RAVI PRAKASH MAHOBIA
@kalingauniversity.ac.in
ASSISTENT PROFESSOR, ELECTRICAL DEPARTMENT
KALINGA UNIVERSITY, RAIPUR
EDUCATION
BE (EEE)
M.TECH(PSE)
RESEARCH INTERESTS
POWER SYSTEM STABILITY, POWER QUALITY, GREEN ENERGY
Scopus Publications
Scholar Citations
Scholar h-index
Scopus Publications
Ravi Prakash Mahobia
EDP Sciences
The problem of vehicle span maximization and path switchinghas been well studied. There exists number of approaches towards maximizing the span of electric vehicles. However, the methods suffer to achieve higher performance in maximizing the span of the vehicle. Towards this, an efficient Location centric power factor path switching model (LPPSM) is presented in this article. As the electric vehicles has the limited span which is being affected by various factors like speed, wind, traffic, number of junctions, distance and so on. It is necessary to perform path switching towards maximizing the span of the vehicle. The model fetches the location of the vehicle at all the time; it finds the routes and measures the traffic at each route. According to the factors like number of junctions, traffic, distance, speed of the vehicle, the method estimates the Span Maximization Support (SMS) for various routes. According to the value of SMS, the method selects the most optimal route to reach the destination. Also, the method focused on maximizing the span of the vehicle and performs efficient path switching. The proposed method improves the performance of span maximization and path switching.
Shailesh Madhavrao Deshmukh and Ravi Prakash Mahobia
EDP Sciences
The power stabilization in photovoltaic systems is well studied. There exist number of approaches in stabilizing the output power of PV systems. The most approaches concern about the input power and residual energy of capacitors. Still they suffer to achieve higher performance in power stabilization. To handle this issue, an efficient Fuzzy inference based Power stabilization model (FIPSM) is presented in this paper. The model is focused on utilizing residual energy on different circuits and avoiding higher drain of energy on any of the circuit. The model fabricated with MOFSET device in each circuit which monitors the input and output voltage of any circuit. As the model has number of circuits framed in serial connection, the method generates fuzzy rules based on the conditions of different circuits for different input voltage with output voltage required. At each duty cycle, the method reads the input voltage and identifies set of circuits were in sleep or charging mode. With the list of circuits, the method computes the Fuzzy Inference Voltage Stabilization Support (FIVSS) for various circuits. Based on the value of FIVSS, the method identifies a unique or a subset of circuits to support stabilization. The proposed model improves the performance of power stabilization in photovoltaic systems.
Ravi Prakash Mahobia, Shimpy Ralhan, Mahesh Singh, and Ritu Sharma
Springer Singapore
Ritu Sharma, Naveen Goel, Saji Chacko, and Ravi Prakash Mahobia
Springer Singapore
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