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Authordc.contributor.authorQuintremil, Sebastián 
Authordc.contributor.authorAlberti, Carolina 
Authordc.contributor.authorRivera, Matías 
Authordc.contributor.authorMedina, Fernando 
Authordc.contributor.authorPuente, Javier 
Authordc.contributor.authorCartier Rovirosa, Luis 
Authordc.contributor.authorRamírez, Eugenio 
Authordc.contributor.authorTanaka, Yuetsu 
Authordc.contributor.authorValenzuela, M. Antonieta 
Admission datedc.date.accessioned2016-01-28T18:07:27Z
Available datedc.date.available2016-01-28T18:07:27Z
Publication datedc.date.issued2016
Cita de ítemdc.identifier.citationAids Research and Human Retroviruses, Volumen: 32 Número: 1 Jan 2016en_US
Identifierdc.identifier.otherDOI: 10.1089/aid.2015.0008
Identifierdc.identifier.urihttps://repositorio.uchile.cl/handle/2250/136847
General notedc.descriptionArtículo de publicación ISIen_US
General notedc.descriptionSin acceso a texto completo
Abstractdc.description.abstractEnergy 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
Patrocinadordc.description.sponsorshipSolar 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: FBO16en_US
Lenguagedc.language.isoenen_US
Publisherdc.publisherMary Ann Lieberten_US
Type of licensedc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile*
Link to Licensedc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/*
Keywordsdc.subjectResponse mediator protein-2en_US
Keywordsdc.subjectHTLV-1-Associated neuroinflammatory diseaseen_US
Keywordsdc.subjectI HTLV-Ien_US
Keywordsdc.subjectT-Cellsen_US
Keywordsdc.subjectSpastic paraparesisen_US
Keywordsdc.subjectNeurologic diseaseen_US
Keywordsdc.subjectExpressionen_US
Keywordsdc.subjectMigrationen_US
Keywordsdc.subjectActivationen_US
Títulodc.titleTax and Semaphorin 4D Released from Lymphocytes Infected with Human Lymphotropic Virus Type 1 and Their Effect on Neurite Growthen_US
Document typedc.typeArtículo de revista


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Atribución-NoComercial-SinDerivadas 3.0 Chile
Except where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 3.0 Chile