Distributed approaches to secondary frequency control have become a way to address the need for more flexible control schemes in power networks with increasingly distributed generation. The distributed averaging proportional-integral (DAPI) controller presents one such approach. In this paper, we analyze the transient performance of this controller, and specifically address the question of its performance under noisy frequency measurements. Performance is analyzed in terms of an H2 norm metric that quantifies power losses incurred in the synchronization transient. While previous studies have shown that the DAPI controller performs well, in particular in sparse networks and compared to a centralized averaging PI (CAPI) controller, our results prove that additive measurement noise may have a significant negative impact on its performance and scalability. This impact is shown to decrease with an increased inter-nodal alignment of the controllers' integral states, either through increased gains or increased connectivity. For very large and sparse networks, however, the requirement for inter-nodal alignment is so large that a CAPI approach may be preferable. Overall, our results show that distributed secondary frequency control through DAPI is possible and may perform well also under noisy measurements, but requires careful tuning.
On the Lie bracket approximation approach to distributed optimization: Extensions and limitations
Institute for Systems Theory and Automatic Control, University of Stuttgart（斯图加特大学系统与自动控制中心）；Department of Mathematics and Statistics, Queen’s University（女王大学数学与统计系）
Macroscopic Noisy Bounded Confidence Models with Distributed Radical Opinions
Delft University of Technology（代尔夫特理工大学）；Politecnico di Torino（都灵理工学院）；Institute for Problems of Mechanical Engineering, Russian Academy of Sciences (IPME RAS)（俄罗斯科学院机械问题研究所）
