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· 분류 : 외국도서 > 기술공학 > 기술공학 > 운영분석
· ISBN : 9783540889649
· 쪽수 : 534쪽
· 출판일 : 2009-01-17
목차
Part I 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 Enterprizes.- Part II 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.- Part III Stochastic Programming - Methods and Applications.- Scenario Tree Approximation and Risk Aversion Strategies for Stochastic Optimization of Electricity Production and Tradin.- 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 Analyse the Large-Scale Integration of Wind Energy.- Part IV Stochastic Programming in Pricing.- Clean Valuation with Regard to EU Emission Trading.- EfficientStochastic Programming Techniques for Electricity Swing Options.- Delta-Hedging a Hydropower Plant Using Stochastic Programming.