Predicting electricity imbalance prices and volumes: capabilities and opportunities

Browell, J. and Gilbert, C. (2022) Predicting electricity imbalance prices and volumes: capabilities and opportunities. Energies, 15(10), 3645. (doi: 10.3390/en15103645)

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.

• Item Type: Articles
• Additional Information: This work was funded by the EPSRC Supergen Energy Networks Hub (EP/S00078X/1), the EPSRC Innovation Fellowship held by JB (EP/R023484/1 and EP/R023484/2), the Energy Technology Partnership, and Scottish Power, SSE, and University of Strathclyde through the latter’s Technology and Innovation Centre Low Carbon Power and Energy program.
• Keywords: Balancing market, imbalance, real-time market, probabilistic forecasting, electricity price forecasting.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Browell, Dr Jethro

Creator Roles

Browell, J.: Conceptualization, Methodology, Formal analysis, Investigation, Resources, Writing – original draft, Writing – review and editing, Visualization, Supervision, Project administration, Funding acquisition

• Authors: Browell, J., and Gilbert, C.
• College/School: College of Science and Engineering > School of Mathematics and Statistics > Statistics
• Journal Name: Energies
• Publisher: MDPI
• ISSN: 1996-1073
• ISSN (Online): 1996-1073
• Published Online: 16 May 2022
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in Energies 15(10): 3645
• Publisher Policy: Reproduced under a Creative Commons License

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
315958		System-wide Probabilistic Energy Forecasting	Jethro Browell	Engineering and Physical Sciences Research Council (EPSRC)	EP/R023484/2	M&S - Statistics