Estimation of Transmission Line Overload due to Forecasting Error of Renewable Energy Sources

As the installed capacity of renewable energy sources (RESs) increases in power systems, unexpected thermal overload of transmission lines can occur because it is difficult to forecast the outputs of the RESs accurately. To cope with unexpected thermal overload, it is essential to grasp patterns of thermal overload caused by forecasting errors and secure the spinning reserve considering the position of operating generators in the transmission network. In this paper, we develop a Particle Swarm optimization-based method to estimate possible thermal overload caused by the forecasting errors. The effectiveness of the proposed method is verified by numerical simulation for the modified IEEE-RTS 24-bus system. The results show the importance of considering the position of generators in the transmission network in securing the spinning reserve for thermal overload of the transmission lines.