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access icon free Unscented Rauch–Tung–Streibel smoother-based power system forecasting-aided state estimator using hybrid measurements

© The Institution of Engineering and Technology
Received 28/10/2018, Accepted 19/06/2019, Revised 10/05/2019, Published 26/06/2019

A hybrid estimator to track the power system states considering fast-rate PMUs and slow-rate supervisory control and data acquisition (SCADA) system is proposed in this article. SCADA measurements arrive at the control centre with various time delays. The estimates obtained using these delayed measurements significantly differs from the actual power system states and is known as the time skew problem. The missing SCADA measurements, owing to their time skewness, are replaced by their predicted values which lead to reduced estimation accuracy. Optimal smoothing algorithms can be utilised to include dynamics in the future measurements to reduce the errors introduced by the time skew problem. Unscented Rauch–Tung–Streibel smoother is used in this study to handle the time skew problem. The performance of the proposed techniques in handling anomalous situations is also studied. The proposed estimator is validated under real-time environment using RTDS, a real-time simulation tool, to assess its applicability in the control centre.

Inspec keywords: SCADA systems; power system measurement; state estimation; Kalman filters; power system state estimation; smoothing methods; data acquisition

Other keywords: time delays; slow-rate supervisory control; future measurements; hybrid measurements; hybrid estimator; time skewness; fast-rate PMUs; real-time simulation tool; reduced estimation accuracy; unscented Rauch–Tung–Streibel smoother-based power system forecasting; real-time environment; delayed measurements; time skew problem; actual power system states; control centre; missing SCADA measurements

Subjects: Power system measurement and metering; Other topics in statistics; Other topics in statistics

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