Intraday imbalance optimization: incentives and impact of strategic intraday bidding behavior

Christopher Koch

doi:10.1007/s12667-021-00445-9

Abstract

Intraday markets are crucial to balance supply and demand in the very short-term, up to delivery. They are often designed as continuous auctions with a pay-as-bid pricing mechanism. While several studies assess trading strategies to balance different types of portfolios, they normally do not consider the incentives of the imbalance prices for portfolio management. This paper analyzes a strategy of taking positions in the German intraday market based on expected imbalance prices and examines its impact on system stability. Using a logistic regression model, it is possible to accurately predict the direction of the overall system balance and to apply a profitable trading strategy. For a period from 01/07/2017 to 30/06/2019, the strategy outperforms a simple approach by EUR 47 000 per MW. However, this behavior would predominantly not have been system supportive due to biased imbalance price incentives. These are asymmetric price spreads and insufficiently low imbalance prices compared to intraday prices. An efficient intraday price constraint would partly solve the problem. The overall share of system supportive imbalance positions would raise by ten percentage points. In situations with high system wide imbalances, up to three-quarters of the positions would stabilize the system. These findings are important for regulation in Germany and other countries with a single imbalance pricing as they provide an indication for crucial points of the imbalance pricing rules to incite appropriate market behavior.

Highlights

Electricity trading in European countries is done in a sequence of interrelated markets serving different purposes to managers of generation and consumption portfolios
This section presents the results of the trading strategy and the potential impact on the system balance. It starts with a discussion of the model results including model assumptions, the coefficients of the independent variables and the model accuracy. It continues by analyzing the potential profit of the trading strategy to validate it as a realistic approach for market participants
Logistic regression models do not make many of the assumptions of linear regression models that are based on ordinary least squares algorithms

Summary

Introduction

Electricity trading in European countries is done in a sequence of interrelated markets serving different purposes to managers of generation and consumption portfolios. The intraday market gives portfolio managers the opportunity to trade until a couple of minutes before delivery and react to latest information. This is crucial for portfolios dominated by fluctuating renewable sources such as wind and solar, as the forecast accuracy increases with less time to delivery [3, 4]. The intraday trading period officially starts with a quarter-hourly auction at 3 pm the day before delivery It was introduced in December 2014 and enables to trade systematic deviations to the hourly mean and scheduling in the required 15-min resolution. Gate closure of continuous trading is at 30 min before delivery with an extended period up until five minutes before delivery for trading within the same control area [29]

Methods

Results

Conclusion