TY - GEN
T1 - Robust optimal power flow with wind integration using conditional value-at-risk
AU - Zhang, Yu
AU - Giannakis, Georgios B.
PY - 2013
Y1 - 2013
N2 - Integrating renewable energy into the power grid requires intelligent risk-aware dispatch accounting for the stochastic availability of renewables. Toward achieving this goal, a robust DC optimal flow problem is developed in the present paper for power systems with a high penetration of wind energy. The optimal dispatch is obtained as the solution to a convex program with a suitable regularizer, which is able to mitigate the potentially high risk of inadequate wind power. The regularizer is constructed based on the energy transaction cost using conditional value-at-risk (CVaR). Bypassing the prohibitive high-dimensional integral, the distribution-free sample average approximation method is efficiently utilized for solving the resulting optimization problem. Case studies are reported to corroborate the efficacy of the novel model and approach tested on the IEEE 30-bus benchmark system with real operation data from seven wind farms.
AB - Integrating renewable energy into the power grid requires intelligent risk-aware dispatch accounting for the stochastic availability of renewables. Toward achieving this goal, a robust DC optimal flow problem is developed in the present paper for power systems with a high penetration of wind energy. The optimal dispatch is obtained as the solution to a convex program with a suitable regularizer, which is able to mitigate the potentially high risk of inadequate wind power. The regularizer is constructed based on the energy transaction cost using conditional value-at-risk (CVaR). Bypassing the prohibitive high-dimensional integral, the distribution-free sample average approximation method is efficiently utilized for solving the resulting optimization problem. Case studies are reported to corroborate the efficacy of the novel model and approach tested on the IEEE 30-bus benchmark system with real operation data from seven wind farms.
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U2 - 10.1109/SmartGridComm.2013.6688033
DO - 10.1109/SmartGridComm.2013.6688033
M3 - Conference contribution
AN - SCOPUS:84893632069
SN - 9781479915262
T3 - 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013
SP - 654
EP - 659
BT - 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013
T2 - 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013
Y2 - 21 October 2013 through 24 October 2013
ER -