This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Massive amounts of data generated in large-scale grids poses a formidable challenge for real-time monitoring of power systems. Dynamic state estimation which is a prerequisite for normal operation of power systems involves the time-constrained solution of a large set of equations which requires significant computational resources. In this study, an efficient and accurate relaxation-based parallel processing technique is proposed in the presence of phasor measurement units. A combination of different types of parallelism is used on both single and multiple graphic processing units to accelerate large-scale joint dynamic state estimation simulation. The estimation results for both generator and network states verify that proper massive-thread parallel programming makes the entire implementation scalable and efficient with high accuracy.
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