Sundararajan G
@jjjcet.ac.in
Assistant Professor/ Department of EEE
JJ COLLEGE OF ENGINEERING AND TECHNOLOGY
EDUCATION
B.E,M.Tech
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Energy Engineering and Power Technology, Renewable Energy, Sustainability and the Environment
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
P. RathiDevi, P. Sivakumar, P. Thirusenthil Kumaran, G. Sundararajan, and D. Jenita
IEEE
In many industrial and scientific applications, induction heaters are widely used to heat magnetic materials, especially when precise, controlled heating is needed. Compared to other heating methods, induction heating has advantages including noncontact heating, high efficiency, surface hardening, clean heating, and more. Hard switching inverter circuits are used in power circuit layouts for induction heating systems in a variety of applications, which increases inverter bridge losses, particularly in high current, high frequency switching applications. Soft switching type induction heaters have the advantages of minimal switching power loss and high frequency operation, which make them suitable for usage in a range of process applications. The implementation and simulation of an induction heater are covered in this research. In this model, a single phase, half bridge, series resonant inverter generates high frequency current. The driver circuit for a single phase half bridge series resonant inverter is controlled by a microcontroller unit.The current passing through the load controls the duty cycle of the gate pulses provided to the switching device's gate. Haul To keep an eye on the current passing through the load, sensors are employed. The microcontroller unit generates the gate pulses required by the switching devices. A PIC16F877A microcontroller is employed. By changing the PWM gate pulse's duty cycle, which is produced by the PIC16F877A microcontroller, the amount of power sent to the load can be adjusted. The power used by the load is managed by the induction heater's closed loop control.
Sivakumar P, Rathi Devi P, Sundararajan G, Sureshraj Se Pa, Nalini D, and Mohamed Badcha Y
IEEE
In general, electric motors that use the energy from the batteries are combined with IC engines to power hybrid electric vehicles. In this study, a pure hybrid electric car with no emissions is explored. Solar PV is coupled with electric motors and energy storage components. Solar energy, which is ubiquitous and abundant in nature, can be a fantastic replacement for traditional resources. The use of this technology will lessen the environmental pollution. Three parameters, including load demand, battery SOC, and solar power, are taken into account while allocating electricity.
G. Sundararajan and P. Sivakumar
Hindawi Limited
Due to the unpredictable and stochastic nature of renewables, current power networks confront operational issues as renewable energy sources are more widely used. Frequency stability of modern power systems has been considerably harmed by fast and unpredictable power variations generated by intermittent power generation sources and flexible loads. The main objective of the power system frequency control is to ensure the generation demand balance at all times. In reality, obtaining precise estimates of the imbalance of power in both transmission and distribution systems is challenging, especially when renewable energy penetration is high. Electric vehicles have become a viable tool to reduce the occasional impact of renewable energy sources engaged in frequency regulation mainly because of vehicle-to-grid technologies and the quick output power management of EV batteries. The rapid response of EVs enhances the effectiveness of the LFC system significantly. This research work investigates a deep learning strategy based on a long short-term memory recurrent neural network to identify active power fluctuations in real-time. The new approach assesses power fluctuations from a real-time observed frequency signal precisely and quickly. The observed power fluctuations can be used as a control reference, allowing automatic generation control to maintain better system frequency and ensure optimum generation cost with the use of demand management techniques. To validate the suggested method and compare it with several classical methods, a realistic model of the Indian power system integrated with distributed generation technology is used. The simulation results clearly indicate the importance of power fluctuation identification as well as the benefits of the proposed strategy. The results clearly show a considerable improvement in response performance indices, as the maximum peak overshoot was decreased by 21.25% to 51.2%, and settling time was lowered by about 23.34% to 65.40% for the suggested control technique compared to other controllers.
A. Vivekanandhan, P. Rathi Devi, P. Sivakumar, S. Vijayalakshmi, G. Sundararajan, P. John Britto, and S. Karthikeyan
IEEE
Diminishing era of conventional non-renewable energy sources set up the path for the research and expansion of renewable energy sources (RES) continues with the development of the microgrid and its controls. Microgrids are supplied from the RES through some power converters which leads to the necessity of a controller to suppress the power quality issues due to their nonlinearity properties. In this paper, the controlling techniques employed and analyzed for microgrid application were briefly overviewed and discussed.
S. Sivakumar, M. Jagabar Sathik, P.S. Manoj, and G. Sundararajan
Elsevier BV