Title :
Temperature-based Model-Predictive Cascade Mitigation in Electric Power Systems
Author :
Almassalkhi, Mads ; Hiskens, Ian
Author_Institution :
Dept. of Electr. Eng.: Syst., Univ. of Michigan, Ann Arbor, MI, USA
Abstract :
This paper proposes a novel model-predictive control scheme which combines both economic and security objectives to mitigate the effects of severe disturbances in electrical power systems. A linear convex relaxation of the AC power flow is employed to model transmission line losses and conductor temperatures. Then, a receding-horizon model predictive control (MPC) strategy is developed to alleviate line temperature overloads and prevent the propagation of outages. The MPC strategy seeks to alleviate temperature overloads by rescheduling generation, energy storage and other network elements, subject to ramp-rate limits and network limitations. The MPC strategy is illustrated with simulations of the IEEE RTS-96 network augmented with energy storage and renewable generation.
Keywords :
load flow; power system control; power system economics; power system security; predictive control; AC power flow; conductor temperatures; electric power systems; energy storage; linear convex relaxation; model predictive control scheme; network limitations; ramp rate limits; receding horizon model predictive control strategy; renewable generation; temperature based model predictive cascade mitigation; temperature overloads; transmission line losses; Approximation methods; Conductors; Economics; Power system dynamics; Schedules; Temperature control;
Conference_Titel :
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location :
Firenze
Print_ISBN :
978-1-4673-5714-2
DOI :
10.1109/CDC.2013.6761090