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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) International Journal of Informatics and Communication Technology (IJ-ICT) International Journal of Applied Power Engineering (IJAPE) International Journal of Advances in Applied Sciences Indonesian Journal of Electrical Engineering and Computer Science
Salkuti, Surender Reddy
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Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Strategic Deployment of EV Charging Infrastructure: An In-Depth Exploration of Optimal Location Selection and CC-CV Charging Strategies Mishra, Debani Prasad; Nayak, Pranav Swaroop; Kumar, Aman; Salkuti, Surender Reddy
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i1.pp259-267

Abstract

The continued expansion of the electric vehicle (EV) market necessitates strategic planning for the placement of charging stations to ensure efficient access and utilization of electric infrastructure. This paper presents a comprehensive review of the critical factors in optimizing the selection of EV charging station locations, along with the implementation of Constant Current-Constant Voltage (CC-CV) charging models. The study addresses the challenges and opportunities in identifying the most effective locations for charging stations to accommodate the growing demand for sustainable transportation. Furthermore, it examines the benefits of adopting CC-CV charging models to improve the charging process, achieving a balance between charging speed and battery longevity. Through this analysis, the review aims to provide valuable insights to stakeholders involved in the development and expansion of EV charging infrastructure, thereby supporting the transition to a more sustainable and extensive electric mobility ecosystem.
Efficient blockchain based solution for secure medical record management Mishra, Debani Prasad; Rajeev, B; Mallick, Soubhagya Ranjan; Lenka, Rakesh Kumar; Salkuti, Surender Reddy
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i1.pp59-67

Abstract

Electronic medical records (EMRs) have become a key player in the healthcare ecosystem contributing to the assessment of ailments, the choice of the treatment avenue, and the delivery of services. However, there is consideration of EMR storage whereby centralized storage leads to increased security and privacy issues in the patient’s record. In this paper, we proposed a blockchain and interplanetary file system (IPFS) based prototype model for EMR management. It provides a smart contract-enabled decentralized storage platform where healthcare data security, availability, and access management are prioritized. This model also employs cryptographic techniques to protect sensitive healthcare data. Finally, the model is evaluated in a realistic scenario. The experimental results demonstrate that compared to the current systems, the proposed prototype model outperforms them in terms of efficiency, privacy, and security.
Application of monarch butterfly optimization algorithm for solving optimal power flow Jung, Chan-Mook; Pagidipala, Sravanthi; Salkuti, Surender Reddy
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 13, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v13i3.pp519-526

Abstract

This paper proposes a highly flexible, robust, and efficient constraint-handling approach for the solution of the optimal power flow (OPF) problem and this solution lies in the ability to solve the power system problem and avoid the mathematical traps. Centralized control of the power system has become inevitable, in the interest of secure, reliable, and economic operation of the system. In this work, OPF is solved by considering the three distinct objectives, generation cost minimization, power loss minimization, and enhancement of voltage stability index. These three objectives are solved separately by considering the evolutionary-based monarch butterfly optimization (MBO) algorithm. This MBO algorithm is validated on the IEEE 30 bus network and the obtained results are compared with differential evolution, particle swarm optimization, genetic algorithm, and Jaya algorithm. The obtained results reveal that among the various optimization algorithms considered in this work, the MBO evolves as the best algorithm for all three case studies.
Analysis and simulation of 7-level and 9-level cascaded H-bridge multi-level inverters Banka, Sujatha; Sunil Kumar, Chava; Salkuti, Surender Reddy; Bhupathiraju, Sai Sruthi; Balakishan, Kasoju Pragathi; Chaturya, Paipoti Pooja; Namineni, Rishitha
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i1.pp11-22

Abstract

Multi-level inverters (MLIs) have created a new revolution in high-power and medium-voltage applications in industry and research. In recent years, cascaded multi-level inverters have gained significant interest due to their ability to generate high-quality output waveforms with reduced total harmonic distortion (THD). This paper discusses the analysis and simulation of 7-level and 9-level cascaded H-bridge multi-level inverters using mathematical models and simulation tools. The proposed research puts emphasis on evaluating the performance and control strategies of these inverters. The control strategies, including pulse width modulation (PWM) techniques, are discussed in depth, with a focus on their effect on output waveform quality and reduction of THD. The simulation results are compared to showcase the advantages offered by the cascaded multi-level inverters in terms of waveform quality. The findings demonstrate the superior performance and power quality advantages offered by these multi-level inverters compared to traditional two-level inverters. Additionally, a passive LC filter is designed and implemented along with a multi-level inverter configuration that helps to keep the THD within the limits specified by IEEE standards.
Metaheuristic algorithms for parameter estimation of DC servo motors with quantized sensor measurements Mishra, Debani Prasad; Behera, Sandip Ranjan; Dash, Arul Kumar; Ojha, Prajna Jeet; Salkuti, Surender Reddy
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i1.pp101-108

Abstract

Manufacturing, aviation, and robotics have increased servo motor use due to their precision, reliability, and adaptability in various applications. This study compares three metaheuristic techniques for servo motor model parameter estimation with sensor measurement quantization, focusing on their accuracy and efficiency. Armature resistance, back electromotive force (EMF) constant, torque constant, coil inductance, friction coefficient, and rotor-load inertia are crucial to servo motor behavior prediction, significantly impacting overall system performance. Each approach was rigorously tested and analyzed to evaluate its effectiveness in predicting servo motor characteristics. The results revealed that particle swarm optimization and the firefly algorithm delivered comparable performance, particularly excelling in scenarios where sensor measurement quantization introduced noise or imprecision in the data. These methods demonstrated strong resilience and accuracy under such challenging conditions. In contrast, the genetic algorithm did not perform as well, falling short when compared to the other two techniques in handling noisy or imprecise data, indicating its relative inefficiency in such environments. These findings give servo motor designers and engineers across industries a powerful tool for performance prediction.
Cyber-physical resilience system for anomaly detection in industrial environments Mishra, Debani Prasad; Lenka, Rakesh Kumar; Yagyna Duthsharma, Rampa Sri Sai; Kumar, Pavan; Bhardwaj, Lakshay; Salkuti, Surender Reddy
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i2.pp497-505

Abstract

This work explores the topic of cybersecurity in the context of electric vehicles (EVs). It ensures the resilience of cyber-physical systems against anomalies, which is paramount for maintaining operational efficiency and safety. This paper presents a cyber-physical resilience system (CPRS) customized for anomaly detection. Maintaining operational efficiency and safety in today’s networked industrial contexts requires that cyber-physical systems be resilient to abnormalities. With an emphasis on EVs, this research introduces a unique CPRS designed for anomaly detection in industrial settings. By utilizing the combination of digital and physical elements, the CPRS uses sophisticated monitoring and reaction systems to identify and address irregularities instantly. The process includes creating algorithms for anomaly detection and putting in place a framework that is responsive enough to change with the dangers that it faces. The efficiency of the CPRS in detecting unusual behaviors in EVs is demonstrated by experimental findings, which also improve the overall resilience of the system. Moreover, the research’s ramifications go beyond EVs to include a variety of industrial settings, providing valuable information for the development and execution of resilient cyber-physical systems. This paper highlights the significance of proactive resilience measures in protecting critical infrastructure and advances anomaly detection approaches.
Load forecasting of electrical parameters: an effective approach towards optimization of electric load Mishra, Debani Prasad; Pradhan, Rudranarayan; Priyadarshini, Ananya; Das, Subha Ranjan; Salkuti, Surender Reddy
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i2.pp708-716

Abstract

The increasing need for energy and the increasing cost of electricity have prompted the development of smart energy optimization systems that can help consumers reduce their electricity consumption and minimize costs. These systems are developed on the concept of a “smart grid” which is a digitalized and intelligent energy network that provides help in the efficient distribution of energy. Load forecasting plays a crucial role in the precise prediction of uncontrollable electrical load. Long-term load analysis predicts a load of more than one year and helps in the planning of power systems whereas short-term and medium-term load forecasting helps in the supply and distribution of load, maintenance of load system, ensuring safety, continuous electricity generation, and cost management. Machine learning (ML) focuses on the development of smart energy optimization systems by enabling intuitive decision-making and reciprocation to sudden variations in consumer energy demands. This study focuses on the consumption of consumer electricity and provides a solution regarding the optimized methods that will predict future consumption based on previous data and help in reducing costs and preserving renewable energy. This research promotes sustainable energy usage. The use of ML models enables intelligent decision-making and accurate predictions, making the system an effective tool for managing electricity consumption.
Enhancing logo security: VGG19, autoencoder, and sequential fusion for fake logo detection Mishra, Debani Prasad; Ojha, Prajna Jeet; Dash, Arul Kumar; Sethy, Sai Kanha; Behera, Sandip Ranjan; Salkuti, Surender Reddy
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i2.pp506-515

Abstract

This paper deals with a way of detecting fake logos through the integration of visual geometry group-19 (VGG19), an autoencoder, and a sequential model. The approach consists of applying the method to a variety of datasets that have gone through resizing and augmentation, using VGG19 for extracting features effectively and autoencoder for abstracting them in a subtle manner. The combination of these elements in a sequential model account for the improved performance levels as far as accuracy, precision, recall, and F1-score are concerned when compared to existing approaches. This article assesses the strengths and limitations of the method and its adapted comprehension of brand identity symbols. Comparative analysis of these competing approaches reveals the benefits resulting from such fusion. To sum up, this paper is not only a major contribution to the domain of counterfeit logo detection but also suggests prospects for enhancing brand security in the digital world.
Optimal placement of DGs in a multi-feed radial distribution system using actor-critic learning algorithm Battu, Neelakanteshwar Rao; Salkuti, Surender Reddy
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i2.pp319-327

Abstract

Multi-feed radial distribution systems are used to reduce the losses in the system using reconfiguration techniques. Reconfiguration can reduce the losses in the system only to a certain extent. Introduction of distributed generators has vastly improved the performance of distribution systems. Distributed generators can be used for reduction of loss, the improvement of the voltage profile, and reliability enhancement. Distribution generators play a vital role in reducing the losses in the distribution system. Placement of distributed generators in a multifeed system is a complex task to be solved using classical optimization methods. Classical optimization techniques may sometimes fail to provide a converged solution. Installation of distributed generators at suitable locations in a multi-feed system is found in this paper using the actor-critic learning algorithm. Actorcritic learning approach uses temporal difference error as a signal in making judgements regarding actions to be taken for future states in accordance with rewards that have been obtained by applying the present policy. The approach is applied to a standard 16-bus distribution system for reduction of system losses, and the results are discussed.
Optimizing vehicle-to-grid scheduling and strategic placement for dynamic wireless charging of electric vehicles Mishra, Debani Prasad; Sahay, Sanchita; Kumar, Ayush; Salkuti, Surender Reddy
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i2.pp328-337

Abstract

Dynamic wireless charging of electric vehicles (EVs) has become popular in intelligent transportation systems (ITS). However, both economic and smart city perspectives should be taken into account in the integration of wireless charging infrastructure for electric vehicles. Current research mainly focuses on power transfer (PT) or autonomous vehicle-to-grid (V2G) transfer. This paper presents a multilayered approach that combines optimal PT planning based on urban traffic and energy efficiency data with dynamic V2G planning. Simulation results show that the efficiency of PT placement and V2G scheduling increases and provides good results for smart city enterprises. This multilayered approach not only optimizes the efficiency of power transfer placement and V2G scheduling but also positions itself as a pivotal driver for the sustainable evolution of urban mobility. As dynamic wireless charging continues to shape the future of intelligent transportation systems, this research stands at the intersection of technological innovation, economic prudence, and urban planning, offering a blueprint for the seamless integration of EVs into the fabric of smart cities.
Co-Authors Agarwal, Nandini Agrawal, Shruti Balakishan, Kasoju Pragathi Banka, Sujatha Battu, Neelakanteshwar Rao Behera, Niharika Behera, Pratyus Ranjan Behera, Sandip Ranjan Behera, Subhashis Satyabrata Bhardwaj, Lakshay Bhatt, Stuti Bhupathiraju, Sai Sruthi Biswal, Prabin Chaturya, Paipoti Pooja Das, Soumya Ranjan Das, Subha Ranjan Dash, Arul Kumar Gupta, Shubh Hembram, Dashmat Jhunjhunwalla, Drishana Jung, Chan-Mook Kedia, Nisha Kumar, Aman Kumar, Ayush Kumar, Pavan Kumar, Prince Lenka, Rakesh Kumar Mallick, Soubhagya Ranjan Mishra, Debani Prasad Mishra, Sivkumar Namineni, Rishitha Nayak, Pranav Swaroop Ojha, Prajna Jeet Padhy, Somya Siddharth Pagidipala, Sravanthi Palei, Shantilata Patro, Aditya Ranjan Pattanayak, Nitesh Pradhan, Partha Sarathi Pradhan, Rudranarayan Priyadarshini, Ananya Rai, Niti Rani rai, Priyanka Rajeev, B Rout, Kishrod Kumar Routray, Bhabesh Sahay, Sanchita Sahoo, Arun Kumar Sahu, Jayanta Kumar Sahu, Smruti Susmita Samal, Sarita Samanvi, Potnuru Sankaran, Madhu Sree Satapathy, Swayamjyoti Senapati, Asutosh Senapati, Rudranarayan Seong-Cheol Kim, Seong-Cheol Sethy, Sai Kanha Shah, Dhruvi Shekhar, Priyansu Singh, Anurag Singh, Saksham Subudhi, Umamani Sunil Kumar, Chava Suresh, Alka Manvayalar Swain, Raj Alpha Uday, Peesodi Yagyna Duthsharma, Rampa Sri Sai Yashwanth, Lingam