DocumentCode :
580910
Title :
Battery energy storage system load shifting control based on real time load forecast and dynamic programming
Author :
Bao, Guannan ; Lu, Chao ; Yuan, Zhichang ; Lu, Zhigang
Author_Institution :
State Key Lab. of Control & Simulation of Power Syst. & Generation Equipments, Tsinghua Univ., Beijing, China
fYear :
2012
fDate :
20-24 Aug. 2012
Firstpage :
815
Lastpage :
820
Abstract :
Battery energy storage system (BESS) is one of the key technologies for smart grid and load shifting is one of the fundamental functions of BESS. BESS load shifting performance is determined by the availability of accurate load curves and optimization approaches. In this paper, a real-time control strategy based on load forecast and dynamic programming methods is presented. The predicted load curve is updated on-line through regress forecasting. The proposed optimization model is solved by using dynamic programming technique. The objective is peak shaving and prolonging the battery lifetime, and the constraints considered include battery state-of-charge (SOC), cycling times per day, converter capacity and step power. The above control strategy was successfully applied to the 5MW*4hour lithium-Ion BESS demonstration project in Biling substation, China Southern Power Grid. The simulation results based on the actual load data of Biling substation demonstrate the effectiveness.
Keywords :
battery management systems; dynamic programming; load forecasting; load regulation; real-time systems; regression analysis; secondary cells; smart power grids; BESS load shifting control; BESS load shifting performance; Biling substation; China southern power grid; battery SOC; battery energy storage system; battery lifetime prolonging; battery state-of-charge; converter capacity; cycling times; dynamic programming; lithium-ion BESS; optimization model; peak shaving; predicted load curve; real-time load forecasting; regression forecasting; smart grid; step power; Batteries; Discharges (electric); Load forecasting; Load modeling; Optimization; Real-time systems; US Department of Defense; Smart grid; battery energy storage system; dynamic programming; load forecast; load shifting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation Science and Engineering (CASE), 2012 IEEE International Conference on
Conference_Location :
Seoul
ISSN :
2161-8070
Print_ISBN :
978-1-4673-0429-0
Type :
conf
DOI :
10.1109/CoASE.2012.6386377
Filename :
6386377
Link To Document :
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