Multi-time interval forecasting-aided state estimation incorporating phasor measurements for power systems with renewable energy sources

To achieve more precise monitoring for state fluctuations in the power network close to renewable energy sources, it is necessary to utilize phasor measurements and shorten the time interval between state estimations. For large scale power systems, however, estimating all of their states with shorter time interval means a drastic increase in computational burden. As a tradeoff between accuracy and computational efficiency, a multi-time interval forecasting-aided state estimation approach is proposed in this paper, where states with various degrees of fluctuations are estimated asynchronously with different time intervals. Based on the newest state estimate, forecasting-aided state estimators are employed to predict states at time moments prior to the next round of measurement update and state estimation. Extensive numerical tests have demonstrated the effectiveness of the proposed approach.