The stochastic optimal dispatch model considering the uncertain line failures events under extreme weather disasters

• Main Authors: Yongxi Zhang, Hongming Yang, Zhaoyang Dong, Mingyong Lai
• Format: Conference Proceeding
• Language: English
• Subjects: Biological system modeling; chance constraints; differential evolution algorithm; Geology; History; line failure probability; sample average approximation; Simulated annealing; stochastic optimal dispatch
• DOI: 10.1109/POWERCON.2010.5666738

Over the past few years several large scale failures of power system due to natural disasters has caused great loss to national economy. They also aroused the consideration of power network secure operations with the respect to natural disaster. Given that the line failure caused by natural disaster is a low probability event, in this paper, we used Poisson distribution theory to depict the uncertainty of line failure. A stochastic power system optimal dispatch model based on chance constrained programming method is also proposed in this paper as well. To solve the stochastic optimization problems with chance constraints programming effectively and numerically, we used sample average approximation to convert the uncertain stochastic optimal dispatch problems into non-continuous, non-differentiable optimal problems first, then through an improved differential evolution algorithm to calculate the total cost of shedding loads and generation. The results of IEEE 9-bus case study show that the dispatch model can effectively consider the uncertain effect of power components under nature disaster. The methods presented in this paper also provides more reasonable dispatch plan for power system disaster prevention and reduction.