Risk-constrained optimal strategy for retailer forward contract portfolio

In the medium term planning, the objective of an electricity retailer is to configure its forward contract portfolio and to determine the selling price offered to its clients. To procure the electricity energy to be sold to the clients, a retailer has to face by two major challenges. Firstly, at buying electricity energy, it must cope with uncertain pool prices and sign forward contracts at higher average prices. Secondly, at selling electricity, it should handle the demand uncertainty and consider this fact that customers might choose a different retailer if the selling price is not competitive enough. In this paper the financial risk associated with the market price uncertainty is modeled using expected downside risk, which is incorporated explicitly as a constraint in the mixed-integer stochastic optimization problem. Roulette wheel mechanism and Lattice Monte Carlo Simulation (LMCS) are employed for random scenario generation wherein the stochastic optimization problem is converted into its respective deterministic equivalents. The proposed optimization problem is solved by a decomposition technique using Benders decomposition algorithm. A realistic case study is implemented to demonstrate the capability of the proposed method.