A stochastic optimization model for gas retail with temperature scenarios and oil price parameters

Abstract

The paper deals with a new stochastic optimization model, named OMoGaS-2SV (Optimization Modelling for Gas Seller-Second Stochastic version), to assist companies dealing with gas retail commercialisation. We consider as source of stochasticity temperature, but we take into account also information on energetic indices. Temperature influences gas consumption of small consumers and is modelled by a mean reverting process. Oil prices and exchange rates influence the energetic indices to which sell and purchase prices are related. Forward curves of energetic indices are analyzed by a vector-autoregressive model while exhange rates are modelled by GARCH model. The profit function depends on the number of contracts with the final consumers, the tipology of such consumers, the cost supported to meet the final demand and penalties for daily maximum consumption exceeding daily maximum capacity. Linear constraints related to a maximum daily gas consumption and binary constraints on indexation formulas are included.