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San Leonardo de Yagüe, Spain

Cortes A.,Ingenieria e Integracion Avanzadas Ingenia | Tellez A.E.,Ingho FM | Gallardo M.,Ingho FM | Peralta J.J.,Instituto Andaluz Of Tecnologia Iat
Intelligent Systems, Control and Automation: Science and Engineering | Year: 2014

This study presents a work in progress of the Smart Home Energy project (SHE), in which tests and simulations have generated a large set of energy consumption data that has been evaluated analytically to define a prediction model for energy consumption, based on automatic machine learning. The SuperDoop Lambda Arquitecture developed by Ingenia for Big Data implementation used in the SHE project allows implementing a service to do predictions massively, developing a personalized home energy knowledge model for each home. These methods and related technology can be used also for other energy consumers, like shops, offices, buildings, industries, electrical vehicles, etc. © Springer International Publishing Switzerland 2014. Source


Peralta J.J.,Instituto Andaluz Of Tecnologia Iat | Perez-Ruiz J.,University of Malaga | De La Torre S.,University of Malaga
2013 IEEE Grenoble Conference PowerTech, POWERTECH 2013 | Year: 2013

This paper presents an algorithm to solve a unit commitment problem that takes into account the uncertainty in the demand. This uncertainty is included in the optimization problem as a joint chance constraint that bounds the minimum value of the probability to jointly meet the deterministic power balance constraints. The demand is modeled as a multivariate, normally distributed, random variable and the correlation among different time periods is also considered. A deterministic mixed-integer linear programming problem is sequentially solved until it converges to the solution of the chance-constrained optimization problem. Different approaches are presented to update the z-value used to transform the joint chance constraint into a set of deterministic constraints. Results from a realistic size case study are presented and the values obtained for the multivariate normal distribution probability are compared with the ones obtained by using a Monte Carlo simulation procedure. © 2013 IEEE. Source


Jimenez-Navarro J.P.,Instituto Andaluz Of Tecnologia Iat | Zubizarreta-Jimenez R.,Instituto Andaluz Of Tecnologia Iat | Manuel Cejudo-Lopez J.,University of Malaga
Dyna (Spain) | Year: 2012

The purpose of this paper is to present the results of the feasibility study for a district heating-cooling network to cover the energy demand in a Scientific and Technological Park under Mediterranean climate conditions. This study consists of three phases: energy demand, technology analysis and economic study. To evaluate the energy demand a bottom-up strategy has been followed: a building inventory has been carried out to define several building types according to use, envelope and glazing. Energy + has been used to obtain heating and cooling demand profiles for each building type and orientation. According to municipal development plans for PTA and forecast in business growth, the energy demand evaluation in a 10-years timeframe has been carried out. Most appropriate technologies has been analyzed and evaluated: cogeneration (gas turbine and alternative internal combustion engines), biomass boiler and conventional technologies have been evaluated with TRNSYS to obtain consumption profiles, consumption rates, efficiency indicators and energy losses. Finally an economic analysis has been done to technologies in a 20 years period to evaluate technology that better economic results address. The main objective of this work is the promotion of the efficient and effective energy supply in areas with high energy consumption. DCH technology is widely used in the North of Europe and this paper tries to demonstrate that this technology could be applied in Mediterranean areas successfully. Source


Horcada A.,University of Seville | Fernandez-Cabanas V.M.,University of Seville | Polvillo O.,University of Seville | Botella B.,Instituto Andaluz Of Tecnologia Iat | And 5 more authors.
Talanta | Year: 2013

In the present study, fatty acid and triacylglycerol profiles were used to evaluate the possibility of authenticating Iberian dry-cured sausages according to their label specifications. 42 Commercial brand 'chorizo' and 39 commercial brand 'salchichón' sausages from Iberian pigs were purchased. 36 Samples were labelled Bellota and 45 bore the generic Ibérico label. In the market, Bellota is considered to be a better class than the generic Ibérico since products with the Bellota label are manufactured with high quality fat obtained from extensively reared pigs fed on acorns and pasture. Analyses of fatty acids and triacylglycerols were carried out by gas chromatography and a flame ion detector. A CP-SIL 88 column (highly substituted cyanopropyl phase; 50 m×0.25 mm i.d., 0.2 μm film thickness) (Varian, Palo Alto, USA) was used for fatty acid analysis and a fused silica capillary DB-17HT column (50% phenyl-50% methylpolysiloxane; 30 m×0.25 mm i.d., 0.15 μm film thickness) was used for triacylglycerols. Twelve fatty acids and 16 triacylglycerols were identified. Various discriminant models (linear quadratic discriminant analyses, logistic regression and support vector machines) were trained to predict the sample class (Bellota or Ibérico). These models included fatty acids and triacylglycerols separately and combined fatty acid and triacylglycerol profiles. The number of correctly classified samples according to discriminant analyses can be considered low (lower than 65%). The greatest discriminant rate was obtained when triacylglycerol profiles were included in the model, whilst using a combination of fatty acid and triacylglycerol profiles did not improve the rate of correct assignation. The values that represent the reliability of prediction of the samples according to the label specification were higher for the Ibérico class than for the Bellota class. In fact, quadratic and Support Vector Machine discriminate analyses were not able to assign the Bellota class (0%) when combined fatty acids and triacylglycerols were included in the model. The use of fatty acid and triacylglycerol profiles to discriminate Iberian dry-cured sausages in the market according to their labelling information is unclear. In order to ensure the genuineness of Iberian dry-cured sausages in the market, identification of fatty acid and triacylglycerol profiles should be combined with the application of quality standard traceability techniques. © 2013 Published by Elsevier B.V. Source


Fernandez-Cabanas V.M.,University of Seville | Polvillo O.,University of Seville | Rodriguez-Acuna R.,Instituto Andaluz Of Tecnologia Iat | Botella B.,Instituto Andaluz Of Tecnologia Iat | Horcada A.,University of Seville
Food Chemistry | Year: 2011

The feasibility of using near infrared reflectance spectroscopy to evaluate the generation of relevant and accurate nutritional information through a rapid determination of the fatty acid profiles in Iberian pork dry-cured sausages was analysed. Individual fatty acids contents together with the saturated (SFA), monounsaturated (MUFA) and polyunsaturated fatty acid (PUFA) groups were determined in 86 samples of Iberian dry-cured sausages. NIR calibrations were developed using modified partial least squared regressions. Selected models for the estimation of major constituents (C14:0, C16:0, C16:1, C18:0, C18:1 and C18:2) exhibited coefficients of determination for cross-validation which ranged between 0.41 and 0.84 with standard errors of cross-validation (SECV) between 0.07 and 1.51. Calibrations developed for SFA, MUFA and PUFA showed coefficients of determination of 0.86, 0.53 and 0.61, and SECV values of 0.98, 1.47 and 0.88, respectively. The results obtained suggest that in general, NIR spectroscopy could provide an exceptional opportunity for the quality control of dry-cured sausages, since it allows an estimation of the major constituents and/or a classification based on their fatty acid profiles rapidly whilst avoiding the generation of chemical residues. This information could be used to estimate shelf life of products and to include extra nutritional information associated to consumers' health in their labelling. © 2010 Elsevier Ltd. Source

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