31 research outputs found
Células solares fotovoltaicas : desarrollo de sistemas de monitorización y seguimiento de sistemas fotovoltaicos
En la UMA se investiga tanto el control y análisis de este tipo de dispositivos, como en las caracterÃsticas eléctricas de módulos de distintas tecnologÃas que ayudan, entre otras cosas, a conocer enn directo indicadores como la producción real de energÃa de estas plataformas
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 AndalucÃa Tec
Modelos para la predicción del autoconsumo en sistemas fotovoltaicos conectados a red
CIES2020 - XVII Congresso Ibérico e XIII Congresso Ibero-americano de Energia SolarRESUMEN: En este trabajo se presentan los resultados obtenidos para la modelización y optimización de instalaciones fotovoltaicas de autoconsumo. Se han obtenido las curvas de autoconsumo y autosuficiencia para diferentes perfiles de consumo horario en función de la potencia pico instalada y el tamaño de la baterÃa. El estudio se ha realizado para tres ciudades españolas con diferentes condiciones climáticas. Para la generalización de los resultados se proponen diferentes modelos de aprendizaje automático que permiten estimar estos parámetros. Las variables de entrada de estos modelos están relacionadas con la configuración de la instalación, su ubicación y el tipo de perfil de consumo. El modelo que arroja mejores predicciones en el parámetro de autosuficiencia es Random Forest, que en la validación cruzada tiene un error relativo del 5%. Para la predicción del autoconsumo, el modelo que mejor se comporta es el Perceptrón Multicapa, con un error absoluto promedio de 0.55 y un error relativo del 3%.ABSTRACT: 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. In order to generalize the obtained results, different models of machine learning are proposed to estimate 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 a relative error of 3%.info:eu-repo/semantics/publishedVersio
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 AndalucÃa Tech. Junta de AndalucÃa. Proyecto de Excelencia P11-RNM-711
Optimization of Energy Distribution in Solar Panel Array Configurations by Graph Theory and Minkowski’s Paths
Nowadays, the development of the photovoltaic (PV) technology is consolidated as a source of renewable energy. The research in the topic of maximum improvement on the energy efficiency of the PV plants is today a major challenge. The main requirement for this purpose is to know the performance of each of the PV modules that integrate the PV field in real time.
In this respect, a PLC communications based Smart Monitoring and Communications Module, which is able to monitor at PV level their operating parameters, has been developed at the University of Malaga. With this device you can check if any of the panels is suffering any type of overriding performance, due to a malfunction or partial shadowing of its surface.
Since these fluctuations in electricity production from a single panel affect the overall sum of all panels that conform a string, it is necessary to isolate the problem and modify the routes of energy through alternative paths in case of PV panels array configuration.Universidad de Málaga. Campus de Excelencia Internacional AndalucÃa Tech
Analysis of CO2 reduction with micro CHP facility: Renewable energies and Stirling engine.
The Cogeneration laboratory is a research facility in the University of Málaga (UMA) that allows for the behavioural study of a renewable energy installation combining solar resources and micro-CHP. Energy generation in the system is provided by a 3 kWp photovoltaic array, two solar thermal connectors and a Whispergen EU1 Stirling micro-CHP unit. Energy storage in the facility is provided by water tank and lithium-ion battery. This laboratory is managed through a programmable Mitsubishi PLC that permits the simulation of different thermal and electrical load profiles, as well as the mode of operation. The electrical energy management is controlled by the solar inverter. Environmental data, are measured using a top of the line weather station.The system’s real time status is logged through the programmable PLC. All this data is transferred and analysed in a purpose-built MATLAB-based software, where power and energy balances are conducted, efficiencies are calculated, and a CO2 emissions evaluation is studied.The CO2 emissions analysis is carried to evaluate the carbon dioxide emissions generated by the facility when the electrical and thermal demand are provided by the joint solar and micro-CHP system. These emissions come from the burning of natural gas in the micro-CHP Stirling engine, and the usage of electricity from the grid. With the current mode of operation, a reduction of up to 70% in CO2 emissions has been achieved, with an energy generation that exceeds the demandUniversidad de Málaga. Campus de Excelencia Internacional AndalucÃa Tech
Cómo medir las actuaciones urbanas para la descarbonización de las ciudades? Aplicabilidad del Ãndice de sostenibilidad energética urbana en los barrios
CIES2020 - XVII Congresso Ibérico e XIII Congresso Ibero-americano de Energia SolarRESUMEN: En este trabajo se recoge la experiencia desarrollada con el Ãndice de sostenibilidad energética urbana para las ciudades de Barcelona y Málaga (Márquez-Ballesteros et al, 2019), planteando nuevas vÃas de trabajo en su aplicabilidad. Se parte de la premisa de que la unidad mÃnima de actuación, en cuanto a la sostenibilidad energética deberÃan ser los barrios. La escala urbana de un distrito hace posible las actuaciones globales, desde edificios hasta actuaciones en el espacio público, pasando por aquellas que tienen que ver con la producción local fotovoltaica o la movilidad sostenible, con el máximo acercamiento a los vecinos y vecinas que deberÃan estar en el centro de toda actuación de mejora. Por lo tanto, las actuaciones en la ciudad barrio a barrio pueden ser una herramienta muy útil en el avance de la sostenibilidad energética. El poder utilizar una herramienta como el Ãndice de sostenibilidad energética urbana para evaluar las actuaciones realizadas en un barrio es un elemento clave para detectar desequilibrios en la ciudad y a su vez acercar la realidad energética a los ciudadanos.ABSTRACT: This work collects all the experience developed with the urban energy sustainability index for the cities of Barcelona and Malaga (Márquez-Ballesteros et al, 2019), proposing new ways of working in its applicability. We start with the premise that the minimum unit of action, in terms of energy sustainability, should be the neighbourhoods. The urban scale of a district makes global measures possible, from buildings to interventions in public space, through those that have to do with local photovoltaic production or sustainable mobility, with the maximum approach to the citizens who should be at the centre of any improvement action. Therefore, interventions in the city neighbourhood by neighbourhood can be a useful tool in the advancement of energy sustainability. The urban energy sustainability index can be used as a tool to evaluate the actions carried out in a neighbourhood and to detect imbalances in the city and finally, bring the energy reality closer to citizens.info:eu-repo/semantics/publishedVersio