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Antonio Javier Martínez-Calahorro; Leocadio Hontoria; Antonio José Partal-Ureña; Francisco José Muñoz-Rodríguez; Catalina Rus-Casas. COMPANY-UNIVERSITY COLLABORATIONS IN THE FIELD OF RENEWABLE ENERGIES. INTED2021 Proceedings 2021, 411 -416.
AMA StyleAntonio Javier Martínez-Calahorro, Leocadio Hontoria, Antonio José Partal-Ureña, Francisco José Muñoz-Rodríguez, Catalina Rus-Casas. COMPANY-UNIVERSITY COLLABORATIONS IN THE FIELD OF RENEWABLE ENERGIES. INTED2021 Proceedings. 2021; ():411-416.
Chicago/Turabian StyleAntonio Javier Martínez-Calahorro; Leocadio Hontoria; Antonio José Partal-Ureña; Francisco José Muñoz-Rodríguez; Catalina Rus-Casas. 2021. "COMPANY-UNIVERSITY COLLABORATIONS IN THE FIELD OF RENEWABLE ENERGIES." INTED2021 Proceedings , no. : 411-416.
Leocadio Hontoria; Antonio Javier Martínez-Calahorro; Gabino Jiménez-Castillo; Juan Domingo Aguilar-Peña; Catalina Rus-Casas. ACTIVITIES THAT PROMOTE MOTIVATION AND ENTREPRENEURSHIP IN THE MASTER OF RENEWABLE ENERGY. INTED2021 Proceedings 2021, 417 -423.
AMA StyleLeocadio Hontoria, Antonio Javier Martínez-Calahorro, Gabino Jiménez-Castillo, Juan Domingo Aguilar-Peña, Catalina Rus-Casas. ACTIVITIES THAT PROMOTE MOTIVATION AND ENTREPRENEURSHIP IN THE MASTER OF RENEWABLE ENERGY. INTED2021 Proceedings. 2021; ():417-423.
Chicago/Turabian StyleLeocadio Hontoria; Antonio Javier Martínez-Calahorro; Gabino Jiménez-Castillo; Juan Domingo Aguilar-Peña; Catalina Rus-Casas. 2021. "ACTIVITIES THAT PROMOTE MOTIVATION AND ENTREPRENEURSHIP IN THE MASTER OF RENEWABLE ENERGY." INTED2021 Proceedings , no. : 417-423.
Solar irradiation that is received on a terrestrial surface at minor scale of an hour does not have many records, since the current solar irradiation databases generally only have data recorded on a daily (most) and hourly (some less) scale. For places where there are no records of solar irradiation, there are a lot of methods that are used to synthetically or artificially generate these data, and again they are usually methods that generate data on a daily or hourly scale. Currently, for all types of applications, especially in the field of photovoltaic solar energy, irradiation data are needed at minor scale of an hour. In this case, there are very few methods to generate such data. For this purpose, a new methodology to generate series of solar irradiation at temporal high-resolution. In this paper, it is presented on a 10-min basis. A comparative study with real data has been done and the conclusion, as it will be explained is that the proposed methodology provides very good results.
Leocadio Hontoria; Catalina Rus-Casas; Juan Aguilar; Jesús Hernandez. An Improved Method for Obtaining Solar Irradiation Data at Temporal High-Resolution. Sustainability 2019, 11, 5233 .
AMA StyleLeocadio Hontoria, Catalina Rus-Casas, Juan Aguilar, Jesús Hernandez. An Improved Method for Obtaining Solar Irradiation Data at Temporal High-Resolution. Sustainability. 2019; 11 (19):5233.
Chicago/Turabian StyleLeocadio Hontoria; Catalina Rus-Casas; Juan Aguilar; Jesús Hernandez. 2019. "An Improved Method for Obtaining Solar Irradiation Data at Temporal High-Resolution." Sustainability 11, no. 19: 5233.
In order to develop future projects in the field of photovoltaic solar energy, it is essential to accurately know the potential solar resources. There are many methods to estimate the incident solar radiation in a certain place. However, most of them are very expensive or do not have the ideal characteristics for good monitoring of a particular photovoltaic installation. For these reasons, an electronic device connected to the internet of things (IoT) is presented in this paper which manages to measure global radiation in photovoltaic applications. The device developed has been patented in the Spanish Patent and Trademark Office. It presents some features that make it very suitable to measure photovoltaic installations with the advantage of being a low cost and very reliable device. The device has been tested to determine global horizontal irradiance obtaining a correlation coefficient R2 = 0.994.
Rus-Casas C.; Hontoria L.; Fernández-Carrasco J.I.; Jiménez-Castillo G.; Muñoz-Rodríguez F.. Development of a Utility Model for the Measurement of Global Radiation in Photovoltaic Applications in the Internet of Things (IoT). Electronics 2019, 8, 304 .
AMA StyleRus-Casas C., Hontoria L., Fernández-Carrasco J.I., Jiménez-Castillo G., Muñoz-Rodríguez F.. Development of a Utility Model for the Measurement of Global Radiation in Photovoltaic Applications in the Internet of Things (IoT). Electronics. 2019; 8 (3):304.
Chicago/Turabian StyleRus-Casas C.; Hontoria L.; Fernández-Carrasco J.I.; Jiménez-Castillo G.; Muñoz-Rodríguez F.. 2019. "Development of a Utility Model for the Measurement of Global Radiation in Photovoltaic Applications in the Internet of Things (IoT)." Electronics 8, no. 3: 304.
Renewable energies have experienced a great growth in recent years, and nowadays participate in the set of energies used in developed and developing countries to produce electricity. Among these technologies, photovoltaic energy, which produces clean electricity from the Sun, is the one that has grown faster, and its implementation all over the world is a guarantee of a solid and efficient energy technology. Nevertheless, in order to design very efficient solar energy systems, it is crucial to have a good solar radiation database. There are databases where it is possible to find information on solar radiation, but only for horizontal surfaces. Afterwards, it is necessary to transform the horizontal solar radiation data to tilt solar radiation data. This transformation is not easy, and the application of complex mathematical equations, and expressions, and difficult algorithms must be done. An application called virtual laboratory “OrientSol 3.0” which allows the user to easily obtain the solar radiation for any tilt surface has been developed by us. Thus, our main objectives in this paper are to present the developed virtual laboratory and to explain its main features and core functionalities. In order to point out the difficulties and complexity of the transformation of horizontal solar radiation data to tilt solar radiation data, we will present some examples of the results this application provides and compare the solar radiation data supplied with this application with some other solar radiation data obtained from other databases.
Mirian Jiménez-Torres; Catalina Rus-Casas; Lenin Guillermo Lemus-Zúiga; Leocadio Hontoria. The Importance of Accurate Solar Data for Designing Solar Photovoltaic Systems—Case Studies in Spain. Sustainability 2017, 9, 247 .
AMA StyleMirian Jiménez-Torres, Catalina Rus-Casas, Lenin Guillermo Lemus-Zúiga, Leocadio Hontoria. The Importance of Accurate Solar Data for Designing Solar Photovoltaic Systems—Case Studies in Spain. Sustainability. 2017; 9 (2):247.
Chicago/Turabian StyleMirian Jiménez-Torres; Catalina Rus-Casas; Lenin Guillermo Lemus-Zúiga; Leocadio Hontoria. 2017. "The Importance of Accurate Solar Data for Designing Solar Photovoltaic Systems—Case Studies in Spain." Sustainability 9, no. 2: 247.
Florencia Almonacid; Pedro Perez-Higueras; Eduardo Fernández; Leocadio Hontoria. A methodology based on dynamic artificial neural network for short-term forecasting of the power output of a PV generator. Energy Conversion and Management 2014, 85, 389 -398.
AMA StyleFlorencia Almonacid, Pedro Perez-Higueras, Eduardo Fernández, Leocadio Hontoria. A methodology based on dynamic artificial neural network for short-term forecasting of the power output of a PV generator. Energy Conversion and Management. 2014; 85 ():389-398.
Chicago/Turabian StyleFlorencia Almonacid; Pedro Perez-Higueras; Eduardo Fernández; Leocadio Hontoria. 2014. "A methodology based on dynamic artificial neural network for short-term forecasting of the power output of a PV generator." Energy Conversion and Management 85, no. : 389-398.
Nowadays there are a lot of problems concerning the use of energy among society, so a greater support to the renewable energies must be present. Some professors from the University of Jaen, Spain, have wide experience in the field of didactic resources for renewable energies subjects teaching. The use of solar energy in order to obtain electricity is called solar energy photovoltaic. This transformation is possible due to the photovoltaic effect. To design a photovoltaic system in any location it is essential to know the exact amount of solar resource available in the area. For this purpose, collecting data on solar radiation becomes crucial. Currently, there exist databases where we can find information on solar radiation but only for horizontal surfaces (known as global solar irradiance on horizontal surfaces). After this, by applying really complex mathematical equations and algorithms, it is possible to obtain solar radiation data for non-horizontal surfaces. In the present work a virtual laboratory which we developed by us is explained. The virtual laboratory “OrientSol 2.0” is an application developed with Matlab© which allows the users (students) to easily obtain the solar radiation on a non-horizontal surface (variations on tilt and orientation). Also, in this work we present all the experience acquired in some years at the University of Jaen when using this virtual laboratory by students from the following courses: Degree in Electronic Industrial Engineering and Master in Renewable Energy.
Catalina Rus-Casas; Leocadio Hontoria; M. Jiménez-Torres; Francisco Muñoz-Rodriguez; Florencia Almonacid. Virtual laboratory for the training and learning of the subject solar resource: OrientSol 2.0. 2014 XI Tecnologias Aplicadas a la Ensenanza de la Electronica (Technologies Applied to Electronics Teaching) (TAEE) 2014, 1 -6.
AMA StyleCatalina Rus-Casas, Leocadio Hontoria, M. Jiménez-Torres, Francisco Muñoz-Rodriguez, Florencia Almonacid. Virtual laboratory for the training and learning of the subject solar resource: OrientSol 2.0. 2014 XI Tecnologias Aplicadas a la Ensenanza de la Electronica (Technologies Applied to Electronics Teaching) (TAEE). 2014; ():1-6.
Chicago/Turabian StyleCatalina Rus-Casas; Leocadio Hontoria; M. Jiménez-Torres; Francisco Muñoz-Rodriguez; Florencia Almonacid. 2014. "Virtual laboratory for the training and learning of the subject solar resource: OrientSol 2.0." 2014 XI Tecnologias Aplicadas a la Ensenanza de la Electronica (Technologies Applied to Electronics Teaching) (TAEE) , no. : 1-6.
In this paper, an artificial neural network (ANN) is used for the generation of ambient temperature hourly time series for some Spanish locations. The model was trained and tested with ten locations and different years of data. Results show that the proposed artificial neural network provides a better approach than other methods. The aim of this paper is to provide a complete description of this ANN so that, it can be used by anyone avoiding all the design, training and testing process again.
F. Almonacid; P. Pérez-Higueras; P. Rodrigo; L. Hontoria. Generation of ambient temperature hourly time series for some Spanish locations by artificial neural networks. Renewable Energy 2013, 51, 285 -291.
AMA StyleF. Almonacid, P. Pérez-Higueras, P. Rodrigo, L. Hontoria. Generation of ambient temperature hourly time series for some Spanish locations by artificial neural networks. Renewable Energy. 2013; 51 ():285-291.
Chicago/Turabian StyleF. Almonacid; P. Pérez-Higueras; P. Rodrigo; L. Hontoria. 2013. "Generation of ambient temperature hourly time series for some Spanish locations by artificial neural networks." Renewable Energy 51, no. : 285-291.
Concentrator Photovoltaic (CPV) systems only work with the Direct Normal Irradiance (DNI), so a knowledge of DNI data is required for the design and evaluation of these kinds of systems. DNI is not always measured at ground meteorological stations due to equipment costs. In recent years, several spatial databases that estimate DNI from satellite data have been developed. These databases are a very useful tool for CPV applications. However, the databases present uncertainty and provide different values of DNI. This lack of DNI data and the uncertainty of available data contrast with the availability of reliable global horizontal irradiation data, which is easy to find or measure. In this paper, a simple procedure for estimating DNI from global horizontal irradiation is presented. It does not try to improve the existing methods, but meets the basic requirements for the analysis of CPV systems. The method can be easily implemented in a spreadsheet or in computer programs in renewable energy and its accuracy is similar than that of the existing databases.
P. M. Rodrigo; Pedro Perez-Higueras; Florencia Almonacid; Leocadio Hontoria; Eduardo Fernández; Catalina Rus-Casas; Juan I. Fernández; Pedro Gómez; Gabino Almonacid. Calculation of direct normal irradiation from global horizontal irradiation. AIP Conference Proceedings 2012, 1477, 391 .
AMA StyleP. M. Rodrigo, Pedro Perez-Higueras, Florencia Almonacid, Leocadio Hontoria, Eduardo Fernández, Catalina Rus-Casas, Juan I. Fernández, Pedro Gómez, Gabino Almonacid. Calculation of direct normal irradiation from global horizontal irradiation. AIP Conference Proceedings. 2012; 1477 (1):391.
Chicago/Turabian StyleP. M. Rodrigo; Pedro Perez-Higueras; Florencia Almonacid; Leocadio Hontoria; Eduardo Fernández; Catalina Rus-Casas; Juan I. Fernández; Pedro Gómez; Gabino Almonacid. 2012. "Calculation of direct normal irradiation from global horizontal irradiation." AIP Conference Proceedings 1477, no. 1: 391.
The use of concentrators implies that CPV systems only work with the Direct Normal Irradiance (DNI). So it is necessary to know DNI data in order to estimate the energy that will be produced by the system, perform economic analysis, supervise plant operation, etc. However, DNI Typical Meteorological Year datasets are expensive and rarely available due to the cost and sophistication of measurement devices and data processing requirements. Particularly, there is a lack of data on the Sunbelt countries, which are more favorable for the use of CPV. In this work, an artificial neural network is used for the generation of DNI hourly time series for some Spanish locations. The model was trained and tested with different locations and different year's data. Although several authors have proposed different methods for the generation of solar radiation synthetic series, these methods are for global radiation and flat panel, nevertheless, we calculate them for direct normal solar radiation and used for CPV systems. A Multilayer Perceptron is explained, looking over the first rudimentary initial version and the last more elaborated final version. Finally, an application of this methodology is presented.
J. Rodrigo; Leocadio Hontoria; Florencia Almonacid; Eduardo F. Fernández; P. M. Rodrigo; P. J. Pérez-Higueras. Artificial neural networks for the generation of direct normal solar annual irradiance synthetic series. AIP Conference Proceedings 2012, 1477, 198 .
AMA StyleJ. Rodrigo, Leocadio Hontoria, Florencia Almonacid, Eduardo F. Fernández, P. M. Rodrigo, P. J. Pérez-Higueras. Artificial neural networks for the generation of direct normal solar annual irradiance synthetic series. AIP Conference Proceedings. 2012; 1477 (1):198.
Chicago/Turabian StyleJ. Rodrigo; Leocadio Hontoria; Florencia Almonacid; Eduardo F. Fernández; P. M. Rodrigo; P. J. Pérez-Higueras. 2012. "Artificial neural networks for the generation of direct normal solar annual irradiance synthetic series." AIP Conference Proceedings 1477, no. 1: 198.
The design and analysis of CPV systems require knowledge of direct normal solar irradiation but ground-based measurements of these data are only available for very few locations. Nowadays, meteorological databases that estimate direct normal irradiation from satellite images and other data sources are used. However, values provided by the different existing databases show large dispersion due to different estimation methods, input data and base years. In this paper, a simplified method for calculating direct normal irradiation is presented. It has been obtained from previous models proposed by several authors. One of its advantages is that it only requires latitude and global horizontal irradiation as input data. As global irradiation is easy to find or measure, the procedure becomes a useful tool in renewable energy applications. The accuracy of this method is similar to that of the existing databases and it is able to easily generate a mass of direct normal irradiation data for different areas worldwide.
P.J. Pérez-Higueras; P. Rodrigo; E.F. Fernández; F. Almonacid; L. Hontoria. A simplified method for estimating direct normal solar irradiation from global horizontal irradiation useful for CPV applications. Renewable and Sustainable Energy Reviews 2012, 16, 5529 -5534.
AMA StyleP.J. Pérez-Higueras, P. Rodrigo, E.F. Fernández, F. Almonacid, L. Hontoria. A simplified method for estimating direct normal solar irradiation from global horizontal irradiation useful for CPV applications. Renewable and Sustainable Energy Reviews. 2012; 16 (8):5529-5534.
Chicago/Turabian StyleP.J. Pérez-Higueras; P. Rodrigo; E.F. Fernández; F. Almonacid; L. Hontoria. 2012. "A simplified method for estimating direct normal solar irradiation from global horizontal irradiation useful for CPV applications." Renewable and Sustainable Energy Reviews 16, no. 8: 5529-5534.
The use of photovoltaics for electricity generation purposes has recorded one of the largest increases in the field of renewable energies. The energy production of a grid-connected PV system depends on various factors. In a wide sense, it is considered that the annual energy provided by a generator is directly proportional to the annual radiation incident on the plane of the generator and to the installed nominal power. However, a range of factors is influencing the expected outcome by reducing the generation of energy. The aim of this study is to compare the results of four different methods for estimating the annual energy produced by a PV generator: three of them are classical methods and the fourth one is based on an artificial neural network developed by the R&D Group for Solar and Automatic Energy at the University of Jaen. The results obtained shown that the method based on an artificial neural network provides better results than the alternative classical methods in study, mainly due to the fact that this method takes also into account some second order effects, such as low irradiance, angular and spectral effects.
F. Almonacid; Catalina Rus-Casas; Pedro Perez-Higueras; Leocadio Hontoria. Calculation of the energy provided by a PV generator. Comparative study: Conventional methods vs. artificial neural networks. Energy 2011, 36, 375 -384.
AMA StyleF. Almonacid, Catalina Rus-Casas, Pedro Perez-Higueras, Leocadio Hontoria. Calculation of the energy provided by a PV generator. Comparative study: Conventional methods vs. artificial neural networks. Energy. 2011; 36 (1):375-384.
Chicago/Turabian StyleF. Almonacid; Catalina Rus-Casas; Pedro Perez-Higueras; Leocadio Hontoria. 2011. "Calculation of the energy provided by a PV generator. Comparative study: Conventional methods vs. artificial neural networks." Energy 36, no. 1: 375-384.
The growth of photovoltaic (PV) for electricity generation is one of the highest in the field of the renewable energies and this tendency is expected to continue in the next years. As an obvious consequence, an increasing number of new PV components and devices, mainly arrays and inverters, are coming into the PV market. The need for PV arrays and inverters to be characterized has then become a more and more important aspect. Due to the variable nature of the operating conditions in PV systems, the complete characterization of these elements is quite a difficult issue. One aspect that can help to achieve this goal is to improve methods for estimating the energy produced by photovoltaic generators. Overall, the annual energy provided by a PV generator is directly proportional to the annual radiation incident on the plane of PV generator and the installed nominal power or peak power. However, there are a number of reasons that cause a decrease in the expected energy and include; mismatch losses, dirt and dust, ohmic losses and many more. In this chapter we present two new studies in the PV field. The first one concerns the application of the Artificial Neural Networks (ANN) for estimating the instantaneous Performance Ratio, which is the fundamental parameter in the characterization of PV systems. The second study aims to compare the results of several methods for estimating the annual energy produced by a PV generator, three classical and one based on artificial neural networks, in different types of systems with different settings and types of modules.
Florencia Almonacid; Catalina Rus-Casas; Pedro Perez-Higueras; Leocadio Hontoria. Two New Applications of Artificial Neural Networks: Estimation of Instantaneous Performance Ratio and of the Energy Produced by PV Generators. Soft Computing Applications for Group Decision-making and Consensus Modeling 2011, 199 -232.
AMA StyleFlorencia Almonacid, Catalina Rus-Casas, Pedro Perez-Higueras, Leocadio Hontoria. Two New Applications of Artificial Neural Networks: Estimation of Instantaneous Performance Ratio and of the Energy Produced by PV Generators. Soft Computing Applications for Group Decision-making and Consensus Modeling. 2011; ():199-232.
Chicago/Turabian StyleFlorencia Almonacid; Catalina Rus-Casas; Pedro Perez-Higueras; Leocadio Hontoria. 2011. "Two New Applications of Artificial Neural Networks: Estimation of Instantaneous Performance Ratio and of the Energy Produced by PV Generators." Soft Computing Applications for Group Decision-making and Consensus Modeling , no. : 199-232.
The presence of PV modules made with new technologies and materials is increasing in PV market, in special Thin Film Solar Modules (TFSM). They are ready to make a substantial contribution to the world's electricity generation. Although Si wafer-based cells account for the most of increase, technologies of thin film have been those of the major growth in last three years. During 2007 they grew 133%. On the other hand, manufacturers provide ratings for PV modules for conditions referred to as Standard Test Conditions (STC). However, these conditions rarely occur outdoors, so the usefulness and applicability of the indoors characterisation in standard test conditions of PV modules is a controversial issue. Therefore, to carry out a correct photovoltaic engineering, a suitable characterisation of PV module electrical behaviour is necessary. The IDEA Research Group from Jaén University has developed a method based on artificial neural networks (ANNs) to electrical characterisation of PV modules. An ANN was able to generate V – I curves of si-crystalline PV modules for any irradiance and module cell temperature. The results show that the proposed ANN introduces a good accurate prediction for si-crystalline PV modules performance when compared with the measured values. Now, this method is going to be applied for electrical characterisation of PV CIS modules. Finally, a comparative study with other methods, of electrical characterisation, is done.
Florencia Almonacid; Catalina Rus-Casas; Leocadio Hontoria; Francisco Muñoz-Rodriguez. Characterisation of PV CIS module by artificial neural networks. A comparative study with other methods. Renewable Energy 2010, 35, 973 -980.
AMA StyleFlorencia Almonacid, Catalina Rus-Casas, Leocadio Hontoria, Francisco Muñoz-Rodriguez. Characterisation of PV CIS module by artificial neural networks. A comparative study with other methods. Renewable Energy. 2010; 35 (5):973-980.
Chicago/Turabian StyleFlorencia Almonacid; Catalina Rus-Casas; Leocadio Hontoria; Francisco Muñoz-Rodriguez. 2010. "Characterisation of PV CIS module by artificial neural networks. A comparative study with other methods." Renewable Energy 35, no. 5: 973-980.
Concentrator Photovoltaic (CPV) is showing a growing trend in the energy market as a consequence of the big investment made by the Photovoltaic industry; but this industrial and commercial growth will be successfully possible with the simultaneous creation of standardization norms that certify the reliability and durability of the CPV systems manufactured. Additionally, the revision of the present CPV standard released is a necessary task as some organisms and laboratories are encountering with some technical problems.
E. Muñoz; P.G. Vidal; Gustavo Nofuentes; Leocadio Hontoria; Pedro Perez-Higueras; Julio Terrados; Gabino Almonacid; J. Aguilera. CPV standardization: An overview. Renewable and Sustainable Energy Reviews 2010, 14, 518 -523.
AMA StyleE. Muñoz, P.G. Vidal, Gustavo Nofuentes, Leocadio Hontoria, Pedro Perez-Higueras, Julio Terrados, Gabino Almonacid, J. Aguilera. CPV standardization: An overview. Renewable and Sustainable Energy Reviews. 2010; 14 (1):518-523.
Chicago/Turabian StyleE. Muñoz; P.G. Vidal; Gustavo Nofuentes; Leocadio Hontoria; Pedro Perez-Higueras; Julio Terrados; Gabino Almonacid; J. Aguilera. 2010. "CPV standardization: An overview." Renewable and Sustainable Energy Reviews 14, no. 1: 518-523.
The integration of grid-connected photovoltaic (GCPVS) systems into urban buildings is very popular in industrialized countries. Many countries enhance the international collaboration efforts which accelerate the development and deployment of photovoltaic solar energy as a significant and sustainable renewable energy option. A previous method, based on artificial neural networks (ANNs), has been developed to electrical characterisation of PV modules. This method was able to generate V–I curves of si-crystalline PV modules for any irradiance and module cell temperature. The results showed that the proposed ANN introduced a good accurate prediction for si-crystalline PV modules performance when compared with the measured values. Now, this method, based on ANNs, is going to be applied to obtain a suitable value of the power provided by a photovoltaic installation. Specifically this method is going to be applied to obtain the power provided by a particular installation, the “Univer generator”, since modules used in these works were the same as the ones used in this photovoltaic generator.
Florencia Almonacid; Catalina Rus-Casas; Pedro Perez-Higueras; Leocadio Hontoria. Estimation of the energy of a PV generator using artificial neural network. Renewable Energy 2009, 34, 2743 -2750.
AMA StyleFlorencia Almonacid, Catalina Rus-Casas, Pedro Perez-Higueras, Leocadio Hontoria. Estimation of the energy of a PV generator using artificial neural network. Renewable Energy. 2009; 34 (12):2743-2750.
Chicago/Turabian StyleFlorencia Almonacid; Catalina Rus-Casas; Pedro Perez-Higueras; Leocadio Hontoria. 2009. "Estimation of the energy of a PV generator using artificial neural network." Renewable Energy 34, no. 12: 2743-2750.
Florencia Almonacid; C. Rus; Leocadio Hontoria; M. Fuentes; Gustavo Nofuentes. Characterisation of Si-crystalline PV modules by artificial neural networks. Renewable Energy 2009, 34, 941 -949.
AMA StyleFlorencia Almonacid, C. Rus, Leocadio Hontoria, M. Fuentes, Gustavo Nofuentes. Characterisation of Si-crystalline PV modules by artificial neural networks. Renewable Energy. 2009; 34 (4):941-949.
Chicago/Turabian StyleFlorencia Almonacid; C. Rus; Leocadio Hontoria; M. Fuentes; Gustavo Nofuentes. 2009. "Characterisation of Si-crystalline PV modules by artificial neural networks." Renewable Energy 34, no. 4: 941-949.
Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. AI-techniques have the following features: can learn from examples; are fault tolerant in the sense that they are able to handle noisy and incomplete data; are able to deal with non-linear problems; and once trained can perform prediction and generalization at high speed. AI-based systems are being developed and deployed worldwide in a myriad of applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. AI have been used and applied in different sectors, such as engineering, economics, medicine, military, marine, etc. They have also been applied for modeling, identification, optimization, prediction, forecasting, and control of complex systems. The main objective of this paper is to present an overview of the AI-techniques for sizing photovoltaic (PV) systems: stand-alone PVs, grid-connected PV systems, PV-wind hybrid systems, etc. Published literature presented in this paper show the potential of AI as a design tool for the optimal sizing of PV systems. Additionally, the advantage of using an AI-based sizing of PV systems is that it provides good optimization, especially in isolated areas, where the weather data are not always available.
A. Mellit; S.A. Kalogirou; L. Hontoria; Sulaiman Shaari. Artificial intelligence techniques for sizing photovoltaic systems: A review. Renewable and Sustainable Energy Reviews 2009, 13, 406 -419.
AMA StyleA. Mellit, S.A. Kalogirou, L. Hontoria, Sulaiman Shaari. Artificial intelligence techniques for sizing photovoltaic systems: A review. Renewable and Sustainable Energy Reviews. 2009; 13 (2):406-419.
Chicago/Turabian StyleA. Mellit; S.A. Kalogirou; L. Hontoria; Sulaiman Shaari. 2009. "Artificial intelligence techniques for sizing photovoltaic systems: A review." Renewable and Sustainable Energy Reviews 13, no. 2: 406-419.
Strategic planning processes, which are commonly used as a tool for region development and territorial structuring, can be harnessed by politicians and public administrations, at the local level, to redesign the regional energy system and encourage renewable energy development and environmental preservation. In this sense, the province of Jaén, a southern Spanish region whose economy is mainly based on olive agriculture, has carried out its strategic plan aiming at a major socioeconomic development. Under the leadership of the provincial government and the University of Jaén, main provincial institutions joined to propose the elaboration of a participatory strategic plan for the whole province. Here, the elaboration of the energy part of the plan, which was directly focused on the exploitation of renewable resources, mainly solar and biomass energy, and which highlights the effectiveness of techniques from business management applied to a sustainable energy model design is presented. Renewable Energy development during the first years of plan execution is presented, and the impact of additional issues is discussed. It is concluded that, although multicriteria decision-making technologies (MCDA) are extensively used in energy planning, a different approach can be utilized to incorporate techniques from strategic analysis. Furthermore, SWOT (strengths, weaknesses, opportunities and threats) analysis has proved to be an effective tool and has constituted a suitable baseline to diagnose current problems and to sketch future action lines.
Julio Terrados; Gabino Almonacid; Leocadio Hontoria. Regional energy planning through SWOT analysis and strategic planning tools.: Impact on renewables development. Renewable and Sustainable Energy Reviews 2007, 11, 1275 -1287.
AMA StyleJulio Terrados, Gabino Almonacid, Leocadio Hontoria. Regional energy planning through SWOT analysis and strategic planning tools.: Impact on renewables development. Renewable and Sustainable Energy Reviews. 2007; 11 (6):1275-1287.
Chicago/Turabian StyleJulio Terrados; Gabino Almonacid; Leocadio Hontoria. 2007. "Regional energy planning through SWOT analysis and strategic planning tools.: Impact on renewables development." Renewable and Sustainable Energy Reviews 11, no. 6: 1275-1287.
L. Hontoria; J. Aguilera; P. Zufiria. An application of the multilayer perceptron: Solar radiation maps in Spain. Solar Energy 2005, 79, 523 -530.
AMA StyleL. Hontoria, J. Aguilera, P. Zufiria. An application of the multilayer perceptron: Solar radiation maps in Spain. Solar Energy. 2005; 79 (5):523-530.
Chicago/Turabian StyleL. Hontoria; J. Aguilera; P. Zufiria. 2005. "An application of the multilayer perceptron: Solar radiation maps in Spain." Solar Energy 79, no. 5: 523-530.