Placement of large‐scale utility‐owned wind distributed generation based on probabilistic forecasting of line congestion

Abstract

Integration of large-scale utility-owned distributed generation (DG) units can be a vital technique in relieving transmission line congestion and improving the reliability of the power grid. However, the impact of DG installation on line congestion management is significant at locations where transmission lines are most heavily loaded. This study presents a novel probabilistic method to forecast the most heavily loaded lines in the transmission network that might be at a higher risk of congestion. The proposed method can be utilised for determining candidate lines to install DG with the objective of relieving line congestion. The proposed method adopts the cumulative probability distribution function that accounts for the uncertainty of line loading. Furthermore, a congestion improvement ratio is developed to investigate the DG location impact on line congestion. The forecasting method is tested on a small modified IEEE 5-Bus system. In order to demonstrate the proposed forecasting method on a larger and more complex system with several generators, the method is also tested on IEEE 30-Bus test system. The simulation results have confirmed the effectiveness of the proposed method.