Open AccessMulti‐agent‐based dynamic state estimator for multi‐area power system
Author(s) -
Sharma Ankush,
Srivastava Suresh Chandra,
Chakrabarti Saikat
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.2015.0504
Subject(s) - kalman filter , phasor , computer science , electric power system , smart grid , extended kalman filter , state (computer science) , real time computing , units of measurement , estimator , phasor measurement unit , software , grid , field (mathematics) , power (physics) , engineering , algorithm , statistics , physics , mathematics , quantum mechanics , artificial intelligence , geometry , pure mathematics , electrical engineering , programming language
The smart grid implementation requires real time monitoring and visualisation of the power system networks. This study presents a multi‐agent‐based multi‐area power system dynamic state estimator (MPDSE), suitable for the network that can be divided into sub‐areas. In this approach, the sub‐areas run MPDSE using field measurements from the remote terminal units (RTUs), as well as from the phasor measurement units (PMUs). The MPDSE is executed for the sub‐areas independently and in parallel to save the overall execution time. Software agents are utilised to exchange the information and run the MPDSE for the RTU and the PMU measurements separately, and, then, integrate their results to estimate the final states of a sub‐area. The central coordinator consolidates the state estimates of all the sub‐areas. The MPDSE is solved by using three approaches based on extended Kalman filter (), unscented Kalman filter, and cubature Kalman filter, and their relative performances are obtained with the help of the simulation results on two test systems.