Scholarly record
AI APPLYING ODDS FOR EFFICIENTLY USING RENEWABLE ENERGY RESOURCES
Abstract
In the context of current global debates about assuring sustainability of human society renewable energy resources have started to find a main role regarding assuring needed energy supply on different levels. In the last time it has been noticed that Artificial Intelligence, AI is transforming the renewable energy sector by optimizing the usage of energy resources like wind, solar, and hydro, which are per-se not constantly available. By applying AI in connection to using renewable energy resources, improving odds can be gathered related to probabilistic forecasting, to optimization algorithms to manage uncertainty and intermittency, and to machine learning. In this contribution Neural Networks will be presented, particularly Artificial Neural Networks, ANNs, being highly effective for solar radiation prediction, achieving high accuracy by succeeding in modeling complex nonlinear relations related to meteorological data. In this scientific contribution some key input parameters will be considered such as temperature, humidity, and wind speed, which can influence solar radiation and by this electricity production by PV systems. The final goal of designing such AI-based techniques is to get increased efficiency, reduced operational costs, and finally lower greenhouse gas emissions avoiding by this anthropogenic global warming and climate change nevertheless maintaining same quality of life of humanity.
Publication details
References13
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