Open AccessParallel relaxation‐based joint dynamic state estimation of large‐scale power systems
Author(s) -
Karimipour Hadis,
Dinavahi Venkata
Publication year - 2016
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2015.0808
Subject(s) - computer science , scalability , electric power system , phasor , scale (ratio) , thread (computing) , state (computer science) , generator (circuit theory) , relaxation (psychology) , parallel computing , algorithm , power (physics) , psychology , social psychology , physics , quantum mechanics , database , operating system
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.