Xiaoyu Kevin Zhang, EE PhD student, takes the Best Paper Award for “Feeder-Level Deep Learning-based Photovoltaic Penetration Estimation Scheme” at 2020 IEEE APPEEC. Congratulations Kevin!
We are proud to announce that Kevin has received the Best Paper Award for his paper “Feeder-Level Deep Learning-based Photovoltaic Penetration Estimation Scheme” presented at the 12th IEEE PES Asia-Pacific Power and Energy Engineering Conference, one of the most influential international conferences in the field of electric energy held in the Asia-Pacific region.
In the paper presented, Kevin proposes a novel hybrid regression multi-layer perceptron (MLP) deep neural network (DNN) model to disaggregate grid measurement into load power and power generated by PV power. The method enables online and offline energy estimation, which is very practical for industrial applications to increase the visibility of load components.
For more info about the paper or his research please contact Kevin.