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008			230124s2022 sz | s |||| 0|eng d
020			_a9783030898038
024	7		_a10.1007/978-3-030-89803-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK1007 _b2022 EB
100	1		_aAnanduta, W. Wicak. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686213
245	1	0	_aNon-centralized Optimization-Based Control Schemes for Large-Scale Energy Systems _cby W. Wicak Ananduta
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XVII, 154 páginas) _b33 ilustraciones, 26 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSpringer Theses Recognizing Outstanding Ph.D. Research _x2190-5061
505	0		_aIntroduction -- Non-centralized MPC-Based Economic Dispatch -- Distributed Augmented Lagrangian Methods.
520			_aThis 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 proposes an 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 and asynchronous updates. Overall, this book presents a set of improved predictive control and distributed optimization methods, together with a rigorous mathematical analysis of each proposed algorithms. It describes a comprehensive approach to cope with communication and cooperation issues of non-centralized control schemes and show how the improved schemes can be successfully applied to solve the economic dispatch problems of large-scale energy systems.
988			_aSpringer_Robotics_2022
650		7	_2embne _9405147 _aEnergía eléctrica _xControl automático
650		7	_2embne _9145705 _aOptimización matemática
776	0	8	_iPrinted edition: _z9783030898021
776	0	8	_iPrinted edition: _z9783030898045
776	0	8	_iPrinted edition: _z9783030898052
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi-org.ezproxy.universidadeuropea.es/10.1007/978-3-030-89803-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2023 _dz _eIG _zSI