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
S Anbuchandran, M Arumuga Babu, D Silas Stephen, and M Thinakaran
IOP Publishing
Abstract This study explores innovative control strategies for electric vehicle (EV) charging stations in a DC Microgrid powered by solar and wind energy. A new methodology regulates the dc-link voltage through various converters while a modified vector control method enhances the performance of switched reluctance motors (SRMs). The implementation of super twisting sliding mode (STSM) controllers show superior performance compared to traditional PI and Fuzzy controllers. The design of an asymmetrical converter with four battery banks also minimizes charging durations. The real-time test system (RTS) effectively managed power generation within a DC microgrid, demonstrating a stable voltage at the DC bus despite variations in total generation from photovoltaic (PVS) and wind systems. In Case 1, the controller successfully maintained power balance while charging electric vehicles and managing DC loads. During load torque adjustments, the system maintained a steady motor speed of 320 RPM even with a load torque increase from 5 Nm to 50 Nm at 3 s, showcasing its robust vector control strategy. Notably, the system facilitated a reverse operation at 10 km h−1 (80 RPM) by seamlessly adjusting the engine’s reference speed from 80 RPM to −80 RPM at t = 4.0 s. The vector control causes the engine speed heading to be opposite in a natural manner., indicating its innovative capability to handle diverse operational scenarios. The MATLAB/Simulink package serves as the foundation for the proposed model, which is then integrated into OPAL-RT modules to create a Hardware-in-the-Loop (HIL) system for showcasing diverse outcomes. Different outcomes are deliberated with validated justifications of the suggested approach. The research is linked to Sustainable Development Goals 7 (Affordable and clean energy) and 13 (Climate action).
S. Anbuchandran, D. Silas Stephen, M. Arumuga Babu, and A. Bhuvanesh
Elsevier BV
Anbuchandran S, Arumuga Babu M, Silas Stephen D, and Thinakaran M
IOP Publishing
Abstract The deregulation of the power system, upward growth in electrical energy demand and network expansion have resulted in an increasing integration of distributed generation (DG) and distribution static synchronous compensator (D-STATCOM) into radial distribution systems (RDS). Nonetheless, the optimal allocation of these devices is highly important to derive immense benefits. This investigation narrows down on optimizing DG and D-STATCOM placement in IEEE 33-bus RDS with a view to increase bus voltages, decrease power losses as well as maximize economic gains. The study undertakes a comprehensive analysis comparing the technical, economic and environmental performance of DG and D-STATCOM; thereby enabling power engineers to make informed choices concerning which device will be most advantageous when it comes to delivering power in RDS. A fuzzy enhanced firefly optimization (FEFO) approach is proposed for the optimization and a multifaceted evaluation in terms of technical, financial and environmental is presented for effective decision-making on distributed energy resource deployment. D-STATCOM and wind DG integrations led to notable reductions in power loss and pollutant emissions, highlighting their effectiveness in improving power quality and reducing reliance on fossil fuels. While wind DG incurred a higher installation cost ($3,100,749.2) compared to D-STATCOM ($90,566.6), it achieved greater yearly power loss cost savings ($69,198 versus $47,619). FEFO’s efficiency in optimization stands out, aiding engineers in making informed decisions for optimizing D-STATCOM and wind-DG integration in the IEEE-33 RDS, ultimately enhancing system performance and cost-effectiveness through proactive planning. The integration of D-STATCOM and wind DG led to a significant improvement in distribution system efficiency, with D-STATCOM reducing real power loss by 28.7% and reactive power loss by 27.8%, while wind DG achieved greater reductions of 41.8% in real power loss and 37.5% in reactive power loss, alongside reductions in pollutant emissions of 1.5% and 2.2%, respectively.
Omar A. AlKawak, Jambi Ratna Raja Kumar, Silas Stephen Daniel, and Chinthalacheruvu Venkata Krishna Reddy
Elsevier BV
Bansilal Bairwa, Kiranmayee Jampala, J P Sridhar, and D Silas Stephen
IEEE
The survey delf into the intricate dynamics of battery behavior nether change temperature conditions, use angstrom comprehensive examination 2RC equivalent circuit battery model. by analyze the relationship between temperature, state of charge (SOC), and voltage feature, the research shed light on the fundamental factor influence battery performance. This probe not lone light the impact of temperature on electrochemical chemical reaction inside the battery merely besides underscore the necessity for effective thermal management scheme to optimize performance and prolong battery life. furthermore, the survey research the deduction of temperature variation on battery thermal profile, identify potential hot spot and hazard that May compromise functionality and safety. The findings supply valuable penetration for engineer and research worker to develop advance thermal management system and compensation algorithm, thereby enhance the dependability and efficiency of battery system, particularly inch demand urban transportation system environment.
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.