Optimization Methodologies for Uncertainty Characterization with Large-Scale Renewables Integration

The increasing penetration of renewable sources into the power grid brings uncertainty of active power on both the generation side and demand side also increases significantly. Power grid dispatching needs to be transformed from deterministic optimization to uncertain optimization. The scenario-based, stochastic programming, and robust optimization methods are optimization methods that can be used to characterize the uncertainty of renewable energy generation and improve power grid dispatching. This paper utilizes three methods to characterize the uncertainty of renewable output and employs a series of techniques to convert these methods into optimization that can be directly handled by existing solvers. An evaluation of each method is provided at the end.