Optimization in the Energy Industry (eBook, PDF)

• Format: PDF

Produktdetails

• Verlag: Springer Berlin
• Erscheinungstermin: 25. Dezember 2008
• Englisch
• ISBN-13: 9783540889656
• Artikelnr.: 37371854

Inhaltsangabe

Challenges and Perspectives of Optimization in the Energy Industry.- Current and Future Challenges for Production Planning Systems.- The Earth Warming Problem: Practical Modeling in Industrial Enterprises.- Deterministic Methods.- Trading Hubs Construction for Electricity Markets.- A Decision Support System to Analyze the Influence of Distributed Generation in Energy Distribution Networks.- New Effective Methods of Mathematical Programming and Their Applications to Energy Problems.- Improving Combustion Performance by Online Learning.- Critical States of Nuclear Power Plant Reactors and Bilinear Modeling.- Mixed-Integer Optimization for Polygeneration Energy Systems Design.- Optimization of the Design and Partial-Load Operation of Power Plants Using Mixed-Integer Nonlinear Programming.- Optimally Running a Biomass-Based Energy Production Process.- Mathematical Modeling of Batch, Single Stage, Leach Bed Anaerobic Digestion of Organic Fraction of Municipal Solid Waste.- Spatially Differentiated Trade of Permits for Multipollutant Electric Power Supply Chains.- Applications of TRUST-TECH Methodology in Optimal Power Flow of Power Systems.- Stochastic Programming: Methods and Applications.- Scenario Tree Approximation and Risk Aversion Strategies for Stochastic Optimization of Electricity Production and Trading.- Optimization of Dispersed Energy Supply —Stochastic Programming with Recombining Scenario Trees.- Stochastic Model of the German Electricity System.- Optimization of Risk Management Problems in Generation and Trading Planning.- Optimization Methods Application to Optimal Power Flow in Electric Power Systems.- WILMAR: A Stochastic Programming Tool to Analyze the Large-Scale Integration of Wind Energy.- Stochastic Programming in Pricing.- Clean Valuation with Regard to EU Emission Trading.- Efficient Stochastic Programming Techniques for Electricity Swing Options.- Delta-Hedging a Hydropower Plant Using Stochastic Programming.

---

Challenges and Perspectives of Optimization in the Energy Industry.- Current and Future Challenges for Production Planning Systems.- The Earth Warming Problem: Practical Modeling in Industrial Enterprises.- Deterministic Methods.- Trading Hubs Construction for Electricity Markets.- A Decision Support System to Analyze the Influence of Distributed Generation in Energy Distribution Networks.- New Effective Methods of Mathematical Programming and Their Applications to Energy Problems.- Improving Combustion Performance by Online Learning.- Critical States of Nuclear Power Plant Reactors and Bilinear Modeling.- Mixed-Integer Optimization for Polygeneration Energy Systems Design.- Optimization of the Design and Partial-Load Operation of Power Plants Using Mixed-Integer Nonlinear Programming.- Optimally Running a Biomass-Based Energy Production Process.- Mathematical Modeling of Batch, Single Stage, Leach Bed Anaerobic Digestion of Organic Fraction of Municipal Solid Waste.- Spatially Differentiated Trade of Permits for Multipollutant Electric Power Supply Chains.- Applications of TRUST-TECH Methodology in Optimal Power Flow of Power Systems.- Stochastic Programming: Methods and Applications.- Scenario Tree Approximation and Risk Aversion Strategies for Stochastic Optimization of Electricity Production and Trading.- Optimization of Dispersed Energy Supply -Stochastic Programming with Recombining Scenario Trees.- Stochastic Model of the German Electricity System.- Optimization of Risk Management Problems in Generation and Trading Planning.- Optimization Methods Application to Optimal Power Flow in Electric Power Systems.- WILMAR: A Stochastic Programming Tool to Analyze the Large-Scale Integration of Wind Energy.- Stochastic Programming in Pricing.- Clean Valuation with Regard to EU Emission Trading.- Efficient Stochastic Programming Techniques for Electricity Swing Options.- Delta-Hedging a Hydropower Plant Using Stochastic Programming.