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Distributionally Robust Optimization and its Applications in Power System Energy Storage Sizing / by Rui Xie, Wei Wei

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Publisher: Singapore : Springer Nature Singapore, 2024Publisher: Singapore : Imprint: Springer, 2024Edition: 1st ed. 2024Description: 1 Online-Ressource(XX, 452 p. 81 illus.)ISBN:
  • 9789819725663
Subject(s): Additional physical formats: 9789819725656 | 9789819725670 | 9789819725687 | Erscheint auch als: 9789819725656 Druck-Ausgabe | Erscheint auch als: 9789819725670 Druck-Ausgabe | Erscheint auch als: 9789819725687 Druck-AusgabeDOI: DOI: 10.1007/978-981-97-2566-3Online resources: Summary: Introduction -- Preliminary -- Basic Distributionally Robust Optimization -- Moment-Based Distributionally Robust Optimization -- Divergence Distributionally Robust Optimization -- Wasserstein-Distance Distributionally Robust Optimization.Summary: This book introduces the mathematical foundations of distributionally robust optimization (DRO) for decision-making problems with ambiguous uncertainties and applies them to tackle the critical challenge of energy storage sizing in renewable-integrated power systems, providing readers with an efficient and reliable approach to analyze and design real-world energy systems with uncertainties. Covering a diverse range of topics, this book starts by exploring the necessity for energy storage in evolving power systems and examining the benefits of employing distributionally robust optimization. Subsequently, the cutting-edge mathematical theory of distributionally robust optimization is presented, including both the general theory and moment-based, KL-divergence, and Wasserstein-metric distributionally robust optimization theories. The techniques are then applied to various practical energy storage sizing scenarios, such as stand-alone microgrids, large-scale renewable power plants, bulkpower grids, and multi-carrier energy networks. This book offers clear explanations and accessible guidance to bridge the gap between advanced optimization methods and industrial applications. Its interdisciplinary scope makes the book appealing to researchers, graduate students, and industry professionals working in electrical engineering and operations research, catering to both beginners and experts.PPN: PPN: 1890094137Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-ENE | ZDB-2-SXEN
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