Dynamic state estimation based on unscented Kalman filter and very short-term load and distributed generation forecasting

Distribution system state estimation-A step towards smart grid

“…Since DNs lack real-time measurements, network observability is achieved using pseudo measurements, which are generated using historical load forecasting. In this regard, the authors in [85], propose a UKF-based dynamic estimator, which utilizes short-term load and DG forecasting for generating pseudo measurements. This algorithm was validated using a 123-bus DN to demonstrate its effectiveness.…”

Neural network-based power system dynamic state estimation using hybrid data from SCADA and phasor measurement units

“…The superiority of the UKF under normal noisy conditions is also addressed by researchers in Valverde and Terzija . Besides applying UKF, nodal power injections from both load points and DG units are projected and transformed into state predictions through load flow computation as an approach to derive state transition model . To enhance the numerical stability of the UKF used for power system DSE, a new UKF method with guaranteed positive semidefinite error covariance matrix is proposed and compared with some existing similar approaches in Qi et al A hybrid method is proposed by Risso et al, with the aim of taking advantages of both WLS and UKF simultaneously.…”

“…20 Besides applying UKF, nodal power injections from both load points and DG units are projected and transformed into state predictions through load flow computation as an approach to derive state transition model. 21 To enhance the numerical stability of the UKF used for power system DSE, a new UKF method with guaranteed positive semidefinite error covariance matrix is proposed and compared with some existing similar approaches in Qi et al 22 A hybrid method is proposed by Risso et al, 23 with the aim of taking advantages of both WLS and UKF simultaneously. A GPU-based 2-level dynamic state estimator is proposed in Karimipour and Dinavahi 24 that is based on the EKF utilizing both SCADA and PMU measurements.…”

Event‐triggered distributed dynamic state estimation with imperfect measurements over a finite horizon

“…As a fundamental infrastructure, power systems play an increasingly important role in modern society. Their stable operation is tied so closely to daily life and industrial production that significant attention has been focused on the monitoring and control of power systems in the past few years [1][2][3][4][5][6][7][8][9]. To realise this goal, a supervisor control and data acquisition (SCADA) system, which is composed of software called an energy management system (EMS), is widely applied in power systems.…”

“…FASE was originated [4] by Debs and Larson, whose work since then has inspired real interest in FASE for power systems. A series of important results were achieved in [5][6][7][8][9]. However, there're several problems that persist with FASE, such as establishing an accurate model and efficient estimation algorithm.…”