Abstract This chapter reviews recent developments of energy systems and corresponding optimization models under uncertainty. A series of commonly used energy system optimization models are analyzed, including stochastic optimization models, robust optimization models, and hybrid models integrated with multiple methods. Characteristics and applications of power systems and distributed energy systems with multiple uncertain variables are briefly described. At the same time, limitations of the application of optimization models and the research direction of energy systems are pointed out. The analysis shows that energy system optimization is developed toward large-scale, complex, and multisystems integration, and the energy system optimization model will be further closely related to machine learning and artificial intelligence in addition to the development trend of complexity and integration.