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23 articles for “hybrid power generation”
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Integration of Wind and Solar Energy with Fuzzy Logic Control MPPT for Grid-Connected Hybrid Renewable Power Generation
Abstract: The utilization of renewable energy sources, such as wind and solar energy, has gained significant attention due to their eco-friendly nature and sustainability. This research paper explores the mechanisms behind wind generation and its integration with solar power, focusing on the adoption of Fuzzy Logic Control (FLC) for Maximum Power Point Tracking (MPPT) in a grid-connected hybrid renewable energy system. The paper outlines the principles of wind and solar energy …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 1–19 Read article
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Efficient Energy Management and Utilization Using IoT Enabled Intelligent System
Abstract: Energy is essential for economic development, and the demand for electricity is rising at an extraordinary pace. Currently, fossil fuels remain the main source of global power generation, but these resources are limited and detrimental to the environment. Therefore, there is an urgent need to broaden energy sources and transition towards cleaner, sustainable, and renewable options. This paper examines the potential of multi-source power generation and usage as a viable …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 1, 2025 · pp. 38–45 Read article
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A Comprehensive Study of various Multi-Area Hybrid Power Systems for Generation Control
Abstract: This paper is a detailed examination of multi-area hybrid power systems in the control of the generation taking into consideration the two area up to five area connected networks. As renewable energy sources are more and more integrated, and modern grids become more and more complex, the stability of the system itself and the frequency regulation have risen to a major issue. The study highlights the significance of Automatic Generation …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 28–42 Read article
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Design and Simulation of Low Power Allow Area High Speed Carry Save Adder using CMOS 16 nm Technology.
Abstract: In this article, we propose a novel 1-bit hybrid full adder circuit that is implemented using eighteen transistors. Simulations are done using the Mentor Graphics Tool 16nm technologies. The performances are evaluated based on their speed, average power consumption, and power-delay product. The essential components of arithmetic units including compressors, comparators, parity checkers, etc. are full adders. Thus, raising the performance of the entire adder will raise the system's performance. …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 1, Issue 2, 2023 · pp. 17–28 Read article
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Low-Grade Heat Recovery: Emerging Materials and Systems for Efficient Utilization
Abstract: Low-grade heat (LGH), generally characterized by temperatures below 200°C, constitutes a significant portion of wasted thermal energy in industrial, commercial, and even residential processes. Despite its vast availability, the efficient recovery and utilization of LGH remains underdeveloped due to its inherently low exergy content and the limitations of traditional heat recovery technologies. The creation of cutting-edge materials and creative system-level approaches for LGH recovery has accelerated significantly as companies continue …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 1, 2025 · pp. 24–29 Read article
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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Development and implementation of Solar-Thermoelectric Hybrid Energy Harvester
Abstract: In today’s consumer-oriented and technology-driven market, researchers are increasingly emphasizing the need to harvest energy from ambient and renewable sources to support sustainable power generation and to minimize dependence on conventional energy resources such as batteries and fossil-fuel-based electricity. The rising deployment of portable electronics, wireless sensor networks, and Internet of Things (IoT) devices has created an urgent demand for compact, low-power, long-life, and maintenance-free energy solutions. In many real-world …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Thermodynamic Optimization and Exergy-Based Performance Analysis of Hybrid Thermal Management Systems for Electric Vehicles
Abstract: The transition toward sustainable transportation has brought electric vehicles (EVs) to the forefront of modern engineering innovation. Despite their environmental benefits and improved energy efficiency, EVs face major thermal challenges that affect performance, safety, and durability. Efficient thermal management of batteries, power electronics, and electric drive systems is vital to ensure reliability under diverse operating conditions. This study presents a detailed thermodynamic optimization and exergy-based performance analysis of hybrid thermal …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 19–23 Read article
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Solar Thermal Energy Utilization: Design Innovations and Performance Enhancement Techniques
Abstract: The utilization of solar thermal energy has become increasingly significant in the pursuit of sustainable and low-carbon energy solutions. Unlike photovoltaic technologies that directly convert sunlight into electricity, solar thermal systems focus on harnessing solar radiation to generate heat, which can then be applied to diverse sectors such as water heating, space conditioning, industrial process heating, and power generation. In recent years, substantial research efforts have been directed toward enhancing …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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A Review on Mechanical Behavior of Lithium Ion Batteries for Electric Vehicles
Abstract: The current automobile industries are much dependent on conventional petroleum fuels like petrol, diesel etc. which are creating many environmental issues due to combustion reactions and generation of carbon dioxide. This continues use of conventional fuels leads to either increasing the price of it and vanishing of its resources in future. Considering this pure battery based electric vehicle or electric vehicle with hybridize combination of battery and any other energy …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 1–20 Read article
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Photonic-Assisted Spintronic Solid-State Switching Model for High-Speed Memory Devices
Abstract: The rapid advancement of high-speed computing and data-centric applications has intensified the demand for energy-efficient and ultra-fast memory technologies. This paper proposes a Photonic-Assisted Spintronic Solid-State Switching Model for next-generation high-speed memory devices. The proposed framework integrates photonic excitation mechanisms with spintronic switching dynamics to enhance data transfer speed, minimize switching delay, and reduce power dissipation in solid-state memory architectures. By combining optical pulse-assisted spin polarization with magnetic tunnel junction-based …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Dielectric Elastomers in Actuation and Energy Applications: Material Behavior and Design Strategies
Abstract: Dielectric elastomers (DEs), a class of electroactive polymers, have attracted significant attention for their ability to undergo large, reversible deformations under electric stimulation. This unique capability makes them highly suitable for a range of actuation and energy harvesting applications, especially in the emerging fields of soft robotics, flexible electronics, artificial muscles, and sustainable power generation systems. DEs offer compelling advantages such as low weight, mechanical flexibility, high energy density, and …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 13–18 Read article
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A Review of Torque Ripple Reduction Techniques in Switched Reluctance Motors
Abstract: Switched Reluctance Motors (SRMs) have emerged as a promising alternative to conventional motor technologies due to their rugged structure, low manufacturing cost, high-temperature capability, and suitability for harsh environments. Despite these advantages, the widespread adoption of SRMs in applications such as electric vehicles, household appliances, industrial drives, and aerospace systems is significantly restricted by the issue of torque ripple. Torque ripple manifests as periodic fluctuations in the developed electromagnetic torque, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 45–50 Read article
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Intelligent Power Quality Enhancement Strategies for PV-Integrated Smart Distribution Networks: A State-of-the-Art Review
Abstract: The rapid integration of photovoltaic (PV) systems into modern power distribution networks has introduced significant challenges related to power quality. Issues such as voltage fluctuations, harmonic distortion, flicker, and reactive power imbalance arise due to the intermittent and nonlinear nature of solar energy generation. This paper presents a concise literature review of various power quality enhancement techniques employed in PV-integrated networks. Key approaches include the use of active power filters …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 30–53 Read article
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Hybrid Braking System: Electromagnetic + Disc Braking
Abstract: The Hybrid Braking System combines electromagnetic braking and traditional disc braking to enhance vehicle safety, improve braking response, and reduce mechanical wear. This system integrates sensor fusion technologies, including ultrasonic and infrared sensors, to enable adaptive braking based on real-time road conditions. A PID-based control algorithm optimizes braking force distribution, ensuring a smooth and controlled deceleration. Additionally, the incorporation of regenerative braking allows for energy recovery, increasing vehicle efficiency and …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 4, Issue 1, 2026 · pp. 8–14 Read article
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Radio in the Age of AI
Abstract: Artificial intelligence (AI) is changing the traditional world of radio broadcasting very quickly. It is changing the way material is made, curated, shared, and listened to. This article talks about how AI technologies like machine learning, natural language processing, and automated voice synthesis can be used in radio production and operations. It looks at how AI-powered solutions may make listening more personalised, give real-time audience statistics, automatically generate news, and …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Study of Finite State Machines as Language Recognizer
Abstract: Finite State Machines (FSMs) play a fundamental role in computer science and linguistics as language recognizers. This study presents an exploration of the principles and applications of FSMs as efficient tools for recognizing formal languages. The study delves into the theoretical foundations of FSMs and their practical implementation in various language recognition tasks. The fundamental ideas of FSMs, including as states, transitions, and input symbols, are introduced in this study. …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 18–24 Read article
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Machine Learning–Guided Cognitive RF System with Dynamic FFT Resolution and Multiplier Reconfiguration for Adaptive Anti-Jamming Communication
Abstract: This paper presents a hierarchical adaptive RF communication system that integrates signal quality-based pre- processing with machine learning-driven signal classification to achieve robust and resource-efficient operation in dynamic, interference-prone environments. Unlike prior art that addresses adaptive RF, ML classification, or anti-jamming individually, this work uniquely combines real-time SNR/RSSI-based signal strength estimation with dynamic FFT size selection (64-, 256- , or 512-point) and arithmetic-level multiplier reconfiguration (CORDIC, Distributed Arithmetic, and hybrid …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article