Smart Solar Energy for the Smart Grid
Solar photovoltaic (PV) installations traditionally are stand-alone systems without integrated computation. However, it is possible to utilize real-time processes to adaptively reconfigure solar PV installations while sensing and computing the environmental factors. This talk will introduce new concepts that allow the solar installations to adapt their performance depending on their environmental conditions. For example, a smart PV panel has been built that can self-heal and self-optimize to produce higher power. Specialized solar fuses can even communicate between themselves and the panels to give diagnostics for dangerous and previously undetectable faults.
Future visions of the research are to utilize sensor information, weather patterns, and high performance computing in order to predict PV power in large geographical regions. This requires, the combination of sophisticated solar theoretical models, statistical signal processing, and fast algorithms. The potential of the synergies of these elements may lead to better prediction of output power production on multiple time scales: minutes, hours, days, months and years. This information is vital for the future of smart grid operation.
Brad Lehman is presently a Professor in the Department of Electrical and Computer Engineering at Northeastern University and previously was a Hearin Hess Distinguished Assistant Professor at Mississippi State University. Dr. Lehman was previously an NSF Presidential Faculty Fellow, an Alcoa Science Foundation Fellowship and a visiting scientist at MIT. Professor Lehman was recently highlighted in the inaugural edition of the book The 300 Best Professors, Princeton Review, 2012. He is Editor-in-Chief of the IEEE Transactions on Power Electronics.