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Titlebook: Decision Making Under Uncertainty; Energy and Power Claude Greengard,Andrzej Ruszczynski Conference proceedings 2002 Springer Science+Busin

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樓主: calcification
21#
發(fā)表于 2025-3-25 04:42:38 | 只看該作者
22#
發(fā)表于 2025-3-25 08:05:59 | 只看該作者
23#
發(fā)表于 2025-3-25 11:38:29 | 只看該作者
Opportunities for Stochastic and Probabilistic Modeling in the Deregulated Electricity Industry,At the turn of the twentieth century, electric power was an exciting new technology. Capital flowed into highly leveraged entities that built power plants and wires in urban centers across the developed world. As time progressed electric utilities came under government regulation or control.
24#
發(fā)表于 2025-3-25 16:27:32 | 只看該作者
25#
發(fā)表于 2025-3-25 21:26:23 | 只看該作者
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29#
發(fā)表于 2025-3-26 12:57:20 | 只看該作者
Data Science – Analytics and Applicationsation problems we allow for the considerable uncertainty in reservoir description by considering a stochastic scenario. The results are represented as probability distribution curves for the NPV and for total production. We also compute an efficient frontier analogous to the efficient frontier in portfolio management.
30#
發(fā)表于 2025-3-26 20:27:45 | 只看該作者
https://doi.org/10.1007/978-3-658-27495-5 history and combining the two types of models into one economic equilibrium model is quite common. Examples are the energy-market models, PIES (Hogan [1975]), IFFS (Murphy, Conti, Sanders and Shaw [1988]), and NEMS (Energy Information Administration [1998]). For a summary of all three, see Murphy and Shaw [1995].
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