Efficient uncertainty quantification in economic re-dispatch under high wind penetration considering interruptible load

Due to the high variability and intermittency of wind power generation, operators tend to have a corrective stage to adjust their predictive dispatch schedules for re-balancing the system following a contingency in the real-time market. This paper presents a new probabilistic real-time re-dispatch model integrating interruptible load (IL) programs with the aim to minimize the total operational cost. The problem is formulated in a probabilistic optimal power flow (P-OPF) framework, accounting for uncertainties on both IL response and wind power forecasts. To address this problem, we develop a probabilistic collocation method (PCM) combining techniques of sparse grids and correlation control, which enables efficient and accurate propagation of correlated uncertain variables with relatively low computational cost. The effectiveness of the proposed model and computational strategy are demonstrated on the modified IEEE RTS 24-bus test case and a simplified regional Jiangsu power grid, where the impacts of IL pricing and capacity on the re-dispatch results are further explored.