The operating conditions of a photovoltaic module determine the amount of electrical energy it generates. To characterise a photovoltaic module it is necessary to know its electrical behaviour (short-circuit current, open-circuit voltage and the voltage and current at the point of maximum power) under certain environmental variables (radiation and temperature).
DaSCI researchers work collaboratively with the research group “Research and Development in Solar Energy” (TEP 101) of the University of Jaén, in the development of methods based on Artificial Intelligence for the characterisation and optimisation of photovoltaic systems with different technologies (flat panel, thin film and concentration) in different scenarios. Information from data acquisition systems from installations of different types and locations has been merged with data from geographic and meteorological information systems to design methods based on neural networks, fuzzy systems and descriptive rules. Work is currently being carried out on the combination of prediction and description methods for the configuration of domestic photovoltaic systems adapted to the consumption curve and characteristics to reduce costs and increase the use of clean energies. This collaboration has enabled the transfer of research results in the field of intelligent buildings. Proof of this is that the Patio 2.12 house, with which the University of Jaén participated in the international competition Solar Decathlon Europe in 2012, incorporated knowledge extracted from some of the models developed, achieving first place in energy management and second overall.
Some significant results:
- Characterisation models for concentrator photovoltaic modules using cooperative competitive radial-based functional networks. DOI: http://dx.doi.org/10.1016/j.eswa.2012.09.016
- Differential evolution models for estimating the maximum power delivered by concentrating photovoltaic modules under real outdoor conditions.
- DOI:
- http://dx.doi.org/10.1016/j.eswa.2015.02.032
- Evolutionary models for exception detection in concentrator photovoltaic modules. DOI: http://dx.doi.org/10.1016/j.knosys.2013.08.001
Period
2008-Current
Researchers
Cristóbal Carmona, María José del Jesus, Pedro González, María Dolores Pérez, Antonio Rivera
Awards
Participation in the international Solar Decathlon Europe competition in 2012, with the Patio 2.12 house.
