Abstract
The lack of meteorological measurements at a location of interest (target location) constitutes a problem that is crucial for the purposes of both weather forecasting and energy system design/validation. This paper constitutes a pilot study for the accurate estimation of meteorological values at a target location employing the meteorological measurements collected at a nearby location (reference location). Artificial neural networks (ANNs) are investigated and compared with traditional estimation methods. The significance of the improvement obtained via the ANN approach both over the traditional estimation methods as well as over simply considering the measurements at the reference location is demonstrated in a number of energy applications.
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