Om Malik

Faculty Professor

Key words:

Control systems, Fuzzy Logic, Intelligent systems, Protection

Unlisted key words: Power System Stabilizers, Adaptive Control, Neural Network Applications in Power Systems

Research description:

Development of adaptive, fuzzy logic and neural network based power system stsbilizers with particular emphasis on implementation and experimental real time assessment of these devices in actual power systems. A number of new techniques have been developed that provide on-line tuning in real time requiring almost nil on-line effort during commissioning. The validy of such algorithms has been demonstrated not only by experimental studies on physical models in the laboratory but also in real power systems. Novel algorithms for protection of high voltage transmission lines using conventional approaches and neural networks have been developed and verified by experimental tests on a physical model and on data collected from actual faults on transmission lines. Work has also been done on the development of models for the simulation of both symmetrical and unsymmetrical internal faults in the stator winding of a synchronous machine.

Laboratory facilities:

Tha laboratory setup consists of a physical model of a single machine connected to a constant voltage bus through a double circuit transmission line. The synchronous machine is a specially designed 3kVA micromachine connected to the contant voltage bus through lines that can model 500kV lines upto 300 km in sections of 50km. the synchronous machine has a time constant regulator by which its time constant can be adjusted between 0.8s and 9.0s. Other equipment includes computers, DSP, and measuring devices for real time on-line control and protection work.

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