DocumentCode :
1774715
Title :
A operational optimization model for wind power and pumped-storage plant based on stochastic programming
Author :
Chunliui Liu ; Liudong Zhang ; Wanxia Liu
Author_Institution :
Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
fYear :
2014
fDate :
23-26 Sept. 2014
Firstpage :
1589
Lastpage :
1595
Abstract :
Based on the day-ahead forecast of system load and wind power output. A joint operation of pumped-storage and wind power plants model is built with the purpose of minimizing the system operation cost. In order to achieve the higher system flexibility and reduce the impact of volatility of wind power, pumped-storage units are incorporated into the unit commitment (UC) problem with wind power. The UC problem of the joint operation of pumped-storage and wind power plants is formulated as the mixed-integer convex program, which is optimized by Cplex. Conducted on a ten-unit system simulation, we can get the conclusion that the joint operation of pumped-storage and wind power plants is effective to reduce the impact of volatility of wind power on the power grid operation. At the same time, economic benefit is remarkable.
Keywords :
convex programming; cost reduction; integer programming; load forecasting; power generation dispatch; power generation economics; power generation scheduling; pumped-storage power stations; stochastic programming; wind power plants; Cplex optimization; UC problem; day-ahead forecasting system; mixed-integer convex program; operation cost minimization; operational optimization model; power grid operation; power system economics; pumped-storage plant; stochastic programming; unit commitment problem; wind power plant; Abstracts; Analytical models; Flowcharts; IP networks; Problem-solving; Programming; Vectors; joint operation; mixed-integer programming; pumped-storage; wind power; wind power scenario;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electricity Distribution (CICED), 2014 China International Conference on
Conference_Location :
Shenzhen
Type :
conf
DOI :
10.1109/CICED.2014.6991974
Filename :
6991974
Link To Document :
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