Threshold-Bad-Scenario-Set Robust Unit Commitment Under Wind Power Uncertainty

This paper proposes the threshold-bad-scenario-set (TBS) robust unit commitment (TBSRUC) problem to hedge against wind-power uncertainty, which is described by a finite set of discrete scenarios. In the TBS robust optimization model, a performance threshold is given to define the TBS for a solution. The sum of squared operating-cost degradations relative to the threshold under bad scenarios of TBS is minimized to obtain a robust unit commitment solution. A united-scenario neighborhood (UN) structure is constructed based on the TBS of a unit commitment solution. A memetic algorithm with the UN structure (MAUN) is developed to solve the proposed TBSRUC problem. An extensive experiment was conducted on benchmark systems with different scales. The computational results show that the obtained robust solutions can hedge against wind-power uncertainty by decreasing the number of bad scenarios and the degree of performance degradation under bad scenarios. Moreover, the computational results demonstrate that the developed MAUN is effective and efficient for solving the proposed TBSRUC problem.