Adaptive robust unit commitment with renewable integration: An extreme scenarios driven model - Wen Lu; Xinhua Yan; Qia Ding; Qi Liu; Rongzhang Cao; Zhengting Jiang (Energy Reports, 2023)
As the penetration rate of renewable energy continues to increase, the uncertainty problem brought by it is becoming more and more serious. Robust optimization is widely used in the process of unit combination as a method of dealing with uncertainty. However, traditional uncertainty coping method, two-stage robust optimization unit commitment, has problems of nonanticipativity and all-scenario feasibility. For this reason, this paper improves the traditional two-stage robust optimization model. The extreme scenarios are first generated from the vertex scenarios of the polyhedron uncertainty set. According to the generated extreme scenarios set, the two-stage robust optimization is transformed into a stochastic programming simultaneously. Finally, this paper incorporates all-scenario-feasibility and nonanticipativity constraints into the model and an example is designed to verify the validity of the model. The results show that the designed model can meet the requirements of all-scenario-feasibility and nonanticipativity.