Controlling a retailer's short‐term financial risk exposure using demand response

Abstract

The transition of the electric power system to reach sustainability goals leads to new market conditions with larger uncertainties. This constitutes new challenges and opportunities for new as well as for existing market players such as retailers. In a future more volatile and unpredictable market, financial risk management becomes an important element for such actors in order to achieve viable businesses. Different instruments can be applied for this purpose, where demand response can contribute in the short-term to manage risks related to price variations and imbalance costs. This study contributes to the enhancement of retailer's businesses by presenting a stochastic optimisation model exploring the possibility to apply demand response to control financial risk exposure. The model considers trading and demand response scheduling for different customer clusters, generating optimal trading volumes for day-ahead markets while also considering the possibility to trade intra-day. The optimisation considers uncertainties in prices and loads as well as imbalance settlement costs. Risk management is integrated into the model by applying conditional value-at-risk as risk measures. The developed model has also been applied in a case study with data from the Swedish and Nordic electricity market together with simulated load profiles for different customer clusters.