Effective Angle Prediction Algorithm for Utilization of PMU Data: Toward Prevention of Wide Area Blackouts

Published via IEEE Xplore

Abstract

Advanced state estimation and angle prediction algorithms utilizing the data measured by Phasor Measurement Units (PMU) can limit the spread of wide area blackouts. Advanced prediction analysis provides information on the overall condition of the power system and allows for the most efficient remedial actions and prevention schemes. This paper proposes and implements a very fast, online and real time bus angle prediction algorithm which provides indication on the impending instability of the power system following any severe system disturbance. The work utilizes the combination of Kalman filter and Taylor series method to come up with a very fast and accurate angle estimation and prediction algorithm which can prevent a power system from reaching an unstable condition and therefore, help avoid wide area blackouts due to cascading effects. The effectiveness of the proposed algorithm is demonstrated via dynamic simulations on a modified IEEE 39-bus New England system model and a real-world bulk power system model with more than 60,000 buses.

EnerNex Contributing Authors


Read Sarina’s blog on Proper Utilization of PMU Data: Towards Prevention of Wide Area Blackouts

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