Enhanced Solar Energy Conversion for Direct Current Motor Speed Control
Design and Development of an Innovative Smart Meter for Real-Time Power Monitoring and Grid Optimization using Embedded Control and Sensor Integration
Development of a Hardware Model for Renewable Energy-Based DC Micro-Grid with Automatic Power Transmission using IoT
Smart Cities for a Green Future: Innovations and Challenges
Energy Efficiency through Communication: Innovations in Electronics 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 a comprehensive examination of speed regulation for a Separately Excited Direct Motor (SEDM). It effectively addresses the challenges posed by variations in irradiance of solar and set points. The array of photovoltaic (PV) efficiently converts solar energy into a stable direct current (DC) output voltage, which powers the motor. To improve performance in light of these variations, we utilize an advanced strategy of Maximum Power Point Tracking (MPPT) that incorporates a converter, thereby ensuring the system operates at peak efficiency consistently. Additionally, a PID controller is employed to manage fluctuations in the set point, which is integrated with a flexible buck-boost converter. The MPPT controller utilizes the Incremental Conductance (IC) algorithm to effectively sustain the system's operating point at its maximum power point. Our simulation studies illustrate the effectiveness of this proposed method, emphasizing its capability to proficiently handle both source-side and set-point variations.
The ever-evolving power grid demands advanced, intelligent metering solutions to enhance monitoring, efficiency, and real-time control. This paper presents the design and development of an innovative smart meter system that not only measures electrical parameters with precision but also facilitates intelligent decision-making using embedded control and sensor fusion techniques. The proposed system integrates an Arduino UNO R3, an ACS712-20A current sensor, a DHT11 humidity-temperature sensor, and signal conditioning components like OPAMP LM358 and XOR logic gates, ensuring both accuracy and adaptability. Input-side measurements record a voltage of 230 V, a current of 16.5 A, and a power factor of 0.98, while output-side data reflects 229.2 V, 15.74 A, and a power factor of 0.93, showcasing minimal losses and robust performance. Active and reactive power readings, along with real-time phase angle and frequency monitoring, further validate the model's applicability in smart grid systems. This cost-effective, modular smart meter prototype demonstrates excellent agreement between hardware and simulation results, proving its feasibility for deployment in both industrial and residential environments.
This paper explores the design, development, and testing of a hardware model for a renewable energy-based DC microgrid, which incorporates Internet of Things (IoT) technology for efficient power management. By integrating renewable energy sources such as solar and wind, combined with energy storage, power conversion, and real-time monitoring, the proposed microgrid ensures seamless and automated power distribution. Using an ESP32 microcontroller, the system dynamically manages loads and transmission based on energy availability. The IoT-enabled infrastructure facilitates remote control and monitoring, enabling scalable and sustainable solutions for energy management. Experimental results validate the system's high efficiency and feasibility in real-world applications, making it a promising candidate for future smart grids.
The rapid urbanization of the 21st century presents significant challenges, including environmental degradation, resource depletion, and increased carbon emissions. Smart cities, powered by advanced technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), and big data, offer transformative solutions to these challenges by seamlessly integrating sustainability and innovation. This paper explores the concept of green smart cities and highlights the key innovations driving their development, including smart energy systems, efficient transportation networks, advanced waste and water management, and urban planning solutions optimized for environmental sustainability. Case studies from leading smart cities demonstrate the tangible benefits of these innovations in reducing ecological footprints and improving quality of life. However, the journey toward green smart cities is fraught with challenges, including technological limitations, financial constraints, social resistance, and regulatory hurdles. This research emphasizes the importance of collaborative efforts, innovative public policies, and emerging technologies to address these challenges and foster sustainable urban development. By aligning technological advancements with environmental objectives, smart cities hold the potential to redefine urban living and ensure a greener, more resilient future for generations to come.
The rising energy demands of modern electronics, especially in IoT devices, wearables, and industrial systems, have made energy-efficient communication a critical design priority. This survey explores how communication processes contribute to overall power consumption and presents innovations that enable sustainable electronics. It reviews low- power protocols such as BLE, ZigBee, and LoRa, highlighting their application-specific advantages. Adaptive techniques like duty cycling, dynamic power scaling, and energy harvesting are examined for their role in minimizing idle and transmission energy. The paper also discusses hardware advancements, including energy-efficient transceivers, antennas, and system-on-chip designs. Through case studies, it demonstrates how these innovations improve battery life and reduce operational expenses across smart homes, portable electronics, and industrial IoT. Main challenges such as protocol compatibility, latency, and energy-performance trade-offs are addressed, along with future opportunities in AI- driven optimization and ultra-low-power 6G networks. This comprehensive analysis supports the development of intelligent, energy-aware communication systems for next-generation sustainable electronics.
