case for developing imbalance price forecasting methods and provide motivating examples from the Great Britain’s balancing market, demonstrating forecast skill and value.

Keywords: balancing market; imbalance; real-time market; probabilistic forecasting; electricity price forecasting (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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