Title :
Model-Predictive Cascade Mitigation in Electric Power Systems With Storage and Renewables—Part II: Case-Study
Author :
Almassalkhi, Mads R. ; HISKENS, Ian A.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA
Abstract :
The novel cascade-mitigation scheme developed in Part I of this paper is implemented within a receding-horizon model predictive control (MPC) scheme with a linear controller model. This present paper illustrates the MPC strategy with a case-study that is based on the IEEE RTS-96 network, though with energy storage and renewable generation added. It is shown that the MPC strategy alleviates temperature overloads on transmission lines by rescheduling generation, energy storage, and other network elements, while taking into account ramp-rate limits and network limitations. Resilient performance is achieved despite the use of a simplified linear controller model. The MPC scheme is compared against a base-case that seeks to emulate human operator behavior.
Keywords :
IEEE standards; cascade control; energy storage; power generation control; power generation scheduling; power transmission lines; predictive control; renewable energy sources; IEEE RTS-96 network; MPC scheme; electric power system; energy storage; linear controller model; model predictive control scheme; model-predictive cascade mitigation; power generation rescheduling; ramp-rate limit; renewable generation; transmission line; Conductors; Energy storage; Generators; Power transmission lines; Temperature measurement; Transmission line matrix methods; Cascade mitigation; convex relaxation; energy storage; model predictive control; modeling; power system operation; receding horizon; thermal overloads;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2014.2320988