A two-stage stochastic optimization model for a gas sale retailer
F. Maggioni; Maria Teresa Vespucci; E. Allevi; Marida Bertocchi; M. Innorta
Kybernetika (2008)
- Volume: 44, Issue: 2, page 277-296
- ISSN: 0023-5954
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topMaggioni, F., et al. "A two-stage stochastic optimization model for a gas sale retailer." Kybernetika 44.2 (2008): 277-296. <http://eudml.org/doc/33926>.
@article{Maggioni2008,
abstract = {The paper deals with a new stochastic optimization model, named OMoGaS–SV (Optimization 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 and are compared with the results obtained by the deterministic version (see Allevi et al. [ABIV]).},
author = {Maggioni, F., Vespucci, Maria Teresa, Allevi, E., Bertocchi, Marida, Innorta, M.},
journal = {Kybernetika},
keywords = {gas sale company; mean reverting process; stochastic programming; gas sale company; mean reverting process; stochastic programming},
language = {eng},
number = {2},
pages = {277-296},
publisher = {Institute of Information Theory and Automation AS CR},
title = {A two-stage stochastic optimization model for a gas sale retailer},
url = {http://eudml.org/doc/33926},
volume = {44},
year = {2008},
}
TY - JOUR
AU - Maggioni, F.
AU - Vespucci, Maria Teresa
AU - Allevi, E.
AU - Bertocchi, Marida
AU - Innorta, M.
TI - A two-stage stochastic optimization model for a gas sale retailer
JO - Kybernetika
PY - 2008
PB - Institute of Information Theory and Automation AS CR
VL - 44
IS - 2
SP - 277
EP - 296
AB - The paper deals with a new stochastic optimization model, named OMoGaS–SV (Optimization 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 and are compared with the results obtained by the deterministic version (see Allevi et al. [ABIV]).
LA - eng
KW - gas sale company; mean reverting process; stochastic programming; gas sale company; mean reverting process; stochastic programming
UR - http://eudml.org/doc/33926
ER -
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