2017/10/19 by Fernando Paganini, Enrique Mallada, Paganini, Fernando +1
Computer Science · Engineering · #FOS: Electrical engineering #FOS: Mathematics #Microgrid Control and Optimization #Nonlinear Dynamics and Pattern Formation #Optimization and Control (math.OC) #Power System Optimization and Stability #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1710.07195
openalex publication_date 2017/10/19 · openalex created_date 2022/10/04 · openalex updated_date 2026/07/28
A recent trend in control of power systems has sought to quantify the\nsynchronization dynamics in terms of a global performance metric, compute it\nunder very simplified assumptions, and use it to gain insight on the role of\nsystem parameters, in particular, inertia. In this paper, we wish to extend\nthis approach to more realistic scenarios, by incorporating the heterogeneity\nof machine ratings, more complete machine models, and also to more closely map\nit to classical power engineering notions such as Nadir, Rate of Change of\nFrequency (RoCoF), and inter-area oscillations.\n We consider the system response to a step change in power excitation, and\ndefine the system frequency as a weighted average of generator frequencies\n(with weights proportional to each machine's rating); we characterize Nadir and\nRoCoF by the L_\∞ norm of the system frequency and its derivative,\nrespectively, and inter-areas oscillations by the L2 norm of the error of\nthe vector of bus frequencies w.r.t. the system frequency.\n For machine models where the dynamic parameters (inertia, damping, etc.) are\nproportional to rating, we analytically compute these norms and use them to\nshow that the role of inertia is more nuanced than in the conventional wisdom.\nWith the classical swing dynamics, inertia constant plays a secondary role in\nperformance. It is only when the turbine dynamics are introduced that the\nbenefits of inertia become more prominent.\n