The Role of Prediction And Real-time Learning in Online Optimization and Control

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• Na Li (Harvard University)
• Thursday 02 May 2019, 10:00-11:00
• Seminar Room 1, Newton Institute.

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MESW03 - Closing workshop: Looking forward to 2050

Uncertainties place a key challenge in transforming the grid into one with a large renewable energy integration and active users' participation. The volatile renewable generation constantly introduces disturbance to the grid operation; while the stochastic user behavior makes it difficult to use demand as a reliable resource for balancing real-time supply-demand. This talk will present two lines of work to address these issues. Firstly, we will study how to use a short term prediction, e.g., renewable energy, to improve the performance for online optimization and control, e.g, economic dispatch with ramping cost. Then, we will study how to use real-time learning to design residential demand response programs for achieving grid reliability while balancing the exploitation and exploration of the uncertain user behavior.

This talk is part of the Isaac Newton Institute Seminar Series series.

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