Risk Constrained Trading Strategies for Stochastic Generation with a Single-Price Balancing Market

TL;DR

This paper develops risk-aware trading strategies for stochastic energy generators in single-price balancing markets, improving revenue and reducing risk by hedging against price asymmetries using probabilistic forecasts.

Contribution

It introduces novel risk-constrained trading strategies that incorporate probabilistic forecasts to manage imbalance costs in single-price balancing markets.

Findings

Strategies increase revenue compared to naive approaches

Strategies effectively reduce risk exposure

Case study confirms practical applicability

Abstract

Due to the limited predictability of wind power and other stochastic generation, trading this energy in competitive electricity markets is challenging. This paper derives revenue-maximising and risk-constrained strategies for stochastic generators participating in electricity markets with a single-price balancing mechanism. Starting from the optimal---and impractical---strategy of offering zero or nominal power, which exposes the participant to potentially large imbalance costs, we develop a number of strategies that control risk by hedging against penalising balancing prices in favour of rewarding ones. Trading strategies are formulated in a probabilistic framework in order to address asymmetry in balancing prices. The large-scale communication of system information characteristic of modern power systems is utilised to inputs for electricity price forecasts and probabilistic system length forecasts. A case study using data from the GB market in the UK is presented and the ability of the proposed strategies to increase revenue and reduce risk is demonstrated and analysed.