
Robust Optimization in Electric Energy Systems by Xu Andy Sun
This book covers robust optimization theory and applications in the electricity sector. The advantage of robust optimization with respect to other methodologies for decision making under uncertainty are first discussed. Then, the robust optimization theory is covered in a friendly and tutorial manner. Finally, a number of insightful short- and long-term applications pertaining to the electricity sector are considered.
Specifically, the book includes: robust set characterization, robust optimization, adaptive robust optimization, hybrid robust-stochastic optimization, applications to short- and medium-term operations problems in the electricity sector, and applications to long-term investment problems in the electricity sector. Each chapter contains end-of-chapter problems, making it suitable for use as a text.
The purpose of the book is to provide a self-contained overview of robust optimization techniques for decision making under uncertainty in the electricity sector. The targeted audience includes industrial and power engineering students and practitioners in energy fields. The young field of robust optimization is reaching maturity in many respects. It is also useful for practitioners, as it provides a number of electricity industry applications described up to working algorithms (in JuliaOpt).-
Designing Competitive Electricity Markets
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Principles of Forecasting
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Optimal Search for Moving Targets
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An Introduction to Robust Combinatorial Optimization
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Handbook of Markov Decision Processes
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Computational Probability
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Handbook of Stochastic Models and Analysis of Manufacturing System Operations
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Modeling Uncertainty
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Analysis and Modeling of Manufacturing Systems
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Military Operations Research
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Stochastic Benchmarking
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Constraint-Based Scheduling
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Quantitative Models for Supply Chain Management
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Health Care Benchmarking and Performance Evaluation
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Elicitation
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Linear Programming
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Linear and Nonlinear Programming
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Markovian Demand Inventory Models
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Building Supply Chain Excellence in Emerging Economies
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Evaluation and Decision Models
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Mathematical Programming and Financial Objectives for Scheduling Projects
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Judgment in Predictive Analytics
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Fundamentals of Traffic Simulation
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Benchmarking with DEA, SFA, and R
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Outline of Complex Systems Management Theory— Based on Irreversibility of Reductionism Thinking
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Handbook of Semidefinite Programming
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Quantitative Risk Analysis of Air Pollution Health Effects
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Making Better Decisions
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The Theory and Practice of Revenue Management
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Multicriteria Decision Making
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Optimal Inventory Modeling of Systems
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Queueing Networks
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Handbook on Data Envelopment Analysis
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Process Optimization
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Spare Parts Inventory Control under System Availability Constraints
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Applied Linear Regression for Business Analytics with R
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Economics of Power Systems
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Handbook of Quantitative Supply Chain Analysis
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Multicriterion Decision in Management
Andy Sun is an assistant professor in the Stewart School of Industrial & Systems Engineering at Georgia Tech, USA. Dr. Sun conducts research in optimization and stochastic modeling with applications in electric energy systems and electricity markets. He also works on theory and algorithms for robust and stochastic optimization, and large scale convex optimization.
Antonio J. Conejo received an M.S. from MIT, US and a Ph.D. from the Royal Institute of Technology, Sweden. He has published over 190 papers in refereed journals and is the author or coauthor of books published by Springer, John Wiley, McGraw-Hill and CRC Press. He has been the principal investigator of many research projects financed by public agencies and the power industry and has supervised 19 PhD theses. He is an IEEE Fellow.
| SKU | Unavailable |
| ISBN 13 | 9783030851279 |
| ISBN 10 | 3030851273 |
| Title | Robust Optimization in Electric Energy Systems |
| Author | Xu Andy Sun |
| Series | International Series In Operations Research And Management Science Ser |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer Nature Switzerland AG |
| Year published | 2021-11-09 |
| Number of pages | 329 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |






































