Stochastic Optimal Power Flow With Joint Chance Constraints Using Generalised Polynomial Chaos

This paper presents a novel approach for the approximation of multiple joint chance constraints. Generalised polynomial chaos is used to model uncertainties, allowing to consider non-Gaussian probability distributions for the input random variables of the system. The effectiveness of the presented approach for the treatment of both individual and joint chance constraints is demonstrated by solving a stochastic dispatching problem on IEEE benchmark systems. Additionally, the approach is compared to state-of-the-art methods for joint chance constraint optimization and current methods for the solution of individual non-Gaussian chance constraints using generalised polynomial chaos. Finally, challenges and limitations for the application of general polynomial chaos methods in real systems and applications are presented.