Managing Price Risk while bidding in a Multimarket Environment

In the deregulated marketplace, generation companies sell energy through auctions in a daily market. The daily-price volatility, together with the bids acceptance process uncertainty, make arise the need of performing risk assessment. A a multi-stage mixed-integer stochastic programming model with linear constraints, able to detect the profitability and risk of bidding in a multi auction energy market, is proposed for power producers. At this purpose, a particularly effective risk measure as the Conditional Value at Risk has been chosen: a discrete formulation has been proposed and evaluated for quantifying the risk of a producer portfolio. The intuitive scenario tree formulation has been adopted to represent the evolution of the random clearing prices and quantities. The Italian zonal pricing has been used as pricing system, to manage network congestions. The proposed model so provides suppliers with an efficient tool able to handle daily market-price uncertainties and to capture, in powerful aggregate risk measures, all relevant portfolio effects of market-risk exposure. Simulations are carried out in a 24-hour time frame on a representative test problem.