Ebook: Decision Making Under Uncertainty: Energy and Power
- Tags: Real Functions, Statistics for Engineering Physics Computer Science Chemistry and Earth Sciences, Computational Intelligence, Math. Applications in Chemistry
- Series: The IMA Volumes in Mathematics and its Applications 128
- Year: 2002
- Publisher: Springer-Verlag New York
- Edition: 1
- Language: English
- pdf
In the ideal world, major decisions would be made based on complete and reliable information available to the decision maker. We live in a world of uncertainties, and decisions must be made from information which may be incomplete and may contain uncertainty. The key mathematical question addressed in this volume is "how to make decision in the presence of quantifiable uncertainty." The volume contains articles on model problems of decision making process in the energy and power industry when the available information is noisy and/or incomplete. The major tools used in studying these problems are mathematical modeling and optimization techniques; especially stochastic optimization. These articles are meant to provide an insight into this rapidly developing field, which lies in the intersection of applied statistics, probability, operations research, and economic theory. It is hoped that the present volume will provide entry to newcomers into the field, and stimulation for further research.
In the ideal world, major decisions would be made based on complete and reliable information available to the decision maker. We live in a world of uncertainties, and decisions must be made from information which may be incomplete and may contain uncertainty. The key mathematical question addressed in this volume is "how to make decision in the presence of quantifiable uncertainty." The volume contains articles on model problems of decision making process in the energy and power industry when the available information is noisy and/or incomplete. The major tools used in studying these problems are mathematical modeling and optimization techniques; especially stochastic optimization. These articles are meant to provide an insight into this rapidly developing field, which lies in the intersection of applied statistics, probability, operations research, and economic theory. It is hoped that the present volume will provide entry to newcomers into the field, and stimulation for further research.
In the ideal world, major decisions would be made based on complete and reliable information available to the decision maker. We live in a world of uncertainties, and decisions must be made from information which may be incomplete and may contain uncertainty. The key mathematical question addressed in this volume is "how to make decision in the presence of quantifiable uncertainty." The volume contains articles on model problems of decision making process in the energy and power industry when the available information is noisy and/or incomplete. The major tools used in studying these problems are mathematical modeling and optimization techniques; especially stochastic optimization. These articles are meant to provide an insight into this rapidly developing field, which lies in the intersection of applied statistics, probability, operations research, and economic theory. It is hoped that the present volume will provide entry to newcomers into the field, and stimulation for further research.
Content:
Front Matter....Pages i-ix
Stochastic Programming Models: Wait-and-See Versus Here-and-Now....Pages 1-15
Optimal Stimulation of Oil Production....Pages 17-37
Power Management in a Hydro-Thermal System under Uncertainty by Lagrangian Relaxation....Pages 39-70
Hedging Electricity Portfolios via Stochastic Programming....Pages 71-93
Opportunities for Stochastic and Probabilistic Modeling in the Deregulated Electricity Industry....Pages 95-113
On Supply Function Bidding in Electricity Markets....Pages 115-133
Qualitative Implications of Uncertainty in Economic Equilibrium Models....Pages 135-151
Back Matter....Pages 153-163
In the ideal world, major decisions would be made based on complete and reliable information available to the decision maker. We live in a world of uncertainties, and decisions must be made from information which may be incomplete and may contain uncertainty. The key mathematical question addressed in this volume is "how to make decision in the presence of quantifiable uncertainty." The volume contains articles on model problems of decision making process in the energy and power industry when the available information is noisy and/or incomplete. The major tools used in studying these problems are mathematical modeling and optimization techniques; especially stochastic optimization. These articles are meant to provide an insight into this rapidly developing field, which lies in the intersection of applied statistics, probability, operations research, and economic theory. It is hoped that the present volume will provide entry to newcomers into the field, and stimulation for further research.
Content:
Front Matter....Pages i-ix
Stochastic Programming Models: Wait-and-See Versus Here-and-Now....Pages 1-15
Optimal Stimulation of Oil Production....Pages 17-37
Power Management in a Hydro-Thermal System under Uncertainty by Lagrangian Relaxation....Pages 39-70
Hedging Electricity Portfolios via Stochastic Programming....Pages 71-93
Opportunities for Stochastic and Probabilistic Modeling in the Deregulated Electricity Industry....Pages 95-113
On Supply Function Bidding in Electricity Markets....Pages 115-133
Qualitative Implications of Uncertainty in Economic Equilibrium Models....Pages 135-151
Back Matter....Pages 153-163
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