Extreme events, such as heat waves or very strong storms, may cause extensive damage and have substantial impacts on power systems, which post extreme challenges to system operation entities. As the large power infrastructure in the US ages, better understanding and preparing for extreme events is a much needed effort for researchers, operators, and planners. We need approaches to increase grid resiliency and recovery capabilities, as well as improved procedures for decision making and damage evaluation. On the other hand, every extreme event is also a rare learning opportunity. For example, the severe weather event of February 2021, winter storm Uri in Texas, has initiated many studies in academia and industry to examine and improve the ERCOT power grid and utilities’ operating procedures. With all the efforts and achievements, we are hardening and preparing the power grid for future challenges.
"Quantifying Power System Operational and Infrastructural Resilience Under Extreme Conditions Within a Water-Energy Nexus Framework"
S. Zuloaga and V. Vittal, IEEE Open Access Journal of Power and Energy, vol. 8, pp. 229-238, 2021
"Safe Reinforcement Learning-Based Resilient Proactive Scheduling for Commercial Building Considering Correlated Demand Response"
Z. Liang, IEEE Open Access Journal of Power and Energy, vol. 8, pp. 85-96, 2021
A technical report to be submitted by BDA WG on Application of Big Data Analytics on Transmission System Dynamic Security Assessment: “Application of data-driven, and machinelearning algorithms for the secure operation of transmission systems.” This report will present the collective effort of 13 research groups, to provide transmission system operators with innovativetools to be potentially applied in control rooms and may assist operators in both normal andemergency operating situations.
Inverter-based Resources Subsynchronous Oscillations: Events and Mechanism Analysis
IEEE-PES Webinar: July 2022
Speakers: Lingling Fan (USF), Yunzhi Cheng (ERCOT), Jayanth R. Ramamurthy (AEMO), Xiaorong Xie (Tsinghua Univ), Jan Shair (Tsinghua University) , Zhixin Miao (USF) IBR SSO Task Force
This webinar presents a survey of real-world subsynchronous oscillation events associated with inverter-based resources (IBR) over the past decade.
Physics-aware and Risk-aware Machine Learning for Power System Operations
IEEE-PES Webinar: February 2022
Speaker: Hao Zhu
Recent years have witnessed rapid transformations of contemporary advances in machine learning (ML) and data science to aid the transition of energy systems into a truly sustainable, resilient, and distributed infrastructure. A blind application of the latest-and-greatest ML algorithms to solve stylized grid operation problems, however, may fail to recognize the underlying physics models or safety constraint requirements. This talk will introduce three examples of bridging physics- and risk-aware ML advances into efficient and reliable grid operations. First, we develop a topology-aware approach using graph neural networks (GNNs) to predict the price and line congestion as the outputs of real-time optimal power flow problem. Building upon the underlying relation between prices and topology, this proposed solution significantly reduces the model complexity of existing end-to-end ML methods while efficiently adapting to varying grid topology. Second, we put forth a risk-aware ML method to ensure the safety guarantees of data-driven, scalable reactive power dispatch policies in distribution grids. The resultant policies can directly account for the statistical risks on prediction error to attain guaranteed voltage violation performance. Last, we consider a reinforcement learning framework for managing a large number of dynamical, flexible energy resources such as electrical vehicles, and demonstrate the need to simplify the system representation through physics-aware state/action aggregation.
Predicting the onset of cascading failures using machine learning
General Meeting Panel Session: July 2022
Panel session from IEEE PES GM 2022.
Late Breaking News - Texas Energy Crisis
General Meeting Panel Session: July 2021
Speaker: W-J Lee, T. Pierpoint, D. Ortiz, M. Lauby, M. Carpenter
This panel of diverse industry leaders will discuss the realities of the situation and provide balanced perspective on mechanisms through which the effects could be mitigated in the future.
"Real-Time Management of Geomagnetic Disturbances: Hydro One's Extreme Space Weather control room tools"
L. Marti and C. Yiu, IEEE Electrification Magazine, vol. 3, no. 4, pp. 46-51, Dec. 2015
"Mobile and Portable De-Icing Devices for Enhancing the Distribution System Resilience Against Ice Storms: Preventive strategies for damage control"
A. Bahrami, M. Yan, M. Shahidehpour, S. Pandey, A. Vukojevic and E. A. Paaso, IEEE Electrification Magazine, vol. 9, no. 3, pp. 120-129, Sept. 2021
PV powered microgrid energy management algorithms
"A Load Switching Group based Feeder-level Microgrid Energy Management Algorithm for Service Restoration in Power Distribution System"
Rongxing Hu, Yiyan Li, Si Zhang, Ashwin Shirsat, Valliappan Muthukaruppan, Wenyuan Tang, Mesut Baran, David Lubkeman, Ning Lu, Proc. of IEEE PES 2021 General Meeting.
"Hierarchical Multi-timescale Framework For Operation of Dynamic Community Microgrid"
Ashwin Shirsat, Valliappan Muthukaruppan, Rongxing Hu, Ning Lu, Mesut Baran, David Lubkeman, Wenyuan Tang, Proc. of IEEE PES 2021 General Meeting.
Grid support functions developed for PV farms and Battery energy storage systems to supply a microgrid during prolonged outages
“A Novel Grid-forming Voltage Control Strategy for Supplying Unbalanced Microgrid Loads Using Inverter-based Resources"
Bei Xu, Victor Paduani, David Lubkeman, and Ning Lu, Proc. of 2022 PES General Meeting.
“Novel Real-Time EMT-TS Modeling Architecture for Feeder Blackstart Simulations”
Victor Paduani, Bei Xu, David Lubkeman, Ning Lu, Proc. of 2022 PES General Meeting.
"A Unified Power-Setpoint Tracking Algorithm for Utility-Scale PV Systems with Power Reserves and Fast Frequency Response Capabilities"
Paduani, Victor Daldegan, Hui Yu, Bei Xu, and Ning Lu, IEEE Transactions on Sustainable Energy 13, no. 1 pp. 479-490, 2021
- To learn more & get involved, please check out the AMPS website.
- The Big Data Webinar Series WG under AMPS BDA Subcommittee has a tutorial series where experts from industry and academia are invited to speak about a large variety of trending topics including extreme events.