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Yuanyuan Presented our Work at INFORMS Annual Meeting

My lab mate, Yuanyuan Shi, presented our joint work at INFORMS Annual Meeting 2017 for Learning, optimization and control for resilient power grids. The work is  focused on building energy control and optimization via deep learning.  It’s quite a unique, general optimal control approach which utilizes deep learning tools for system modeling and optimization. Take a look at our slides: Informs_talk.

Paper submitted to IEEE Transcations on Power Systems

Paper entitles “Model-Free Renewable Scenario Generation Using Generative Adversarial Networks

A work with Yishen Wang, Daniel Kirschen and Baosen Zhang on renewables scenarios generation has been submitted to IEEE Transactions on Power Systems Special Section on
Enabling very high penetration renewable energy integration into future power systems. Take a loot at our Arxiv version: https://arxiv.org/pdf/1707.09676.pdf

Update:  Jan.17th 2017 Paper accepted to IEEE Transactions on Power Systems.  Preprint: http://ieeexplore.ieee.org/document/8260947/