Benchmarking the performance of controllers for power grid transient stability
Queen Mary University of London（伦敦大学玛丽女王学院）；Università di Catania（卡塔尼亚大学）；INFN（意大利国家核物理研究所）；Technical University of Dresden（德累斯顿工业大学）；Max Planck Institute for Dynamics and Self-Organization（马克斯·普朗克动态与自组织研究所）
Randall Martyr, Benjamin Schaefer, Christian Beck, Vito Latora
备注：
Major revision with more descriptive third-order model, updated simulations for a new four-node network, and two more controllers added to the comparison. 14 pages, two columns, 6 figures with 19 subfigures in total. Results from previous version with two-node and five-node networks are still applicable
As the energy transition transforms power grids across the globe, it poses several challenges regarding grid design and control. In particular, high levels of intermittent renewable generation complicate the task of continuously balancing power supply and demand, requiring sufficient control actions. Although there exist several proposals to control the grid, most of them have not demonstrated to be cost efficient in terms of optimal control theory. Here, we mathematically formulate an optimal centralized (therefore non-local) control problem for stable operation of power grids and determine the minimal amount of active power necessary to guarantee a stable service within the operational constraints, minimizing a suitable cost function at the same time. This optimal control can be used to benchmark control proposals and we demonstrate this benchmarking process by investigating the performance of three distributed controllers, two of which are fully decentralized, that have been recently studied in the physics and power systems engineering literature. Our results show that cost efficient controllers distribute the controlled response amongst all nodes in the power grid. Additionally, superior performance can be achieved by incorporating sufficient information about the disturbance causing the instability. Overall, our results can help design and benchmark secure and cost-efficient controllers.
Learning over All Stabilizing Nonlinear Controllers for a Partially-Observed Linear System
Sydney Institute for Robotics and Intelligent Systems（悉尼机器人与智能系统研究所）；Australian Centre for Field Robotics（澳大利亚野外机器人中心）；School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney（悉尼大学航空航天、机械与机电工程学院）
Robust Decentralized Secondary Frequency Control in Power Systems: Merits and Trade-Offs
University of Groningen（格罗宁根大学）；Johns Hopkins University（约翰斯·霍普金斯大学）；National Renewable Energy Laboratory（国家可再生能源实验室）；Swiss Federal Institute of Technology (ETH) Zürich（苏黎世联邦理工学院）
