Dr.L V Suresh Kumar was born in Kovvada Village, Andhra pradesh,India in 1987. He received the B.Tech degree in Electrical and electronics engineering from JNTU Hyderabad, M.Tech. degrees in power and energy system from the University of national institute of technology, karnataka, in 2010 and the Ph.D. degree in electrical and electronics engineering from GITAM University, Vishakhapatnam, India, in 2020.From 2010 to 2020, he was a Assistant professor in electrical and electronics engineering with the Electrical Engineering Department, GMR Institute of technology,Rajam. He is the author of one book, more than 40 articles. His research interests include renewable energy systems, FACTS, AGC and Electrical system applications.
EDUCATION
Ph.D, M.Tech, B.Tech
RESEARCH INTERESTS
Control system, Power system, Renewable energy systems, multi level inverters , FACTS, Optimization
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Scopus Publications
Scopus Publications
Deep Learning and Cloud-Integrated IoT Systems for Early Crop Disease Detection Suresh Kumar L V, Kuppili Saipraneeth, Bojanki Priyanka Proceedings of the 2025 3rd International Conference on Cyber Physical Systems Power Electronics and Electric Vehicles Icpeev 2025, 2025 Crop diseases pose significant challenges to global agricultural productivity and food security, often leading to severe economic and environmental consequences. Leveraging advanced technologies such as deep learning and computer vision offers promising solutions for early detection and effective management of crop diseases. This paper provides a comprehensive review of recent advancements in crop disease detection methods, focusing on state-of-the-art deep learning frameworks like Dense Net. Emphasis is placed on their application to various crops, highlighting the integration of Sensors with Raspberry pi-5 and cloud-based solutions. Key contributions include the synthesis of approaches for disease classification, data augmentation strategies, and the identification of research gaps, paving the way for future innovations.
Real Time Environmental Monitoring with Raspberry pi 3B+ and MATLAB for Enhanced Worker Safety through IoT L V Suresh Kumar, T S L V Ayyarao Proceedings of the 2024 2nd International Conference on Cyber Physical Systems Power Electronics and Electric Vehicles Icpeev 2024, 2024 In industrial environments, ensuring worker safety through real-time environmental monitoring is crucial. This paper proposes an integrated system that combines Raspberry Pi and MATLAB through Internet of Things (IoT) technologies to enhance worker safety with MQ2 and MQ135 sensors. The system continuously monitors air quality by detecting various pollutants and hazardous gases. The MQ135 sensor detects a wider spectrum of gases, including ammonia, carbon dioxide, and carbon monoxide, and the MQ2 sensor, which measures gases including gases like smoke. Data collected from these sensors is processed in real-time using MATLAB, which facilitates advanced data analysis, visualization, and alert generation. The system's IoT capability allows for remote monitoring and control, providing timely notifications and ensuring a proactive approach to managing workplace safety. This solution offers a cost-effective, scalable approach to maintaining safe industrial environments for employee protection with potential for adaptation in various sectors.
Real-Time Environmental Monitoring: IoT Integration and Remote Access via Raspberry Pi and VNC Viewer L V Suresh Kumar, T S L V Ayyarao Proceedings of the 2024 2nd International Conference on Cyber Physical Systems Power Electronics and Electric Vehicles Icpeev 2024, 2024 The growing concerns over air quality and environmental pollution necessitate advanced real-time monitoring systems capable of providing accurate environmental data. This paper introduces a scalable framework for real-time environmental sensing using the Raspberry Pi as the core processing unit. The system integrates multiple sensors: the DHT-11 for humidity and temperature, and the MQ-2 is a Smoke detecting sensor, and MQ-135 for detecting gases such as methane, carbon dioxide, and ammonia. This integration allows for continuous monitoring and data acquisition essential for both urban and industrial applications. The system's performance is evaluated based on accuracy, response time, and reliability under various conditions, demonstrating its effectiveness in delivering real-time, precise measurements. Its cost-efficiency and scalability make it suitable for both large-scale urban monitoring networks and localized industrial environments. Additionally, the system's flexibility in sensor integration and data processing capabilities provides a robust foundation for future advancements in environmental monitoring technologies. This work advances the field of IoT-based environmental sensing by addressing the challenges of sensor integration and real-time data processing on a cost-effective platform like the Raspberry Pi, contributing to improve environmental monitoring and public health initiatives.
Performance of Various Integrated Converters at Charging Station of EV's G I Kishore, T S L V Ayyarao, L V Suresh Kumar, P Pavan Satish Proceedings of the 2024 2nd International Conference on Cyber Physical Systems Power Electronics and Electric Vehicles Icpeev 2024, 2024 Industries are increasingly compelled to reduce carbon dioxide (CO2) emissions due to environmental concerns and stringent regulations. The automotive sector is tackling this challenge by focusing on vehicle electrification, which includes plug-in hybrid electric vehicles (PHEVs), hybrid electric vehicles (HEVs) and battery electric vehicles (BEVs). BEVs, in particular, offer the promise of zero tailpipe emissions and substantial long-term CO2 reduction. However, the broad embrace of electric vehicles (EVs) introduces significant challenges to power grids, primarily due to new loads and peak demand fluctuations. To mitigate these issues, Vehicle-to-Home (V2H) and Vehicle-to-Grid (V2G) technologies have been proposed, allowing for bidirectional energy flow and adaptive charging rates. Fast DC chargers, essential for quick EV charging, present additional concerns such as harmonics and peak demand, especially in weaker power systems. Addressing these concerns involves strategies like using low voltage DC-Buses, local battery storage, and integrating renewable energy sources. This work focuses on integrating various converters to optimize the charging of energy storage systems (ESS) and further charging of EVs. The system's common bus voltage is set at 1000 V, utilizing an AC to DC converter and single-inductor-energy-storage cell-based switched capacitor (SIESC-SCs) converters to achieve this output. A bidirectional converter and a buck converter connected to the common DC bus provide 800 V for charging both EVs and ESS. This configuration is implemented in MATLAB/SIMULINK, demonstrating advancements in EV charging infrastructure and potential innovations in electric vehicle technology.
Accurate Proton Exchange Membrane Fuel Cell modelling using Hiking Optimizer Tummala S L V Ayyarao, L V Suresh Kumar, K Venkata Ramireddy, Bojanki Priyanka, Alfoni Jose Kezhiyur Proceedings of the 2024 2nd International Conference on Cyber Physical Systems Power Electronics and Electric Vehicles Icpeev 2024, 2024 Proton Exchange Membrane (PEM) Fuel Cells represent a promising clean energy technology due to their high efficiency and low environmental impact. However, accurate modeling of PEM fuel cells is critical for their optimization and integration into energy systems. Traditional models often suffer from inaccuracies due to suboptimal parameter selection. This research addresses the need for a precise PEM fuel cell model by introducing an innovative parameter optimization technique. The Hiking Optimizer (HO), a novel algorithm inspired by the dynamic and adaptive strategies used in hiking, is employed to optimize the parameters of a mathematical model for PEM fuel cells. The HO algorithm's ability to navigate complex search spaces effectively makes it particularly suited for this task. The proposed optimization approach is evaluated through two benchmark case studies and its performance is compared with three well-established algorithms. The experimental results demonstrate that the Hiking Optimizer not only improves the accuracy of the PEM fuel cell model but also achieves superior optimization performance compared to the other algorithms.
Independent Active and Reactive Power Control for Single Stage H8 Transformer-less Solar PV Inverter D.V.N Ananth, L.V. Sursh Kumar, D.A. Tatajee Journal of Engineering Research Kuwait, 2023 With the rapid development in power electronics technologies and solar photovoltaic (PV) cells, the interest in solar PV cell-based electric power generation and other applications is increasing more incredibly. For low power grid or direct load applications, single-stage solar PV inverters without transformers are advantageous. Based on this concept solar single-stage eight switch H8 based transformerless solar PV inverter is proposed. The objective of the work is to present a control scheme for the H8 inverter to have better power handling capability and for independent active and reactive power control. For this, the test system is studied using MATLAB/ SIMULINK software under three cases (i) constant active power and varying reactive power, (ii) varying active power and constant reactive power, and (iii) varying both active and reactive power. The proposed inverter is compared with single-stage solar PV with two switches boost and six switches inverter topology. It is found that power flow ripples and surges are lesser for proposed H8 than with single-stage topology.
Optimal Load Frequency Control of Renewable Integrated Multi-Area Power System using War Strategy Optimization Algorithm T S L V Ayyarao, Suresh Kumar L V, Padmini Sasapu, Hema Sai Padi Proceedings of the 2023 1st International Conference on Cyber Physical Systems Power Electronics and Electric Vehicles Icpeev 2023, 2023 The increasing integration of renewable energy sources in power systems has posed new challenges in maintaining stable frequency control. This paper proposes an optimal load frequency control strategy for a multi-area power system with renewable energy integration using a War Strategy Optimization (WSO) algorithm. The objective function for tuning the PID controller parameters is based on the integral square error criterion, aiming to minimize the deviation between the system’s actual and desired frequencies. The proposed strategy is designed for a two-area power system model, considering the complexities arising from the integration of renewable energy sources. The WSO algorithm is employed to optimize the PID controller parameters, enabling the system to effectively regulate the frequency deviations caused by varying load and intermittent renewable generation.
Speed control of fuel cell electric vehicle with sinusoidal carrier wave Suresh Kumar L V, Padmini Sasapu, Hema Sai Padi, Manasa Namburi, Jyothikrishna Kona, V S S Tanuja Setti Proceedings of the 2023 1st International Conference on Cyber Physical Systems Power Electronics and Electric Vehicles Icpeev 2023, 2023 An electric vehicle (EV) is propelled by an electric motor rather than an internal combustion engine, which produces power by burning a mixture of fuel and gases. In order to solve issues like increasing pollution, global warming, the loss of natural resources, etc., such a vehicle is therefore being considered as a potential replacement for current-generation cars. many types of electric vehicles, such as EVs, HEVs, PHEVs, and FCHEVs. Since brushless DC motors (BLDC), particularly in the field of motor control, are becoming more and more popular in a variety of applications. The main goal of this paper is to simulate the speed control of a BLDC motor powered by a fuel cell and a battery using MATLAB/SIMULINK. It also compares the performance of a sinusoidal back EMF motor with a trapezoidal back EMF motor, concluding that the latter is preferable due to its higher efficiency, reduced torque ripple, smooth motion, and dynamic response.
Performance Enhancement of Doubly Fed Induction Generator–Based Wind Farms With STATCOM in Faulty HVDC Grids Yellapragada Venkata Pavan Kumar, Lagudu Venkata Suresh Kumar, Duggirala Venkata Naga Ananth, Challa Pradeep Reddy, Aymen Flah, Habib Kraiem, Jawad F. Al-Asad, Hossam Kotb, Kareem M. Aboras Frontiers in Energy Research, 2022 In this study, an investigation of different faults for a wind turbine–based doubly fed induction generator (DFIG) system is studied and the performance using a static compensator (STATCOM) is observed. The DFIG network is connected to a voltage source converter high-voltage dc link with a fault occurring near the wind generator network. The ride through capability of DFIG is promising with STATCOM using the proposed control strategy. The ac and dc voltage and torque oscillations are damped effectively, and improved power flow is observed. The low voltage AC grid fault occurs for an HVDC transmission, and the DFIG performance without and with STATCOM is compared, where the DFIG converter control schemes are developed using the proposed improved field-oriented control (IFOC) method. In this, the reference rotor flux value alters to a new synchronous speed value or a slighter value or a standstill depending on the stator voltage dip due to grid disturbance. This speed variation leads to introducing rotor current at that new rotor slip frequency as there is a change in the rotor speed because of the fault, which further decreases the stator flux dc component. Hence, this dc-offset constituent in the stator flux is alleviated and decays rapidly in scheming the divergence of the speed of the rotor to a new orientation speed with decay in the rotor flux. This operation is done in the inner control scheme of the rotor converter, which is quicker in response to the faults. Apart from this, the stator’s real and reactive power also changes accordingly based on the lookup table mechanism–based closed-loop control action of the pulse generator, and this power change is done in the outer loop. The analysis for DFIG and HVDC operation is verified under different faults without and with STATCOM.
Salp swarm algorithm based optimal speed control for electric vehicles Devendra Potnuru, Tummala Siva Lova Venkata Ayyarao, Lagudu Venkata Suresh Kumar, Yellapragada Venkata Pavan Kumar, Darsy John Pradeep, Challa Pradeep Reddy International Journal of Power Electronics and Drive Systems, 2022
Micro inverter base grid connected photovoltaic system 7th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2016, 2016
A logic sort algorithm based voltage balancing of modular multilevel converters in back to back HVDC systems International Journal of Control Theory and Applications, 2016
Multi winding transformer through multi level inverter with super capacitor base stand alone integrated wind energy system International Journal of Control Theory and Applications, 2016
