PV-grid Performance improvement through Integrated Intelligent Water Drop Optimization with Neural Network for Maximum Power Point Tracking
A Digital Healthcare Monitoring System with Real-Time Analysis
Advancements in Smart Meter Design and Integration for Enhanced Energy Management and Efficiency
Electric Vehicles in Modern Transportation: Environmental Impacts, Configurations, and Future Trends – A Review
GTO Technique Based Hybrid Power System Controller Design
Design and Development Of Paddy Cutter Using Solar Energy
Design Of Double-Input DC-DC Converter (DIC) Solar PV-Battery Hybrid Power System
Comparison of Harmonics, THD and Temperature Analysis of 3-Phase Induction Motor with Normal Inverter Drive and 5-Level DCMI Drive
Application of Whale Optimization Algorithm for Distribution Feeder Reconfiguration
Detection and Classification of Single Line to Ground Boundary Faults in a 138 kV Six Phase Transmission Line using Hilbert Huang Transform
The Modeling of Analogue Systems through an Object-Oriented Design Method
Circuit Design Techniques for Electromagnetic Compliance
A Technological Forecast for Growth in Solid-State Commercial Lighting using LED Devices
Testing of Analogue Design Rules Using a Digital Interface
Simulation and Transient Analysis of PWM Inverter Fed Squirrel Cage Induction Motor Drives
This paper presents an optimized model that combines the Intelligent Water Drop (IWD) Optimization algorithm with a neural network (NN) for maximum power point tracking (MPPT) in PV applications. The novel approach and high performance of the present method are fully demonstrated as well as compared to conventional methods, which include Fuzzy Logic Control, Perturb & Observe (P&O), Particle swarm optimization (PS), Genetic algorithm(GA) and Incremental conductance (INC) control The enhanced model enhances adaptability and convergence because of the IWD algorithm's optimization characteristic, as well as takes advantage of NN's predictive characteristics for tracking with improved speed. The result suggests that this could serve as the breakthrough for future-generation PV system like solar energy applications.
In the contemporary landscape of healthcare, the demand for efficient and proactive monitoring solutions is paramount. Digital healthcare monitoring systems, leveraging cutting-edge technologies such as the Internet of Things (IoT), have emerged as transformative tools in revolutionizing health data collection, analysis and utilization. This paper presents a comprehensive overview of a Digital Healthcare Monitoring System with Real-Time Analysis, aimed at providing continuous, real-time monitoring of vital health parameters through a custom-built mobile application. The system integrates various sensors including the DHT11 for temperature and humidity, the MAX30102 for heart rate and SpO2 and the AD8232 for ECG monitoring, facilitated by the NodeMCU microcontroller. The collected data is processed and transmitted to a mobile application for visualization and analysis in real-time, enabling timely interventions and improved patient outcomes. Key objectives of the system include real-time monitoring, multi-sensor integration, remote accessibility, alerts and notifications, data analytics, user-friendly interface, scalability and interoperability. Through rigorous methodology encompassing hardware and software integration, testing, and calibration, the system ensures accuracy, reliability and user engagement. The project underscores the transformative potential of digital health technologies in fostering proactive and personalized healthcare, ultimately leading to better health outcomes and quality of life.
The integration of smart meters into contemporary energy infrastructure is paramount for optimizing energy utilization and efficiency. This paper delves into a comprehensive exploration of smart meter design and operation using microcontroller-based simulation through Proteus Professional software. Incorporating essential components such as OPAMP LM358, XOR Gate 74LS386, resistors, capacitors, diodes, transformers, and microcontrollers, the smart meter aims to precisely measure and monitor power consumption. Moreover, it envisions seamless integration with connectivity technologies like GPRS, Public Network, Corporate Network, and Global Gateway to facilitate real-time communication and data exchange. By fostering a symbiotic relationship between smart meters and the smart grid, this integration strives to elevate energy management practices, curtail wastage, and foster sustainability. The paper elucidates the conceptual framework, design principles, and potential benefits of this integration, thus setting the stage for future advancements in smart energy infrastructure. Notably, the proposed smart meter boasts the capability to measure various electrical parameters including Voltage, Current, Frequency, Energy, Phase Angle, Active power, Reactive power, making it pivotal for big data analysis, thereby underscoring its significance in contemporary energy management endeavours.
This article provides a concise history of road transport vehicles and then analyses the environmental problems caused by them. Many problems have arisen as a result of modern transportation, such as air pollution, global warming, and the exhaustion of fossil fuels. Key nations' present and future electric car needs are covered in the article. Following this, it explains several electric vehicle kinds with the use of well-organized graphics. After a brief introduction to hybrid cars and their concepts, this article will go over the several configurations of Hybrid Electric cars (HEVs), including series, parallel, series-parallel, torque-coupling, and speed-coupling systems, and how they work. The text provides an easy-to-understand explanation of the main points of electric cars. The article concludes by discussing possible future prospects for engineers and the electric vehicle industry.
In this paper a controller is designed for a hybrid power system using a soft computing technique, the power system consists of PV system, fuel cell, aqua electrolysers, diesel engine generator and a battery energy storage system and frequency of the system is controlled by proportional plus integral (PI) controller and proportional plus integral and derivative (PID) controller. A powerful optimization technique named as Gorilla Troops optimizer technique is used for optimization of controller gains of the proposed hybrid power system. The system responses with GTO optimization-based controllers are compared with the Particle swarm optimization technique. Finally, from the frequency responses GTO based controller is better to mitigate the frequency responses in the system.
