Probabilistic Real-Time Dynamic Line Rating Forecasting Based on Dynamic Stochastic General Equilibrium With Stochastic Volatility

Real-time dynamic line rating forecasting can be classified into two critical steps of evaluating the operation risk, and avoiding the overload operation of transmission lines. The dynamic capacity of the transmission line is generally predicted for scheduling power networks in the day-ahead market. However, the forecasting error motivates researchers to propose real-time forecasting models to correct the day-ahead scheduling results based on the accurate data close to real-time values in the balancing market. Among the methods presented for real-time dynamic line rating forecasting, the single-point estimation type has been considered more than other forecasting types. Despite its safety, and efficiency, a single point estimation type suffers from several significant drawbacks. For instance, this forecasting type cannot indicate the probabilistic distribution function of forecasted value, which is used in novel balancing methods of market scheduling. The main purpose of this paper is to present a density forecast method to predict real-time dynamic line rating for covering the balancing market requirements. Dynamic stochastic general equilibrium (DSGE) is applied to achieve this aim. Due to incorporating stochastic volatility in the proposed real-time forecasting model, evaluating simulation results, and reference models highlight a significant improvement in the performance of the real-time density forecast of DLR.