Title :
Robust Unit Commitment With Wind Power and Pumped Storage Hydro
Author :
Jiang, Ruiwei ; Wang, Jianhui ; Guan, Yongpei
Author_Institution :
Dept. of Ind. & Syst. Eng., Univ. of Florida, Gainesville, FL, USA
fDate :
5/1/2012 12:00:00 AM
Abstract :
As renewable energy increasingly penetrates into power grid systems, new challenges arise for system operators to keep the systems reliable under uncertain circumstances, while ensuring high utilization of renewable energy. With the naturally intermittent renewable energy, such as wind energy, playing more important roles, system robustness becomes a must. In this paper, we propose a robust optimization approach to accommodate wind output uncertainty, with the objective of providing a robust unit commitment schedule for the thermal generators in the day-ahead market that minimizes the total cost under the worst wind power output scenario. Robust optimization models the randomness using an uncertainty set which includes the worst-case scenario, and protects this scenario under the minimal increment of costs. In our approach, the power system will be more reliable because the worst-case scenario has been considered. In addition, we introduce a variable to control the conservatism of our model, by which we can avoid over-protection. By considering pumped-storage units, the total cost is reduced significantly.
Keywords :
AC generators; costing; optimisation; power generation economics; power generation reliability; power generation scheduling; power grids; power markets; pumped-storage power stations; renewable energy sources; wind power plants; day-ahead market; intermittent renewable energy; overprotection avoidance; power grid systems; power system; pumped storage hydro; pumped-storage units; robust optimization approach; robust unit commitment schedule; thermal generators; wind power output scenario; worst-case scenario; Electricity; Generators; Power systems; Robustness; Uncertainty; Wind forecasting; Wind power generation; Generation scheduling; pumped-storage; robust optimization; wind uncertainty;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2011.2169817