Visible to the public Wide-Area Damping Control Using Multiple DFIG-Based Wind Farms Under Stochastic Data Packet Dropouts

TitleWide-Area Damping Control Using Multiple DFIG-Based Wind Farms Under Stochastic Data Packet Dropouts
Publication TypeConference Paper
Year of Publication2019
AuthorsYogarathinam, A., Chaudhuri, N. R.
Conference Name2019 IEEE Power Energy Society General Meeting (PESGM)
Keywordsasynchronous generators, Communication channels, communication network, computer network security, cyber system, Cyber-physical systems, damping, damping performance, distributed phasor measurement units, feedback, Gilbert-Elliott model, Monte Carlo methods, Monte Carlo simulation, multiple DFIG-based wind farms, networked phasor measurement units, nonlinear time-domain simulations, observer-driven reduced copy approach, Observers, ORC, phasor measurement, power engineering computing, power generation control, power system security, power system stability, pubcrawl, remote feedback signals, resilience, Resiliency, Scalability, smart power grid, smart power grids, Stochastic Computing Security, stochastic data packet dropouts, Stochastic processes, telecommunication channels, time-domain analysis, wide-area oscillation damping control, wind energy resources, wind power plants
AbstractData dropouts in communication network can have a significant impact on wide-area oscillation damping control of a smart power grid with large-scale deployment of distributed and networked phasor measurement units and wind energy resources. Remote feedback signals sent through communication channels encounter data dropout, which is represented by the Gilbert-Elliott model. An observer-driven reduced copy (ORC) approach is presented, which uses the knowledge of the nominal system dynamics during data dropouts to improve the damping performance where conventional feedback would suffer. An expression for the expectation of the bound on the error norm between the actual and the estimated states relating uncertainties in the cyber system due to data dropout and physical system due to change in operating conditions is also derived. The key contribution comes from the analytical derivation of the impact of coupling between the cyber and the physical layer on ORC performance. Monte Carlo simulation is performed to calculate the dispersion of the error bound. Nonlinear time-domain simulations demonstrate that the ORC produces significantly better performance compared to conventional feedback under higher data drop situations.
Citation Keyyogarathinam_wide-area_2019