  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.
