Open AccessReal‐time estimation of ATC using PMU data and ANN
Author(s) -
Shukla Devesh,
Singh S.P.
Publication year - 2020
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.2019.1260
Subject(s) - phasor measurement unit , emulation , artificial neural network , phasor , computer science , electric power system , set (abstract data type) , real time computing , units of measurement , engineering , power (physics) , data mining , artificial intelligence , physics , quantum mechanics , economics , programming language , economic growth
An artificial neural network (ANN) architecture for real‐time estimation of available transfer capability (ATC) has been reported in this study. The real‐time data obtained from phasor measurement unit (PMU) is utilised to generate target output (ATC) using the pattern search optimisation‐based method. The set of information provided as input to the pattern search‐based ATC optimiser along with its output forms the input and target output for ANN training. The input information consists of active and reactive power injected along with voltage and current vectors measured at PMU buses. The ATC optimiser is functional as long as ANN is under training. Once the ANN is trained, it receives input set directly from PMU and produces ATC values. PMU emulation is employed for archiving the PMU data. The proposed method is tested on modified IEEE 24‐bus, IEEE 30‐bus, and IEEE 118‐bus test system. The proposed method has also been implemented on real‐time digital simulator.