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  • PES
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    Length: 01:02:41
Panel Session 06 Aug 2020

Machine Learning (ML) has become key to power systems operation as we transition to a smarter and cleaner grid with increasing penetration of variable renewable energy. This panel will cover ML applications not only for energy forecasting but also a broad spectrum of energy analytics such as how ML is being used to inform electricity access and to accelerate solution of large scale optimization problems.

At micro-level, the Long Short-Term Memory Network (LSTM) has been employed to predict plug loads of individual buildings and improve energy efficiency. In electricity market, artificial intelligence has been applied in the spot price forecasting, risk management and investment analysis. With increasing alternative data set (i.e., satellite images) and advanced image processing algorithms, researchers are able to evaluate electricity infrastructure and accelerate clean energy deployment. That being said, big data and machine learning weigh in on almost every aspect of the power and energy industry.

Chairs:
Luana Lima, Ao Teng
Primary Committee:
Power System Operations, Planning & Economics (PSOPE)
Sponsor Committees:
Power System Economics Subcommittee

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