Silas Stephen D
@panimalar.ac.in
Professor
Panimalar Engineering College
RESEARCH INTERESTS
Power System Engineering, Power System Optimization, Micro-Grid, Electric Vehicle Technology, Renewable Energy
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Omar A. AlKawak, Jambi Ratna Raja Kumar, Silas Stephen Daniel, and Chinthalacheruvu Venkata Krishna Reddy
Elsevier BV
D. Silas Stephen, T. Muthamizhan, and Jinu Sophia J
Springer Nature Singapore
T. Muthamizhan, D. Silas Stephen, and A. Sivakumar
IOS Press
The paper aims to define the speed control of Brushless DC Motor (BLDC) drive using an Adaptive Neuro Fuzzy Interface System (ANFIS) controller. ANFIS controller-based switching scheme reduces the power quality issues present in the system by minimizing the Total Harmonic Distortion (THD). Incremental conductance algorithm-based control technique for the Maximum Power Point Tracking (MPPT) in variable solar irradiation conditions for photovoltaic (PV) system is proposed. INC algorithm are used to operate the photovoltaic panels at maximum power, by generating PWM pulse to control the flyback converters in differential power processing mode. BLDC motor drive is electronically commutated by means of switching logical pulses from the rotor position sensor using PI controllers. The simulation shows the significance and robustness of BLDC drive and the results offered illustrates the intended control is effective, with fast responseandminimum settling times.
C. Kothai Andal, R. Jayapal, and D. Silas Stephen
Lecture Notes on Data Engineering and Communications Technologies Springer International Publishing
D. Silas Stephen and P. Somasundaram
Springer Science and Business Media LLC
D Silas Stephen, , P Somasundaram, and
School of Electrical Engineering and Informatics (STEI) ITB
Fuzzy based stochastic algorithms for solving Multi-objective Reactive Power Optimization (MORPO) problem including FACTS devices is presented in this paper. The Multi-Objective Reactive Power Optimization problem is formulated as a nonlinear constrained multi-objective optimization problem where the active power, voltage deviation and investment cost has to be minimized simultaneously. Fuzzy logic strategy incorporated with Evolutionary Programming (EP), Tabu search (TS) algorithms and Particle Swarm Optimization (PSO) has been proposed to handle the problem as a true multi-objective problem. The proposed algorithm has been used to solve the MORP problem with and without FACTS devices namely STATCOM, TCSC and UPFC.IEEE 30-bus system is used as a test system. The simulation results are promising and show the effectiveness and robustness of the proposed approach.