Risk-averse bidding of energy and spinning reserve by wind farms with on-site energy storage

The increased net-demand uncertainty and volatility observed in power systems with large-scale penetration of intermittent renewables has translated into the deployment of larger volumes of reserve and into the need for procuring new sources of flexibility. In order to cope with increased uncertainty and risk of experiencing low profits, wind farm owners must adopt flexible bidding strategies such as coordinating its operation with energy storage systems (ESS). Besides managing wind imbalances, ESS are also capable of providing ancillary services such as spinning reserve (SPR) and frequency response to improve profitability. In this context, this paper proposes a novel two-stage stochastic mathematical programming model that allows considering different degrees of risk aversion when optimising the day-ahead energy and SPR bidding strategy of a wind farm with on-site ESS. Uncertainty is modelled through prices and wind generation forecasts, while the conditional-value-at-risk metric is used to handle day-ahead profit risk. The developed case studies provide evidence of the value of combined wind farm and ESS bidding not only through increased daily profits but also through reduced offer uncertainty which improves the position of a wind farm in the day-ahead markets.