Tax and Semaphorin 4D Released from Lymphocytes Infected with Human Lymphotropic Virus Type 1 and Their Effect on Neurite Growth
Author
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Quintremil, Sebastián
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Alberti, Carolina
Author
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Rivera, Matías
Author
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Medina, Fernando
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Puente, Javier
Author
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Cartier Rovirosa, Luis
Author
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Ramírez, Eugenio
Author
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Tanaka, Yuetsu
Author
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Valenzuela, M. Antonieta
Admission date
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2016-01-28T18:07:27Z
Available date
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2016-01-28T18:07:27Z
Publication date
dc.date.issued
2016
Cita de ítem
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Aids Research and Human Retroviruses, Volumen: 32 Número: 1 Jan 2016
en_US
Identifier
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DOI: 10.1089/aid.2015.0008
Identifier
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https://repositorio.uchile.cl/handle/2250/136847
General note
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Artículo de publicación ISI
en_US
General note
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Sin acceso a texto completo
Abstract
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Energy management systems (EMSs) are used for operators to optimize, monitor, and control the performance of a power system. In microgrids, the EMS automatically coordinates the energy sources aiming to supply the demand. The coordination is carried out considering the operating costs, the available energy, and the generation and transmission capabilities of the grid. With this purpose, the available energy of the sources is predicted, and the operating costs are minimized. Thereby, an optimal operation of the microgrid is achieved. Often, the optimization procedure is executed throughout a receding horizon (model predictive control approach). Such approach provides some robustness to the microgrid operation. But, the high variability of the nonconventional energy sources makes the prediction task very complex. As a consequence, the reliable operation of the microgrid is compromised. In this paper, a scenario-based robust EMS is proposed. The scenarios are generated by means of fuzzy interval models. These models are used for solar power, wind power, and load forecasting. Since interval fuzzy models provide a range rather than a trajectory, upper and lower boundaries for these variables are obtained. Such boundaries are used to formulate the EMS as a robust optimization problem. In this sense, the solution obtained is robust against any realization of the uncertain variables inside the intervals defined by the fuzzy models. In addition, the original robust optimization problem is transformed into an equivalent second-order cone programming problem. Hence, desired mathematical properties such as the convexity of the optimization problem might be guaranteed. Therefore, efficient algorithms, based, e.g., on interior-point methods, could be applied to compute its solution. The proposed EMS is tested in the microgrid installed in Huatacondo, a settlement located at the north of Chile.
en_US
Patrocinador
dc.description.sponsorship
Solar Energy Research Center SERC-Chile, CONICYT/FONDAP/ Project
15110019
National Fund for Science and Technology Project
1140775
Complex Engineering Systems Institute
ICM: P-05-004-F
CONICYT: FBO16