Journal of Energy Markets

Assessing the potential profitability of automated power market trading using event signals sourced from grid frequency data

Thomas Bowcutt, Patrick Denvir, Giuseppe Destino, Navesh Kumar and Chris Regan

  • Our event-driven trading strategy demonstrated superior profitability compared to a baseline average strategy, especially when reacting swiftly to grid event signals.
  • Significantly higher profits were observed when the reaction time to grid events was minimized.
  • Analysis showed a distinct and substantial impact of grid events on market prices, underscoring the potential for strategic trading gains.
  • Utilising real-time monitoring and data analysis of grid events, as well as an algorithmic trading engine capable of conducting trades swiftly and precisely, proved crucial for the success of the strategy.

Within a power system, the instantaneous loss of generation or import/export via an interconnector causes a disturbance in the grid frequency. In a low inertia system, it becomes increasingly feasible to identify, size, classify and locate such grid events using a suitably sensitive and accurate network of measurement devices. Loss of generation or interconnector capacity often leads to a significant change in the price stack, leading to movement in market prices as traders adjust their positions. We demonstrate that a systematic trading strategy using an event-detection signal based on public frequency data and highly accurate measurement devices can be profitable. We also assess the sensitivity of profits to the overall event-detection and trade-execution lead times.

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