A Gas Retail Stochastic Optimization Model by Mean Reverting Temperature Scenarios

F. Maggioni, M.T. Vespucci, E. Allevi, M.I. Bertocchi, M. Innorta


The paper deals with a new stochastic optimization model, named OMoGaS-SV (Optimisation Modelling for Gas Seller-Stochastic Version), to assist companies dealing with gas retail commercialization. Stochasticity is due to the dependence of consumptions on temperature uncertainty. Due to nonlinearities present in the objective function, the model can be classified as an NLP mixed integer model, with the profit function depending on the number of contracts with the final consumers, the typology of such consumers and the cost supported to meet the final demand. Constraints related to a maximum daily gas consumption, to yearly maximum and minimum consumption in order to avoid penalties and to consumption profiles are included. The results obtained by the stochastic version give clear indication of the amount of losses that may appear in the gas seller’s budget.

[DOI: 10.1685 / CSC06162] About DOI

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DOI: https://doi.org/10.1685/

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