Abstract
The exploitation of solar power for energy supply is of increasing importance. While technical development mainly takes place in the engineering disciplines, computer science offers adequate techniques for simulation, optimisation and controller synthesis.
In this paper we describe a work from this interdisciplinary area. We introduce our tool for the optimisation of parameterised solar thermal power plants, and report on the employment of genetic algorithms and neural networks for parameter synthesis. Experimental results show the applicability of our approach.
This work is based on the Fraunhofer ISE project “optisim”, which was funded by the German Ministry of Environment (project number FKZ 0325045).
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Richter, P., Ábrahám, E., Morin, G. (2011). Optimisation of Concentrating Solar Thermal Power Plants with Neural Networks. In: Dobnikar, A., Lotrič, U., Šter, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2011. Lecture Notes in Computer Science, vol 6593. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20282-7_20
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DOI: https://doi.org/10.1007/978-3-642-20282-7_20
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