Name
Abstract | ||
|---|---|---|
Model predictive control (MPC) methods have a well-earned reputation for providing on-line solutions to optimal feedback control problems, particularly for systems with control and parameter constraints. Previous work has shown the value of MPC in designing non-disruptive load-shedding strategies for power systems. The nonlinear, non-smooth dynamics of power systems make direct application of MPC difficult though. Therefore previous load-shedding applications of MPC have made use of an approximate discrete-time linear dynamic model that describes perturbations to the system's nominal behavior over a finite-time horizon. This approximate model is based on trajectory sensitivities. The article pursues several enhancements of such MPC-based load-shedding strategies. Specifically, at each MPC stage, we propose using a two-step optimization process to determine the optimal input sequence. This helps in combating the possibility of growing error in the discrete-time approximation if large input modifications are needed. We also consider the effects of varying voltage constraints over the MPC optimization horizon. The new two-step MPC strategies are used to design load-shedding controls that prevent voltage collapse in a ten-bus benchmark-system example. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/Allerton.2012.6483372 | 2012 50TH ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING (ALLERTON) |
Keywords | Field | DocType |
optimal control,predictive control,feedback,linear systems | Mathematical optimization,Optimal control,Nonlinear system,Linear system,Computer science,Control theory,Voltage,Model predictive control,Electric power system,Trajectory,Load Shedding | Conference |
ISSN | Citations | PageRank |
2474-0195 | 0 | 0.34 |
References | Authors | |
1 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mengran Xue | 1 | 61 | 13.36 |
| Ian A. Hiskens | 2 | 502 | 56.93 |