Dr Asit Mohanty
@miet.edu.in
Professor,Electrical Engineering
Professor,MIET Bhubaneswar
RESEARCH, TEACHING, or OTHER INTERESTS
Energy, Renewable Energy, Sustainability and the Environment, Electrical and Electronic Engineering, Ocean Engineering
Scopus Publications
Scopus Publications
Abhay Sanatan Satapathy, Sthitapragyan Mohanty, Asit Mohanty, Reji Kumar Rajamony, Manzoore Elahi M Soudagar, T.M. Yunus Khan, MA Kalam, Muhammad Mahmood Ali, and Muhammad Nasir Bashir
Elsevier BV
Abhay Sanatan Satapathy, Asit Mohanty, Prakash K. Ray, Javed Khan Bhutto, Ahmad Jaber Mohammad Alfiafi, and Omar Khulaif Alharbi
Institute of Electrical and Electronics Engineers (IEEE)
This article addresses the optimality and stability issues of a Tidal power based hybrid power system (HPS). The Tidal system gets destabilized by the uncertain variation of tidal waves and wind input. Stability of the system is restored through the introduction of Unified Power Flow Controller (UPFC) controller. The controller is optimized through the process of configuration of Hyper Spherical Search (HSS) based algorithm. The evaluation of the effectiveness of the suggested controllers is conducted through comparison analyses in order to regulate the voltage profile of the interconnected power network under various loading scenarios. The efficacy of the suggested controllers is assessed by stability analysis utilizing Eigen and Nyquist plots. Further, it is quite evident that optimal tuning is possible in case of the controller where the parameters can create significant impact on the system performance. Consequently, a novel heuristic optimization technique, such as HSS Algorithm are suggested to find the best output of the proposed controller. Finally, by using real-data, the performance as well as robustness of the suggested controller have examined by utilizing a real-time digital simulation platform, specifically the OPAL-RT 5142.
Prakash K Ray, Harish Kumar Sahoo, Asit Mohanty, Javed khan Bhutto, Abdulwasa Bakr Abbas Barnawi, and Abdulmjeed Ali Alshaya
Institute of Electrical and Electronics Engineers (IEEE)
Dillip K. Mishra, Asit Mohanty, and Prakash K. Ray
Springer Science and Business Media LLC
Pratik Kar, Durgesh Prasad Bagarty, Prakash Kumar Ray, and Asit Mohanty
IEEE
The paper deals with the design of an asymmetric multilevel inverter producing maximum level with optimal number of circuit components. The objective of this paper is to design a multilevel inverter keeping all necessary points of interest like overall robustness, lower harmonic distortion, reduced voltage stress, efficiency and simplicity of the circuit. The proposed circuit is designed to generate 15 levels of voltage. A transformer at output is used to boost voltage with a half bridge circuit at secondary terminal for polarity reversal. Pulses are generated for the proposed configuration using Nearest Level Control technique. The proposed inverter is compared with other recent topologies based on various factors such as number of components, voltage stress, overall performance, etc. Its extension for producing higher levels is also described. The simulation with result verification is carried out to validate the proposed circuit.
Pratik Kar, Durgesh Prasad Bagarty, Prakash Kumar Ray, and Asit Mohanty
IEEE
This paper proposes a unique reduced component sensor-based topology of capacitor-switched multilevel inverter (CSMLI) which is compatible for low, medium and high voltage application. In this configuration only one voltage source is required. The proposed circuit is a seven-level inverter that uses least number of switches with only one capacitor and one voltage source. Special attention is given to charging of capacitor, eliminating any kind of voltage imbalance or abrupt change in voltage across capacitor with minimum inrush charging current. The design of the circuit is accomplished to have minimum voltage stress across various circuit elements. The operational principle of this inverter and some known modulation strategies are used to evaluate the overall circuit performance. The proposed work is compared with other work of similar type with regards to device count and performance. The simulation with result verification is carried out to validate the proposed circuit.
Rachita R. Sarangi, Abhijeet Pradhan, Janmajay Moharana, Prakash K. Ray, and Asit Mohanty
IEEE
The frequency variation is detected in a microgrid consisting of wind turbine, solar thermal, fuel cell, diesel generator along with storage devices like battery and flywheels. The frequency changes abruptly because of sudden and stochastic changes in load, solar and wind turbine outputs. The rate of change of frequency (ROCOF) is detected using a relay which is tested both in simulation as well as real-time hardware set up using NVIDIA JETSON NANO and NI DAQ. It is analyzed that the proposed technique detects the change in frequency effectively and generates the required trip signal for the circuit breaker for improvements in the protection strategy in microgrid under various operating scenarios.
Rachita R. Sarangi, Prakash K. Ray, Krishna Kabita Srichandanray, Lalbahadur Majhi, and Asit Mohanty
IEEE
DER (Distributed energy resources) are integrated in to the power system with help of advanced power electronic converters which help to maintain the system stability and integrity in event of a fault through the implementation of robust control techniques and advanced communication technology. In order to build a sustainable and reliable system with DERs being integrated, now a days advanced signal processing based fault diagnostic technologies have been developed in order to assist the existing converter based technology. Usually these time frequency based analysis techniques are being employed to enhance the existing passive methods in wake of a source based un certainty. The current work analyzes the effectiveness of an existing signal processing method which is EMD (Empirical mode of decomposition) in order to extract the relevant quantities to identify and segregate the various fault types and their characteristics. Further the use of advanced machine learning techniques can help to classify them in to different fault types.
Shanti S. Rath, Satyavarta Kumar Prince, Prakash K. Ray, Asit Mohanty, and Gayadhar Panda
IEEE
Within the intricate power infrastructure of microgrids, characterized by diverse energy sources like PV solar panels, intricate loads, and sophisticated control systems, the operational complexity amplifies, especially during contingency scenarios, demanding a meticulous relay coordination study. Particularly prevalent in rural or remote locations, these microgrids demand a safeguarding protection coordination system that swiftly and reliably detects and responds to faults, ensuring a secure and dependable power supply. This study presents a novel two-stage fault detection solution tailored for Distributed Energy Resource systems, leveraging the Empirical Mode Decomposition technique. In this methodology, fault detection and classification unfold across two stages, as the Empirical Mode Decomposition precisely decomposes the current signal into a suite of Intrinsic Mode Functions. Subsequent analysis of these Intrinsic Mode Functions enables the identification of fault signatures and their respective types. Rigorously evaluated using a Modified ETAP model, the proposed approach exhibits significant effectiveness in both fault detection and classification, as underscored by comprehensive simulation results. The application of this approach in ETAP further solidifies its efficacy in fortifying the system against potential damages arising from faults. This technical paper delves into the application of the Empirical Mode Decomposition method to signal processing, offering a versatile solution with diverse applications in smart grid scenarios.
Rachita R. Sarangi, Prakash K. Ray, and Asit Mohanty
IEEE
Renewable energy sources are intermittent and unpredictable in nature, integrating them into power networks pose challenges in segregation and categorization of faults that happen from that of a transient change which might be due machine starting or transformer inrush etc. The present research suggests using sophisticated signal processing methods for the precise and effective identification and categorization of disturbances in renewable energy integrated power systems. Electrical signals from monitoring equipment have been analyzed in this work in order to extract relevant qualities that capture the characteristics of various failure types. These properties are then applied to fault classification using machine learning and pattern recognition methods, such as neural networks and support vector machines. The proposed technique uses MA(Moving average filter) and HHT (Hilbert-Huang Transform) to effectively segregate a power system transient from an internal fault and classify them in to various fault types.
Rachita R. Sarangi, Prakash K. Ray, Ajit K. Barisal, and Asit Mohanty
IEEE
With the penetration of DERs (Distributed Energy Resources), conventional transmission and distribution systems are getting increasingly replaced with converter based topologies along with localized transfer of power to loads. These are extremely dynamic systems, exposed to numerous intermittent sources of energy such as solar power, wind energy etc. The converters which interface the power generation sources with the load have to tightly maintain the bus voltage in order to maintain supply reliability and power quality. They also need to be resilient enough when faced with faults and disturbances in the system. However, these power converters which consist mostly of power electronic components which have very high switching frequencies, when faced with an unprecedented condition might give in to failures due to their low tolerance to very high currents that might cause damage to these components. These kinds of faults need to be accurately detected and isolated within time then to create a smart, reliable, energy efficient power system.
Rachita R. Sarangi, Asit Mohanty, Prakash K. Ray, Ajit K. Barisal, and Suvendu M. Baral
Springer Nature Singapore
Lipsa Pani, Abhimanyu Mohapatra, Prakash K. Ray, and Asit Mohanty
Springer Nature Singapore
Dillip Kumar Mishra, Prakash Kumar Ray, Asit Mohanty, and Tapas Kumar Panigrahi
Elsevier
Dillip Kumar Mishra, Asit Mohanty, Prakash Kumar Ray, and Tapas Kumar Panigrahi
Elsevier
Dillip Kumar Mishra, Prakash Kumar Ray, and Asit Mohanty
Elsevier
Dillip Kumar Mishra, Tapas Kumar Panigrahi, Prakash Kumar Ray, and Asit Mohanty
Elsevier
S. Mohanty, P. K. Patra, A. Mohanty, A. Harrag, and Hegazy Rezk
Frontiers Media SA
The measurement of solar radiation and its forecasting at any particular location is a difficult task as it depends on various input parameters. So, intelligent modeling approaches with advanced techniques are always necessary for this challenging activity. Adaptive neuro-fuzzy inference system (ANFIS) based on modeling plays a vital role in the selection of relevant input parameters for undertaking precise solar radiation prediction. Numerous literature works focusing on ANFIS-based techniques have been reviewed during the estimation of solar energy incidents in the eastern part of India. During solar forecasting, the input parameters considered for this model are the duration of the sunshine, temperature, and humidity whereas the clearness index value has been considered as an output parameter for calculation. For designing the model, practical data sets have been prepared for some specified locations. Finally, the outcome is compared with several other techniques. During this course of analysis, several studies have been reviewed for a comprehensive literature survey work.
Dillip Kumar Mishra, Prakash Kumar Ray, Li Li, Jiangfeng Zhang, M.J. Hossain, and Asit Mohanty
Elsevier BV
Mrutyunjay Senapati, Pratap K Panigrahi, Prakas K Ray, and Asit Mohanty
IEEE
Due to the switchover in the operation pattern from grid-connected position to the islanded one, there is a considerable and frequent fluctuation with respect to short current position in the microgrid. As a result, this observed change in the network will have an impact on the over current scheme. Further, there will be a delay in the over current relay (OCR) operational time or perhaps a failure to isolate problems inside the microgrid. In this study, optimization of the Time Multiplier Setting (TMS) of the over-current relay is carried out in order to tackle the problem of coordination of OCRs. The undesirable industrial relay limitations and restrictions are also articulated as optimization constraints in this study. Particle Swarm Optimization(PSO) is used to compare the outcomes of the given optimization strategy. With the IEC Microgrid Benchmark, the suggested approach’s efficacy and potency are evaluated. The model-750/760 over-current relay from GE- Multilin is used in ETAP to verify the results.
Aishwarya A Jena, Suvendu M. Baral, Shanti S. Rath, P. Ray, Ajit Kumar Barisal, Rachita R. Sarangi and A. Mohanty
Because of the penetration of renewable energy into the power system, the system will undergo significant changes, not only in terms of performance but also in terms of relay protection settings. It will disrupt existing relay coordination, perhaps preventing these relays from detecting a fault that is intended to be inside their protective zone. A considerable number of relay and circuit breaker sets must be placed in order to provide appropriate reliable protection and maintain the smooth operation of the electrical system. A suitable coordinated protection system with a predetermined sequence of action is necessary to isolate the malfunctioning zone from the remainder of the network. The primary protection relay must operate at the set time. If case of failure of primary protection, the backup protection shall be coordinated to isolate the faulty part. Using ETAP software, protection coordination is simulated in real time and the results are presented.
Shanti S. Rath, Prakash K. Ray, Gayadhar Panda, Aishwarya A Jena, Suvendu M. Baral, Rachita R. Sarangi, and Asit Mohanty
IEEE
Reliability of operation is necessary in industrial applications wherein the failure or blackout of generators can have severe consequences on constantly running loads which cater to various processes. This concern has been addressed through redundant sources which are connected through tie breakers to cater to the loads in case that the main sources of generation fail. This entire system is connected to the grid to evacuate any excess generation or draw power from the grid in case there is any deficit. This paper studies the concept of power generation stability, in a nine-generator, two-bus system. The purpose of this study is to examine and assess the stability of such industrial networks, under various contingencies. Changing fault operating points and protection device settings were used to simulate the performance of the industrial network to test its robustness. This article focuses entirely on transient analysis, system coordination, and star protection. This was done with the ETAP software.
Dillip K. Mishra, Mojtaba J. Ghadi, Li Li, Md. Jahangir Hossain, Jiangfeng Zhang, Prakash K. Ray, and Asit Mohanty
Elsevier BV
Soumya Ranjan Das, Prakash K. Ray, Asit Mohanty, and Himansu Das
Springer Science and Business Media LLC