DocumentCode :
631030
Title :
MPC for reducing energy storage requirement of wind power systems
Author :
Chiao-Ting Li ; Huei Peng ; Jing Sun
Author_Institution :
Dept. of Mech. Eng., Univ. of Michigan, Ann Arbor, MI, USA
fYear :
2013
fDate :
17-19 June 2013
Firstpage :
6607
Lastpage :
6612
Abstract :
This paper discusses using the battery energy storage system (BESS) to mitigate wind power intermittency, so that wind power can be dispatchable on an hourly basis like fossil fuel power plants. In particular, model predictive control (MPC) is used to control the charge and discharge of BESS to compensate for wind power forecast errors and minimize operation costs to the wind farm owner. A ramp rate penalty on wind power scheduling is included in the optimization to make the optimal control trajectory smoother, while the performance is kept intact. Numerical simulations with a one-year long wind power dataset show that MPC controller is much more effective in reducing the operation cost to the wind farm owner than the heuristic control algorithm or conventional reserves, in that BESS with a much smaller capacity will be suffice to achieve the same cost reduction.
Keywords :
battery storage plants; error compensation; load forecasting; numerical analysis; optimal control; power generation control; power generation economics; power generation scheduling; predictive control; wind power plants; MPC controller; battery energy storage system; charge control; discharge control; energy storage requirement reduction; fossil fuel power plants; model predictive control; numerical simulations; operation cost minimization; operation cost reduction; optimal control trajectory smoother; ramp rate penalty; wind farm; wind power forecast error compensation; wind power intermittency mitigation; wind power scheduling; wind power systems; Batteries; Discharges (electric); Heuristic algorithms; System-on-chip; Wind farms; Wind forecasting; Wind power generation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2013
Conference_Location :
Washington, DC
ISSN :
0743-1619
Print_ISBN :
978-1-4799-0177-7
Type :
conf
DOI :
10.1109/ACC.2013.6580876
Filename :
6580876
Link To Document :
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