Open AccessDevelopment of a quasi‐real‐time distribution voltage monitoring system
Author(s) -
Sarkar Subhra J.,
Sahoo Sarat Kumar,
Kundu Palash K.,
Pattanayak Rutuparna
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.2020.0616
Subject(s) - encryption , computer science , ascii , microcontroller , compressed sensing , data compression , key (lock) , computer hardware , algorithm , data security , encoding (memory) , computer network , artificial intelligence , computer security , operating system
Data compression has its own importance in numerous applications, including power systems and several algorithms were developed for managing data associated with the power system. As security is a matter of concern in transferring the compressed information through any communication channel, data encryption can ensure data security. A low computational, microcontroller implementable, asymmetric key encryption algorithm similar to Rivest–Shamir–Adleman algorithm is proposed here for encrypting any ASCII character. As combined differential binary encoding algorithm (C‐DBEA) can handle almost all practical data sets and can achieve a moderately high compression ratio (CR), an attempt was made to ensure the security of the compressed data by developing the low computational compressed, encrypted algorithm. A data array is compressed by using C‐DBEA in this compressed, encrypted algorithm and is encrypted by using the proposed encryption algorithm. After successful PC‐based testing, the algorithm is implemented successfully at the microcontroller level as well. Finally, the compressed, encrypted Data Acquisition System is realised for measuring distribution voltage where compressed, encrypted data transfer occurs between two microcontrollers. High CR is obtained for the less fluctuating voltage profile data of urban areas where the volume of data reduces by >95%.