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Titlebook: Non-centralized Optimization-Based Control Schemes for Large-Scale Energy Systems; W. Wicak Ananduta Book 2022 The Editor(s) (if applicabl

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發(fā)表于 2025-3-21 18:28:33 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Non-centralized Optimization-Based Control Schemes for Large-Scale Energy Systems
編輯W. Wicak Ananduta
視頻videohttp://file.papertrans.cn/668/667069/667069.mp4
概述Is nominated as an outstanding Ph.D. thesis by Universitat Politècnica de Catalunya.Presents new solutions for communication and cooperation issues of non-centralized optimization.Offers a rigorous ma
叢書(shū)名稱(chēng)Springer Theses
圖書(shū)封面Titlebook: Non-centralized Optimization-Based Control Schemes for Large-Scale Energy Systems;  W. Wicak Ananduta Book 2022 The Editor(s) (if applicabl
描述.This book describes the development of innovative non-centralized optimization-based control schemes to solve economic dispatch problems of large-scale energy systems. Particularly, it focuses on communication and cooperation processes of local controllers, which are integral parts of such schemes. The economic dispatch problem, which is formulated as a convex optimization problem with edge‐based coupling constraints, is solved by using methodologies in distributed optimization over time-varying networks, together with distributed model predictive control, and system partitioning techniques. At first, the book describes two distributed optimization methods, which are iterative and require the local controllers to exchange information with each other at each iteration. In turn, it shows that the sequence produced by these methods converges to an optimal solution when some conditions, which include how the controllers must communicate and cooperate, are satisfied. Further, it proposesan information exchange protocol to cope with possible communication link failures. Finally, the proposed distributed optimization methods are extended to the cases with random communication networks an
出版日期Book 2022
關(guān)鍵詞Distributed Augmented Lagrangian Method; Model Predictive Control Methods; Non‐centralized MPC Scheme;
版次1
doihttps://doi.org/10.1007/978-3-030-89803-8
isbn_softcover978-3-030-89805-2
isbn_ebook978-3-030-89803-8Series ISSN 2190-5053 Series E-ISSN 2190-5061
issn_series 2190-5053
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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發(fā)表于 2025-3-21 21:30:41 | 只看該作者
Non-centralized MPC-Based Economic Dispatch,s the model of the systems. Then, in Sect. ?., the mathematical formulation of the problem is stated. Section?. presents a non-centralized scheme based on model predictive control (MPC) as the general framework considered in this thesis, whereas Sect.?. introduces the benchmark case that is used whe
板凳
發(fā)表于 2025-3-22 03:55:15 | 只看該作者
Distributed Augmented Lagrangian Methods,blem (2.15). The proposed methods are based on the augmented Lagrangian approach. First, in Sect.?., a brief introduction about the augmented Lagrangian approach is presented. Then, in Sect.?., a distributed algorithm based on this approach is designed and its convergence properties are stated. Sect
地板
發(fā)表于 2025-3-22 08:33:49 | 只看該作者
Mitigating Communication Failures in Distributed MPC Schemes,roblem of communication failures in DMPC strategies and proposes a distributed solution to cope with them. The proposal consists in an information-exchange protocol that is based on consensus. By applying this protocol as a complementary plug-in to a DMPC strategy, the controllers improve the resili
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Resiliency of Non-centralized MPC Schemes Against Adversaries, some of the agents perform one type of adversarial actions (attacks) and they do not comply with the decisions computed by performing a non-centralized MPC algorithm. A novel resilient non-centralized MPC scheme for such systems that can cope with non-compliance issue is proposed in this chapter. T
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