Models for the Optimization and Evaluation of Photovoltaic Self-Consumption Facilities

The results obtained for the modeling and optimization of photovoltaic self-consumption facilities are presented. The study has been carried out for three Spanish cities with different climatic conditions. The self-consumption and self-sufficiency curves for different hourly consumption profiles have been obtained based on the installed peak power and the size of the battery. Different models of machine learning are proposed to predict these parameters. The input variables of these models are related to the configuration of the installation, its location and the type of consumption profile. The model with best predictions of self-sufficiency is Random Forest, which in cross-validation has a relative error of 5%. For the prediction of self-consumption, the model that performs best is the multilayer perceptron, with an average absolute error of 0.55 and an absolute relative error of 3%

Characterisation of hourly temperature of a thin-film module from weather conditions by artificial intelligence techniques

The aim of this paper is the use and validation of artificial intelligence techniques to predict the temperature of a thin-film module based on tandem CdS/CdTe technology. The cell temperature of a module is usually tens of degrees above the air temperature, so that the greater the intensity of the received radiation, the greater the difference between these two temperature values. In practice, directly measuring the cell temperature is very complicated, since cells are encapsulated between insulation materials that do not allow direct access. In the literature there are several equations to obtain the cell temperature from the external conditions. However, these models use some coefficients which do not appear in the specification sheets and must be estimated experimentally. In this work, a support vector machine and a multilayer perceptron are proposed as alternative models to predict the cell temperature of a module. These methods allow us to achieve an automatic way to learn only from the underlying information extracted from the measured data, without proposing any previous equation. These proposed methods were validated through an experimental campaign of measurements. From the obtained results, it can be concluded that the proposed models can predict the cell temperature of a module with an error less than 1.5 °C.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

New software tool to characterize photovoltaic modules from commercial equipment

A software platform has been developed in order to unify the different measurements obtained from different manufacturers in the photovoltaic system laboratory of the University of Malaga, Spain. These measurements include the current-voltage curve of PV modules and several meteorological parameters such as global and direct irradiance, temperature and spectral distribution of solar irradiance. The measurements are performed in an automated way by a stand-alone application that is able to communicate with a pair of multimeters and a bipolar power supply that are controlled in order to obtain the current–voltage pairs. In addition, several magnitudes, that can be configured by the user, such as irradiance, module temperature or wind speed, are incorporated to register the conditions of each measurement. Moreover, it is possible to attach to each curve the spectral distribution of the solar radiation at each moment. Independently of the source of the information, all these measurements are stored in a uniform relational database. These data can be accessed through a public web site that can generate several graphics from the data.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Junta de Andalucía. Proyecto de Excelencia P11-RNM-711

Barrios zero como germen de ciudades sin emisiones.

El trascurso del siglo XX está íntimamente relacionado con el nacimiento y auge de las metrópolis contemporáneas. Durante este siglo, el desarrollo de la humanidad se relaciona íntimamente al desarrollo y crecimiento de las ciudades Hoy en día, el 55% de la población mundial vive en áreas urbanas, una proporción que se espera que aumente al 68% para 2050. De alguna manera, las ciudades se distancian de ser un problema para convertirse en una parte fundamental de la solución. Cuanto más se actúa de manera local, más fácil es involucrar a vecinos, empresas y administraciones, porque solamente desde esta acción conjunta se pueden definir vías de trabajo eficientes en la mejora de las ciudades y en el desarrollo sostenible de los territorios. En este proyecto hemos querido conocer en un caso real, cual es el consumo energético y que acciones deberían tomarse para que fuera un barrio cero emisiones, bajo la hipótesis de que el planteamiento de las actuaciones de revitalización de barrios y su sostenibilidad energética se deben hacer desde el esfuerzo comunitario, partiendo de la reflexión sobre la creación de distritos de energía casi nula basados en una economía baja en carbono, como un proceso en el que los vecinos estén concienciados de que la mitigación del cambio climático parte de la voluntad de ellos mismos para la modificación de sus hábitos de consumo, la gestión de la demanda energética y en el conocimiento de los factores que hacen más sostenible el futuro de las ciudades. Hemos evaluado a modo de proyecto piloto, un barrio de Málaga, con el fin de establecer las acciones para convertir el barrio en un espacio libre de emisiones, estableciendo una metodología propia, que parte de los consumos de los barrios, lo relaciona con las posibles acciones vinculadas, así como sus consecuencias en las posibles mejoras de la sostenibilidad energética urbana

Smart Solar Micro-exchangers for Sustainable Mobility of University Camps

Publicado el resumen en: https://www.wmcaus.org/files/WMCAUS2020_Book.pdf. Pendiente de publicación de las contribuciones en IOP Conference Series: Materials Science and Engineering.A significant number of universities have several campuses located in urban or rural settings, or with scattered university buildings that require the use of means of transportation. This implies the mobility and potential displacement of a large community of students, professors and researchers. The use of electric bicycles (e-bikes) is an intermediate alternative between the bicycle and electric cars. It can be an important stimulus for the promotion of the decarbonisation of the University Campus, avoiding the traffic congestion and reducing space requirements for parking. This paper presents the smart solar micro-exchanger model managed through a sustainable mobility web platform, applied to the case study of the University of Malaga (Spain). It is a solar charging station for e-bike, whose design is based on the principles of solar architecture (providing great security to e-bike). It managed by a web platform and app that allows the user to make reservations and learn about the savings in CO2 emissions. The system allows performing an aerobic sports activity without sweating problems when you reach the job. The platform also incorporates a database of quiet and safe routes for e-bike users.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Edoxaban versus warfarin in patients with atrial fibrillation

Contains fulltext : 125374.pdf (publisher's version ) (Open Access)BACKGROUND: Edoxaban is a direct oral factor Xa inhibitor with proven antithrombotic effects. The long-term efficacy and safety of edoxaban as compared with warfarin in patients with atrial fibrillation is not known. METHODS: We conducted a randomized, double-blind, double-dummy trial comparing two once-daily regimens of edoxaban with warfarin in 21,105 patients with moderate-to-high-risk atrial fibrillation (median follow-up, 2.8 years). The primary efficacy end point was stroke or systemic embolism. Each edoxaban regimen was tested for noninferiority to warfarin during the treatment period. The principal safety end point was major bleeding. RESULTS: The annualized rate of the primary end point during treatment was 1.50% with warfarin (median time in the therapeutic range, 68.4%), as compared with 1.18% with high-dose edoxaban (hazard ratio, 0.79; 97.5% confidence interval [CI], 0.63 to 0.99; P<0.001 for noninferiority) and 1.61% with low-dose edoxaban (hazard ratio, 1.07; 97.5% CI, 0.87 to 1.31; P=0.005 for noninferiority). In the intention-to-treat analysis, there was a trend favoring high-dose edoxaban versus warfarin (hazard ratio, 0.87; 97.5% CI, 0.73 to 1.04; P=0.08) and an unfavorable trend with low-dose edoxaban versus warfarin (hazard ratio, 1.13; 97.5% CI, 0.96 to 1.34; P=0.10). The annualized rate of major bleeding was 3.43% with warfarin versus 2.75% with high-dose edoxaban (hazard ratio, 0.80; 95% CI, 0.71 to 0.91; P<0.001) and 1.61% with low-dose edoxaban (hazard ratio, 0.47; 95% CI, 0.41 to 0.55; P<0.001). The corresponding annualized rates of death from cardiovascular causes were 3.17% versus 2.74% (hazard ratio, 0.86; 95% CI, 0.77 to 0.97; P=0.01), and 2.71% (hazard ratio, 0.85; 95% CI, 0.76 to 0.96; P=0.008), and the corresponding rates of the key secondary end point (a composite of stroke, systemic embolism, or death from cardiovascular causes) were 4.43% versus 3.85% (hazard ratio, 0.87; 95% CI, 0.78 to 0.96; P=0.005), and 4.23% (hazard ratio, 0.95; 95% CI, 0.86 to 1.05; P=0.32). CONCLUSIONS: Both once-daily regimens of edoxaban were noninferior to warfarin with respect to the prevention of stroke or systemic embolism and were associated with significantly lower rates of bleeding and death from cardiovascular causes. (Funded by Daiichi Sankyo Pharma Development; ENGAGE AF-TIMI 48 ClinicalTrials.gov number, NCT00781391.)