Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment, Renewable Energy, Sustainability and the Environment, Embryology
9
Scopus Publications
28
Scholar Citations
2
Scholar h-index
1
Scholar i10-index
Scopus Publications
GSM based Prepaid Energy Meter S. Poorna Chander Rao, Muthyala Ramakrishna, Venapally Sairam, Bangari Narsimulu Proceedings of 7th International Conference on Inventive Material Science and Applications Icima 2025, 2025 The GSM-based prepaid energy meter is a system designed to help manage electricity usage efficiently and remotely. It operates on a prepaid basis, where users load credit into their accounts before consuming electricity. Once the credit is exhausted, the power supply is automatically cut off, preventing further use without payment. This system is user-friendly, allowing users to recharge their credit via SMS, making it easy to add funds from anywhere. The meter tracks energy consumption and transmits the data to the service provider's central system, enabling the monitoring of usage patterns and identifying any billing issues. When the account balance is low or the power is disconnected, users are alerted via SMS. Additionally, the system supports remote control for disconnecting and reconnecting power, giving users more control over their electricity supply. This technology helps reduce energy theft, improve the accuracy of billing, and enhance the overall efficiency of electricity distribution.
Enhancing Smart City Efficiency by Mitigating Electricity Theft in Smart Grids Using Lightweight DNN and SMO S Poorna Chander Rao, Swarnam S, Neeraj Kumar, Sheikameer Batcha S, Vanaja Sivalanka, A. V. Deepan Chakravarthi 3rd International Conference on Integrated Circuits and Communication Systems Icicacs 2025, 2025 Smart cities require smart grid integration, industrial IoT, energy communities, renewable energy, smart healthcare systems, and the 6G network. Smart grids enable two-way power and data communication between various IoT devices and apps. However, increasing cyber layers and IoT connection threaten grid stability. Miscreants use these loopholes to illegally cut their power costs. The recommended approach includes model training, feature extraction, and preprocessing. Fixing outliers, standardizing units, and filling missing data are preprocessing steps. Feature extraction emphasizes majority class samples while considering minority class samples to account for the power consumption dataset's class imbalance. During model training, a lightweight deep neural network (DNN) addresses these difficulties. The Lightweight DNN model outperforms DNN and CNN for power theft detection. It improved smart grid power theft defenses to 94.28% accuracy. Smart grid electricity theft hinders smart city growth, but this study indicates that the Lightweight DNN model can handle it. The method ensures detection accuracy and grid stability, helping smart city infrastructures integrate current technology sustainably.
Intelligent IoT-Based Home Energy Management System using BO-BiLSTM Vittam Rakesh, S. Poorna Chander Rao, Padmaja Voleti, N. Rajavinu, G. Indira, Vijay Kumar Dwivedi 2025 International Conference on Intelligent Computing and Knowledge Extraction Icicke 2025, 2025 Cost savings, environmental protection, and a smaller carbon footprint are all benefits of smart houses with efficient energy consumption. As a result, Intelligent Home Energy Management Systems are vital for smart city and smart home energy efficiency optimisation. Unfortunately, there aren't many low-cost, easy-to-implement, and low-maintenance solutions available, which is preventing their widespread adoption. There are also difficulties in storing, managing, and analysing the massive amounts of data produced from many sources. Big Data and the IoT provide scalable answers to these problems by allowing us to sense, monitor, and control the energy consumption in our homes. Preprocessing, feature extraction, and model training are the three steps that make up the proposed Intelligent Home Energy Management System. Before offline feature extraction and grouping, normalisation is used as a preprocessing step. BO-BiLSTM is used to train the model, which improves the accuracy of predictions. With better efficiency and scalability, the suggested method beats the standard BiLSTM and BO-LSTM models, according to the results. The system's integration of IoT and Big Data allows it to more reliably regulate energy use and successfully overcome deployment hurdles. Improving computing efficiency and integrating real-time adaptive learning for additional optimisation can be the subject of future study.
Next-Generation Safety using a Continuous HMM Method for Automatic Accident Detection S. Poorna Chander Rao, Deepak Asrani, Vinayak Niwasrao Patil, K. Kartheeban, Manasi Vyankatesh Ghamande, S. R. Raja 3rd International Conference on Data Science and Information System Icdsis 2025, 2025 Traffic has been thicker and more demanding on drivers over the past few decades due to a precipitous growth in vehicle numbers. This situation has increased road accidents in most countries, causing concern. Sharing information about traffic accidents through the mutually beneficial link between cars and communication technology can help victims and speed up emergency response. If disasters' people and material needs were better estimated, victims may be greatly minimised. The recommended model involves feature extraction, model training, and preprocessing. First, min-max normalisation is used. For each shot, it compare the histograms of the subsequent frames to find critical frames. Next, measure vehicle distances to spot accidents. This work uses a continuous HMM to categorise occurrences by state transition probability density to understand accidents. This study shows that the Hybrid Continuous HMM ensemble classifier accurately tracks automated accident detection dynamics. The suggested traffic accident identification and categorisation technique was accurate at 95.64%. The investigation reveals that the suggested automatic accident detection system works. Using advanced models and real-time data processing can improve response times and resource allocation. Future research could strengthen the model and investigate other parameters to improve detection accuracy and resilience.
ML-ANN - Based Hybrid Model for Intelligent EV Battery Management S. Poorna Chander Rao, Periyasamy. V M, Satheesh Kumar. R, K. Balasubramanian, A. A. Ahamed Haris, Varadharaj. M 2nd International Conference on Intelligent Algorithms for Computational Intelligence Systems Iacis 2025, 2025 EV safety and efficiency depend on precise parameter measurements and well-functioning battery storage systems. Overcharging, over discharging, overloading, cell imbalance, thermal runaway, and combustion hazards are among the significant threats that can result from inadequate monitoring. A key metric in Intelligent EV Battery Management is the SOC, which measures the amount of energy that is currently accessible in a battery in relation to its capacity and gives important information about how reliable it is to operate. In order to overcome these obstacles, this research used an MLANN model for enhanced prediction and monitoring. To improve the accuracy of the predictions, the method took data cleansing and balancing procedures into account, and also examined moulding characteristics including injection speed, holding duration, and cooling time. The MLANN model was able to capture complicated interactions between system characteristics and battery behaviour, as shown by its excellent prediction accuracy of 94.44% during experimental validation. The results show that Intelligent EV Battery Management systems can benefit from MLANN integration in terms of stronger safety procedures, better overall system performance, and more accurate SOC prediction. This, in turn, can lead to safer, more efficient, and dependable EV technologies.
Protection System for High Voltage Electrical Appliances Against Over and Under Voltage Fluctuations S. Poorna Chander Rao, Venapally Sairam, Muthyala Ramakrishna, Bangari Narsimulu 5th International Conference on Sustainable Communication Networks and Application Icscna 2024 Proceedings, 2024 The instability of AC mains supply poses a significant threat to the integrity of industrial and household appliances, which are often costly and vulnerable to damage. Voltage fluctuations can lead to energy losses, reduced power factors, and decreased overall efficiency. Moreover, poor power quality can have a detrimental impact on expensive equipment, emphasizing the need for a reliable protection mechanism. The proposed system recognizes under-voltage situations arising from sudden load surges, system faults, or high source impedance due to loose connections. Conversely, over-voltage conditions are triggered by rapid load reductions in circuits with poor voltage regulation or faulty neutral wire connections. By establishing a protective threshold, the system classifies any voltage below the rated value as under-voltage and above as overvoltage, ensuring the safe operation of electrical appliances. The system can detect when the voltage exceeds or drops below predetermined limits, triggering the relay to trip.
An IoT-Based Sensor Technology for Improving Reliability and Power Quality in Smart Grid Systems , S. Poorna Chander Rao, M. Sushama International Journal of Electrical and Electronic Engineering and Telecommunications, 2023 An Internet of Things (IoT) based smart grid technology becomes more popular and gained significant attention in present days. Due to the rapid growth of information and technology, the IoT is increasingly used for industrial automation, smart monitoring and control. The work is focused on implementing IoT based smart sensor technology for improving the reliability and power quality of smart grid systems. Typically, the smart sensors are considered as the most essential IoT devices used for improving the reliability of smart grid systems. The proposed framework comprises the major elements of monitoring, communication and analysis components, in which the monitoring element comprises the current and voltage sensors that is directly connected with the consumer loads. Then, the communication component comprises the Arduino sensor and WiFi module, which helps to establish the wireless communication. Here, the analysis component is used as a remote application that is used to get the voltage profiles, energy reports, voltage and current. During analysis, the performance of the proposed framework is validated and tested by using different parameters like, voltage, current, power, apparent power, and energy.
Performance Analysis of Artificial Intelligence Controller for PV and Battery Connected UPQC Koganti Srilakshmi, S Poorna Chander Rao, G Deepika, B.V Sai Thrinath, Alapati Ramadevi, et al. International Journal of Renewable Energy Research, 2023 Nowadays, integration of the non-conventional energy sources like wind, tidal, solar etc into the grid is suggested in order to minimize the losses in the distribution network and to meet the demand. The arrival of the power electronics equipments to control the nonlinear loads has made an impact on the power quality. The unified power quality conditioner (UPQC) is a FACTS device with the back to back converters, coupled together with a DC-Link capacitor. This paper suggests an intelligent hybrid controller for the solar Photo-voltaic system and Battery storage system integrated UPQC. The proposed controller adapts both the qualities of artificial neural network and Integral sliding-mode controller. The synchronization of phases is created by self tuning filter (STF) in association with unit vector generation method (STF-UVGM) for the superior performance of UPQC during the unbalanced/ distorted supply voltages conditions. Therefore, the necessity of Phase-locked-loop, Low pass filters and High pass filters are eliminated. However, STF is used for separating the Harmonic and Fundamental components. In addition, STF-UVGM was used for generation of synchronization phases of series and shunt filters. The prime objectives of the suggested artificial neural network integral sliding mode hybrid controller (ANNISMHC) are fast action to retain the DC-Link voltage to the constant value during load/ irradiation variations, diminish the harmonics in the current waveforms, power-factor enhancement, maximum mitigation of sag, swell and disturbances in supply voltage, and compensation for the unbalanced supply voltages. The working of suggested ANNISMHC was investigated on five test cases for several combinations of loads, and balanced/unbalanced supply voltages. However, to demonstrate supremacy of the suggested ANNISMHC comparative study with the different controllers those are available in literature and also with the standard controllers like PIC, SMC, and FLC. The ANNISMHC shows an extra-ordinary performance in diminishing THD thereby improving PF and reducing voltage distortions.
Power systems protection coordination and associated reliability with smart grid security S Poorna Chander Rao, G. Mohan Babu Proceedings of the International Conference on Computing Methodologies and Communication Iccmc 2017, 2017 In this paper, new Hierarchically Coordinated Protection (HCP) concept that mitigates and manages the effects of increased grid complexity on the protection of the power system is proposed. The concept is based on predicting protection circumstances in real-time, adapting protection actions to the power system's prevailing conditions, and executing corrective actions when an undesirable outcome of protection operation is verified. Depending on an application, HCP concept may utilize local and wide area measurements of the power system parameters, as well as non-power system data, such as meteorological, detection of lightning strikes, outage data and geographic information. Since HCP introduces intelligence, flexibility and self-correction in protection operation, it is well suited for the systems with increased penetration of renewables where legacy solutions may be prone to mis-operate. Such instances are unintended distance relay tripping for overloaded lines, insensitive anti-islanding scheme operation, and inability to mitigate cascading events, among other system conditions caused by renewable generation prevailing in future grids.
RECENT SCHOLAR PUBLICATIONS
Artificial Intelligence and Machine Learning Applications in Electric Vehicle Technology and Education HYD Mr. S Poorna Chander Rao (Asst. Prof. EEE, GCET Artificial Intelligence and Machine Learning Applications in Electric … , 2025 2025
“ML-ANN–Based Hybrid Model for Intelligent EV Battery Management” HYD Mr. S Poorna Chander Rao (Sr. Asst. Prof. EEE, GCET 2nd International Conference on Intelligent Algorithms for Computational … , 2025 2025
An IOT and Machine Learning Enabled Smart Solar Powered Pesticide Sprayer for Precision Agriculture HYD Mr. S. Poorna chander Rao (Asst. Prof. EEE, GCET IN Patent 202541026572 A , 2025 2025
Next-Generation Safety using a Continuous HMM Method for Automatic Accident Detection HYD Mr. S Poorna Chander Rao (Sr. Asst. Prof. EEE, GCET 2025 3rd International Conference on Data Science and Information System … , 2025 2025
Protection System for High Voltage Electrical Appliances Against Over and Under Voltage Fluctuations HYDVS S. Poorna Chander Rao (Sr. Asst. Prof. EEE, GCET, ... 2024 International Conference on Sustainable Communication Networks and … , 2025 2025
Intelligent IoT-Based Home Energy Management System using BO-BiLSTM HYD Mr. S Poorna Chander Rao (Asst. Prof. EEE, GCET 2025 International Conference on Intelligent Computing and Knowledge … , 2025 2025
Adoption of Solar-Powered Cold Storage and Renewable Energy Solutions in Post-Harvest Management for Rural SMEs HYD Mr. S Poorna Chander Rao (Asst. Prof. EEE, GCET Adoption of Solar-Powered Cold Storage and Renewable Energy Solutions in … , 2025 2025
Solar Thermal Technologies and Nano Enhanced phase Change materials for High Efficiency Electric and Solar Mobility HYD Mr. S Poorna Chander Rao (Sr. Asst. Prof. EEE, GCET Solar Thermal Technologies and Nano Enhanced phase Change materials for High … , 2025 2025
Enhancing Smart City Efficiency by Mitigating Electricity Theft in Smart Grids Using Lightweight DNN and SMO HYD Mr. S Poorna Chander Rao (Sr. Asst. Prof. EEE, GCET 2025 3rd International Conference on Integrated Circuits and Communication … , 2025 2025
Solar Power System HYD Mr. S Poorna Chander Rao (Asst. Prof. EEE, GCET 2024
Hybrid Power Integration on Highways SPCR D Abhilash N.Pravalika, S.Nagaraju INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN TECHNOLOGY 10 (11), 1277-1280 , 2024 2024
An Internet Of Things Based Anomaly Detection Approach For Accurate Fault Detection On Fire Alarm Systems SP Rao 2023
Implementation of hybrid machine learning models for sensor fault detection and management of battery in electric vehicles SPC RAO 2023
Performance analysis of artificial intelligence controller for PV and battery connected UPQC K Srilakshmi, SPC Rao, G Deepika, BVS Thrinath, A Ramadevi, ... International Journal of Renewable Energy Research (IJRER) 13 (1), 155-170 , 2023 2023 Citations: 24
Electrical Machines VR S POORNA CHANDER RAO, VOLETI PADMAJA 2023
The Technology of Electrical Vehicles SPC RAO RK Publications , 2023 2023
An IoT-Based Sensor Technology for Improving Reliability and Power Quality in Smart Grid Systems DMS S POORNA CHANDER RAO International Journal of Electrical and Electronic Engineering … , 2023 2023
Renewable Energy System with Preventive Mechanism for Smart Grid DMS S POORNA CHANDER RAO CR Publication Agency 1 (2), 1-7 , 2023 2023
Design and Analysis of Battery super capacitor Hybrid Electrical Energy Storage Systems for Regulation Service SPC RAO 2022
Document classification using Artificial Intelligence SPC RAO 2022
MOST CITED SCHOLAR PUBLICATIONS
Performance analysis of artificial intelligence controller for PV and battery connected UPQC K Srilakshmi, SPC Rao, G Deepika, BVS Thrinath, A Ramadevi, ... International Journal of Renewable Energy Research (IJRER) 13 (1), 155-170 , 2023 2023 Citations: 24
Power systems protection coordination and associated reliability with smart grid security SPC Rao, GM Babu 2017 International Conference on Computing Methodologies and Communication … , 2017 2017 Citations: 2
Enhancement of fast loop controlling mechanism for capacitor-supported dynamic voltage restorer (DVR) using modulation technique SPC Rao International Journal of Engineering Research and Applications 3 (2), 1474-1491 , 2013 2013 Citations: 2
Artificial Intelligence and Machine Learning Applications in Electric Vehicle Technology and Education HYD Mr. S Poorna Chander Rao (Asst. Prof. EEE, GCET Artificial Intelligence and Machine Learning Applications in Electric … , 2025 2025
“ML-ANN–Based Hybrid Model for Intelligent EV Battery Management” HYD Mr. S Poorna Chander Rao (Sr. Asst. Prof. EEE, GCET 2nd International Conference on Intelligent Algorithms for Computational … , 2025 2025
An IOT and Machine Learning Enabled Smart Solar Powered Pesticide Sprayer for Precision Agriculture HYD Mr. S. Poorna chander Rao (Asst. Prof. EEE, GCET IN Patent 202541026572 A , 2025 2025
Next-Generation Safety using a Continuous HMM Method for Automatic Accident Detection HYD Mr. S Poorna Chander Rao (Sr. Asst. Prof. EEE, GCET 2025 3rd International Conference on Data Science and Information System … , 2025 2025
Protection System for High Voltage Electrical Appliances Against Over and Under Voltage Fluctuations HYDVS S. Poorna Chander Rao (Sr. Asst. Prof. EEE, GCET, ... 2024 International Conference on Sustainable Communication Networks and … , 2025 2025
Intelligent IoT-Based Home Energy Management System using BO-BiLSTM HYD Mr. S Poorna Chander Rao (Asst. Prof. EEE, GCET 2025 International Conference on Intelligent Computing and Knowledge … , 2025 2025
Adoption of Solar-Powered Cold Storage and Renewable Energy Solutions in Post-Harvest Management for Rural SMEs HYD Mr. S Poorna Chander Rao (Asst. Prof. EEE, GCET Adoption of Solar-Powered Cold Storage and Renewable Energy Solutions in … , 2025 2025
Solar Thermal Technologies and Nano Enhanced phase Change materials for High Efficiency Electric and Solar Mobility HYD Mr. S Poorna Chander Rao (Sr. Asst. Prof. EEE, GCET Solar Thermal Technologies and Nano Enhanced phase Change materials for High … , 2025 2025
Enhancing Smart City Efficiency by Mitigating Electricity Theft in Smart Grids Using Lightweight DNN and SMO HYD Mr. S Poorna Chander Rao (Sr. Asst. Prof. EEE, GCET 2025 3rd International Conference on Integrated Circuits and Communication … , 2025 2025
Solar Power System HYD Mr. S Poorna Chander Rao (Asst. Prof. EEE, GCET 2024
Hybrid Power Integration on Highways SPCR D Abhilash N.Pravalika, S.Nagaraju INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN TECHNOLOGY 10 (11), 1277-1280 , 2024 2024
An Internet Of Things Based Anomaly Detection Approach For Accurate Fault Detection On Fire Alarm Systems SP Rao 2023
Implementation of hybrid machine learning models for sensor fault detection and management of battery in electric vehicles SPC RAO 2023
Electrical Machines VR S POORNA CHANDER RAO, VOLETI PADMAJA 2023
The Technology of Electrical Vehicles SPC RAO RK Publications , 2023 2023
An IoT-Based Sensor Technology for Improving Reliability and Power Quality in Smart Grid Systems DMS S POORNA CHANDER RAO International Journal of Electrical and Electronic Engineering … , 2023 2023
Renewable Energy System with Preventive Mechanism for Smart Grid DMS S POORNA CHANDER RAO CR Publication Agency 1 (2), 1-7 , 2023 2023