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Data-driven modeling of solar-powered urban microgrids
Author(s) -
Arda Halu,
Antonio Scala,
Abdulaziz Khiyami,
Marta C. González
Publication year - 2016
Publication title -
science advances
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.928
H-Index - 146
ISSN - 2375-2548
DOI - 10.1126/sciadv.1500700
Subject(s) - microgrid , robustness (evolution) , computer science , distributed generation , distributed computing , context (archaeology) , photovoltaic system , mathematical optimization , renewable energy , engineering , paleontology , biochemistry , chemistry , control (management) , mathematics , artificial intelligence , biology , electrical engineering , gene
Distributed generation takes center stage in today’s rapidly changing energy landscape. Particularly, locally matching demand and generation in the form of microgrids is becoming a promising alternative to the central distribution paradigm. Infrastructure networks have long been a major focus of complex networks research with their spatial considerations. We present a systemic study of solar-powered microgrids in the urban context, obeying real hourly consumption patterns and spatial constraints of the city. We propose a microgrid model and study its citywide implementation, identifying the self-sufficiency and temporal properties of microgrids. Using a simple optimization scheme, we find microgrid configurations that result in increased resilience under cost constraints. We characterize load-related failures solving power flows in the networks, and we show the robustness behavior of urban microgrids with respect to optimization using percolation methods. Our findings hint at the existence of an optimal balance between cost and robustness in urban microgrids.MIT-Portugal ProgramKing Abdulaziz City of Science and Technology (Saudia Arabia). Center for Complex Engineering System

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