DocumentCode
31772
Title
Model-Predictive Cascade Mitigation in Electric Power Systems With Storage and Renewables—Part I: Theory and Implementation
Author
Almassalkhi, Mads R. ; HISKENS, Ian A.
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA
Volume
30
Issue
1
fYear
2015
fDate
Jan. 2015
Firstpage
67
Lastpage
77
Abstract
A novel model predictive control (MPC) scheme is developed for mitigating the effects of severe line-overload disturbances in electrical power systems. A piece-wise linear convex approximation of line losses is employed to model the effect of transmission line power flow on conductor temperatures. Control is achieved through a receding-horizon model predictive control (MPC) strategy which alleviates line temperature overloads and thereby prevents the propagation of outages. The MPC strategy adjusts line flows by rescheduling generation, energy storage and controllable load, while taking into account ramp-rate limits and network limitations. In Part II of this paper, the MPC strategy is illustrated through simulation of the IEEE RTS-96 network, augmented to incorporate energy storage and renewable generation.
Keywords
approximation theory; energy storage; load flow control; piecewise linear techniques; power generation scheduling; power system control; predictive control; IEEE RTS-96 network; MPC scheme; conductor temperatures; controllable load; electrical power systems; energy storage; generation rescheduling; line flows; line losses; line temperature overloads; model predictive control scheme; network limitations; piecewise linear convex approximation; ramp-rate limits; receding-horizon MPC strategy; receding-horizon model predictive control strategy; renewable generation; severe line-overload disturbances; transmission line power flow; Economics; Energy storage; Linear approximation; Load modeling; Power systems; Standards; Cascade mitigation; convex relaxation; energy storage; model predictive control; modeling; optimization; thermal overloads;
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/TPWRS.2014.2320982
Filename
6824273
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