Research Output per Year
Research Output per Year
Overview
Personal Profile
Yiyun Yao's focus is on enhancing the resilience and operational efficiency of power systems through advanced grid modeling, state estimation techniques, and the integration of distributed energy resources. His work includes developing robust algorithms for real-time optimal power flow, designing anomaly detection schemes for distributed energy resources, and improving the dynamic hosting capacity of photovoltaic systems. By leveraging machine learning and optimization techniques, his research contributes to the advancement of grid modernization and the increased resilience/security of energy systems under various operational scenarios.
Research Interests
Situational awareness
Optimal power flow
Reinforcement learning
Distributed energy resouce management system
Professional Experience
Post-Doctoral Researcher, National Renewable Energy Laboratory (2019-2021)
Research Fellow, Market Services Research and Development, Midcontinent Independent System Operator (2018)
Research Intern, Advanced Grid Modeling, Argonne National Laboratory (2017-2018)
Research Assistant, Robert W. Galvin Center for Electricity Innovation, Illinois Institute of Technology (2013-2014)
Education/Academic Qualification
PhD, Electrical and Computer Engineering, Illinois Institute of Technology
Master, Electrical and Computer Engineering, Illinois Institute of Technology
Fingerprint
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Collaborations and Top Research Areas From the Past 5 Years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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A Measurement-Based Adaptive Voltage Regulation Method Considering Topology Changes
Wang, H., Zhao, J., Yao, Y., Ding, F. & Liang, Y., 2024. 5 p.Research output: Contribution to conference › Paper
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Analytic Neural Network Gaussian Process Enabled Chance-Constrained Voltage Regulation for Active Distribution Systems with PVs, Batteries and EVs
Su, T., Zhao, J., Pei, Y., Yao, Y. & Ding, F., 2024, In: IEEE Transactions on Power Systems.Research output: Contribution to journal › Article › peer-review
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Deep Reinforcement Learning for Microgrid Cost Optimization Considering Load Flexibility
Pei, Y., Yao, Y., Zhao, J., Ding, F. & Wang, J., 2024. 5 p.Research output: Contribution to conference › Paper
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Learning-Based Building Flexibility Estimation and Control to Improve Microgrid Economics and Resilience: Preprint
Ding, F., Yao, Y., Hao, J., Pei, Y., Wang, J. & Zhao, J., 2024. 8 p.Research output: Contribution to conference › Paper
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Online Model-Free DER Dispatch Via Adaptive Voltage Sensitivity Estimation and Chance Constrained Programming
Wang, H., Liang, Y., Yao, Y., Zhao, J. & Ding, F., 2024, In: IEEE Transactions on Power Systems. 39, 6, p. 7318-7330 13 p.Research output: Contribution to journal › Article › peer-review
1 Scopus Citations
Awards and Honors
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IEEE Power and Energy Society General Meeting, Best Paper Award,
Yao, Y. (Recipient), 2023
Prize: Honorary award
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IEEE Power and Energy Society ISPEC Conference, Best Paper Award
Yao, Y. (Recipient), 2021
Prize: Honorary award
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IEEE Transactions on Power Delivery, Outstanding Reviewer
Yao, Y. (Recipient), 2019
Prize: Honorary award
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IEEE Transactions on Power Systems, Outstanding Reviewer
Yao, Y. (Recipient), 2023
Prize: Honorary award