Friday, May 23, 2014

Modeling Solar Radiation

In our tutorial at the 2014 IEEE Innovative Smart Grid Technologies - Asia conference, Tamer Khatib and I covered the application of machine learning techniques for energy applications, in particular for modeling solar radiation. In the first part we explored meta-heuristic search algorithms and envisioned their application for designing distributed, self-organizing control systems using evolutionary algorithms. We provide an open-source software tool, FREVO, to conveniently apply this approach of finding the proper configuration of a local agent.

In the second part, we targeted the problem of solar radiation modeling. After stepping through different classical modeling approaches, we presented the possibility of using artificial neural networks to learn the correlation of input parameters such as latitude, longitude, temperature, humidity, month, day, hour to predict global and diffuse solar radiation. Experiments show that this method can achieve a high accuracy compared to existing models.


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