9783030851309-3030851303-Robust Optimization in Electric Energy Systems (International Series in Operations Research & Management Science)

Robust Optimization in Electric Energy Systems (International Series in Operations Research & Management Science)

ISBN-13: 9783030851309
ISBN-10: 3030851303
Edition: 1st ed. 2021
Author: Antonio J. Conejo, Xu Andy Sun
Publication date: 2022
Publisher: Springer
Format: Paperback 340 pages
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Book details

ISBN-13: 9783030851309
ISBN-10: 3030851303
Edition: 1st ed. 2021
Author: Antonio J. Conejo, Xu Andy Sun
Publication date: 2022
Publisher: Springer
Format: Paperback 340 pages

Summary

Robust Optimization in Electric Energy Systems (International Series in Operations Research & Management Science) (ISBN-13: 9783030851309 and ISBN-10: 3030851303), written by authors Antonio J. Conejo, Xu Andy Sun, was published by Springer in 2022. With an overall rating of 3.7 stars, it's a notable title among other Macroeconomics (Economics, Economics, International Business, Operations Research, Processes & Infrastructure) books. You can easily purchase or rent Robust Optimization in Electric Energy Systems (International Series in Operations Research & Management Science) (Paperback) from BooksRun, along with many other new and used Macroeconomics books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.53.

Description

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).

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