DocumentCode :
3508990
Title :
Application of artificial neural networks in adaptive interlocking systems
Author :
Agarwa, S.H. ; Prabhu, V.N.
Author_Institution :
Testing Dept., Tata Electr. Co., Bombay, India
fYear :
1993
fDate :
1993
Firstpage :
453
Lastpage :
458
Abstract :
Interlocks have been in use ever since protective relaying schemes were implemented for power devices like generators, transformers, transmission lines, etc. Although the science of protective relaying has undergone marked changes and improvements, the interlocking philosophy has not changed much. Recently with the availability of programmable logic controllers (PLCs), interlocking schemes have been implemented by means of these devices with basic philosophy of logic remaining the same. This paper suggests the implementation of interlocking schemes with artificial neural networks employing threshold logic unit (TLU) elements. It is demonstrated that while the basic hardware required is same as that of any common PLC, the suggested system will have added flexibility, adaptability to various switchyard modifications, electrical topology changes and equipment/switchyard conditions as well as network complexity.
Keywords :
adaptive control; neural nets; power system computer control; power system protection; programmable controllers; PLCs; adaptive control; artificial neural networks; generators; hardware; interlocking; power system protection; programmable logic controllers; relay protection; switchyard; threshold logic unit; transformers; transmission lines; Adaptive systems; Artificial neural networks; Availability; Logic devices; Power generation; Power transmission lines; Programmable control; Programmable logic arrays; Protective relaying; Transformers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks to Power Systems, 1993. ANNPS '93., Proceedings of the Second International Forum on Applications of
Conference_Location :
Yokohama, Japan
Print_ISBN :
0-7803-1217-1
Type :
conf
DOI :
10.1109/ANN.1993.264306
Filename :
264306
Link To Document :
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