Title :
Optimal storage scheduling for minimizing schedule deviations considering variability of generated wind power
Author :
Dutta, S. ; Overbye, T.J.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
Abstract :
Incorporation of energy storage units with wind farms is being considered critical for wind farms to address variability in wind power generation and meeting committed generation schedules. However, operational constraints such as limited energy of storage units, in addition to the inherent variability of wind power, limit the maximum generation commitment that can be met reliably by a wind farm operating in combination with a storage plant. This paper presents a method for computing an optimal storage dispatch for a storage unit coupled with a wind farm over the period of one hour with the objective of minimizing generation schedule deviations and taking into consideration the uncertainties involved in wind power predictions. The optimization uses a stochastic dynamic programming framework in discrete time. The algorithm minimizes the total expected deviations from a steady power delivery schedule of the combined wind farm-energy storage plant. Tests on a simplified model of a wind-storage plant connected to a load verify the desired objectives. The deviations when generated wind power is known accurately are also presented as a special case. Results provide insights about the maximum generation commitment the combined wind-storage unit can meet without deviations over the scheduling horizon given the probabilities of power generation from wind.
Keywords :
dynamic programming; power generation dispatch; power generation scheduling; stochastic processes; wind power plants; optimal storage dispatch; optimal storage scheduling; power generation probability; schedule deviation minimization; stochastic dynamic programming framework; wind farm energy storage plant; wind power generation; wind power predictions; wind storage unit; Discharges; Dynamic programming; Energy storage; Schedules; Wind; Wind farms; Wind power generation; coordination of energy storage with wind; generation schedule; probability distribution of wind power; schedule deviation; stochastic dynamic programming; storage optimization;
Conference_Titel :
Power Systems Conference and Exposition (PSCE), 2011 IEEE/PES
Conference_Location :
Phoenix, AZ
Print_ISBN :
978-1-61284-789-4
Electronic_ISBN :
978-1-61284-787-0
DOI :
10.1109/PSCE.2011.5772521