International Journal of Applied Power Engineering (IJAPE)
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Improve the thermal performance of the combined water-paraffin hot storage tank in the absorption cooling cycle
Get PDFThis research investigates the thermal performance of storage materials in a hot tank designed to extend the operation time of a 1.5-ton water ammonia absorption cooling system. Thermal energy is supplied by concentric parabolic solar collectors, which heat the absorption cycle generator during periods of sufficient solar radiation. When the water temperature exceeds the system’s operating threshold, the additional heat accumulates in the hot tank. It is later used to drive the generator during periods of low solar availability, such as in the afternoon or after sunset. The system is designed to provide air conditioning for a room; its load was calculated hourly. The suitable size of the storage tank and the corresponding collector area were determined based on simulations of the absorption system to achieve an optimal coefficient of performance (COP). The collector area was increased after the addition of paraffin phase change material (PCM) to enhance system performance, and a temperature control strategy was implemented to prevent the water in the hot storage tank from reaching the boiling point. This was achieved by incorporating a specific percentage of paraffin, a PCM, with a melting point of 85 °C. The size of the hot storage tank containing both water and a specified proportion of paraffin, in addition to the solar collector area, was optimized to maximize the tank temperature. These parameters were entered into the energy balance model as input data to ensure the effective operation of the absorption system under optimal conditions. A comprehensive system simulation was conducted by deriving and simplifying the heat balance equations for the hybrid hot storage tank, the solar collector, and the absorption system. The simulation aimed to identify the optimal wax ratio of 5% to 20% to maximize system performance. The optimal paraffin ratio was found to be 10% of the tank volume, which enabled an additional 4 hours of operation and extended the system’s uptime to its maximum potential
Design and implementation of solar-grid based charging station for electric vehicle with fault detection method using R-Pi and IoT processor
Get PDFIn this research describes the electrical vehicle (EV) charging station using PV panel with fault detection methods. The PV modules will failure for some time, because of some external factors and internal factors. In direct fault condition the monitor and analyze the external factors such as the life span, high intensity and breakage of the PV panels using Raspberry Pi (R-Pi) processor with internet of things (IoT) system. In power demand/day on the PV panel will be evaluated and analyzed through R-Pi processor and IoT. The efficiency and the range values of the PV panels will be monitored and analyzed through IoT. Proposed work explains, how the fault detection techniques have been improved and adopted in using R-Pi processor through IoT platform. The proposed dataset pre-processing system is incorporated with IoT module. The grid fault clearing time will be compared with the actual values through R-Pi processor. The PV panel faults are detected using thermal image processing, that image parameter values analysis through IoT based internal monitoring system
A hybrid framework of IoT and machine learning for predictive analytics of a DC motor
Get PDFMany industrial applications utilize direct current (DC) motor as an essential element. It functions as the backbone of several industries and global pillar of manufacturing applications. The predictive analytics of motor is primary for preventing unpredicted downtime, reducing protection costs, and improving system effectiveness. This paper presents a hybrid framework integrating the internet of things (IoT) and machine learning (ML) for real-time predictive analytics of DC motors. The leveraging of machine learning algorithms in predictive maintenance of DC motors has shown significant potential in reducing downtime and increasing the lifespan of the motor. Therefore, a system for predictive analytics with machine learning strategy is proposed and message queuing telemetry transport (MQTT messaging) is included for effective information transmission between sensors and gateways. The data received from the sensors is utilized to make prediction about the remaining useful life of the motor and generate alerts for maintenance before failures occur. So, the integration of machine learning algorithms in predictive maintenance of DC motors is a promising approach to increase the reliability and efficiency of DC motors. The highest performance is achieved in random forest with accuracy of 93.4%
Power quality enhancement for a grid connected wind turbine energy system with PMSG
Get PDFThis project investigates the burgeoning potential of gearless wind turbine systems as a pivotal clean energy resource. Unlike conventional gearbox-based turbines, which grapple with issues like frequent breakdowns, intricate repairs, and prolonged downtimes, gearless systems present a suite of advantages. Chief among these is heightened reliability, diminished maintenance costs, and augmented efficiency. By circumventing the need for a gearbox, gearless turbines shed weight, bolster reliability, and demand less upkeep. The incorporation of permanent magnet generators further elevates their efficiency and renders them well-suited for offshore deployment. The emergence of gearless wind turbines heralds a promising frontier for effectively and efficiently harnessing wind power. Their streamlined design and robust performance potential position them as a transformative force in the renewable energy landscape, poised to catalyze substantial advancements towards sustainable energy goals. As research delves deeper into their capabilities and optimization, gearless turbines are poised to emerge as a cornerstone technology in the global pursuit of clean energy solutions
Integral backstepping control design for enhanced stability and dynamic performance of VSC-HVDC systems
Get PDFThe increasing demand for efficient and reliable high-voltage direct current (HVDC) transmission systems has underscored the necessity for advanced control strategies to augment system performance. This article presents the design and implementation of an integral backstepping control approach customized for voltage source converter (VSC)-based HVDC systems. The proposed methodology primarily concentrates on tackling the inherent nonlinearities, uncertainties, and disturbances that typically impede the stability and efficiency of VSC-HVDC systems. By incorporating integral action into the backstepping control framework, two key objectives are accomplished: i) precise regulation of the direct voltage at the rectifier station and accurate control of the active power at the inverter station, and ii) effective power factor correction (PFC) at both stations within the HVDC system. These objectives contribute to robust tracking performance, enhanced dynamic stability, and improved overall system efficiency. The theoretical design has been verified through extensive numerical simulations conducted in the MATLAB/Simulink environment, showcasing the efficacy of the proposed control strategy in ensuring stability and performance under varying conditions
Effect on saturated and unsaturated fatty acids on various vegetable oils on droplet combustion characteristic
Get PDFVegetable oils have composed of triglycerides, which one consist of 3 fatty acids combined with glycerol. Each saturated and unsaturated fatty acid has a different effect on burning characteristics. This study aimed to investigated effect of fatty acids at ceiba pentandra and jatropha oils on the flame behavior of the droplet combustion process. The combustion characteristic was observed by an ignited droplet at the junction using a thermocouple and a high-speed camera (120 fps). Results showed that a higher saturated fatty acid content resulted in long-life and steady flames. This is because more oleic and linoleic acid carbon atoms leave the droplet area and react with air. Jatropha oil produces a higher temperature of 780 °C than ceiba pentandra oil. Temperature of a vegetable oils flame is influenced by number of carbon chains, double bond, and heating value. Ceiba pentandra oil has a higher burning rate of 0.185 mm/s than jatropha oil at 0.155 mm/s. The chain content of polyunsaturated fatty acids has significant effect on rate of combustion, which is due to the weak van der Waals dispersion forces, such that heat absorption is more active and energetic. The highest flame height for ceiba pentandra oil is 55.03 mm compared to for jatropha oil it is 46.82 mm. Long-chain unsaturated double bonds and glycerol cause micro-explosions. This micro-explosion caused the shape of the flame to split and expand so that evaporation occurred faster, thus increasing the size of the flame
Gated dilated causal convolution-based encoder-decoder network for IoT intrusion detection
Get PDFThe internet of things (IoT) is perhaps the greatest modern development, as it affects our daily lives and is rapidly expanding in its application zones. The IoT is used in everyday activities, so security is more crucial because intrusion detection will introduce and eliminate attacks. In this paper, a novel deep learning based intrusion detection technique (DEBIT) has been proposed that detects the intrusion using deep learning techniques efficiently. Initially, the data from IoT user is preprocessed and classified using the novel gated dilated casual convolution based encoder-decoder (GDCC-ED) method, which classifies the data into attack and non-attack. The proposed DEBIT framework has been assessed using a MATLAB simulator. The performance of the proposed DEBIT framework has been assessed based on specific parameters, including recall, detection rate, accuracy, F1 score, and precision. Based on experimental results, the suggested method is 99.5% more accurate than pigeon-inspired optimization (PIO), Res-TranBiLSTM, and blockchain-based African buffalo (BbAB), which are 85.4%, 92.5%, and 85%, respectively
Performance analysis of seven level multilevel inverter for power quality improvement
Get PDFPower conversion systems for demanding applications requiring high power and power quality are increasingly using multi-level converters. Due to its many advantages, such as low harmonic content, low electromagnetic interference (EMI) output, and low power consumption in power switches, the multilayer inverter (MLI) topology is more commonly used in medium and high power applications. The chosen switching technique of the inverter for operation significantly contributes to the suppression of harmonic components while creating the optimal output voltage. A single-phase 7-level cascaded H-bridge multilevel inverter (CHB-MLI) with fewer switches and alternative control algorithms is available in MATLAB-based simulation on the SIMULINK platform. In this research, the total harmonic distortion (THD) of several control techniques is compared. From the simulation results, it was found that the proposed artificial neural network (ANN) controller outperforms the proportional-integral (PI) controller. With a lower THD value and a comparatively better sinusoidal waveform, the ANN controller produces an output voltage. It is also more suitable for improving the quality of electricity. The efficiency and performance of the proposed 7-level CHBMI system are demonstrated by the improved sinusoidal output waveform and reduced output voltage THD
Organic solar cells: a study on material selection and fabrication precision
Get PDFThe accelerating development of renewable energy technologies is imperative for addressing the problems of climate change and resource depletion. Solar energy, ideal for distributed power generation and more environmentally friendly, is integral to the progression of solar technology. Organic solar cells (OSCs) have become a key innovation in this domain, offering a promising alternative to traditional solar technologies. OSCs have received a lot of interest in the preceding years owing to their capacity to increase efficiency, affordability, and longevity. However, a dearth of research and development activities aimed at improving organic photovoltaic systems exists. This work details the laborious process of building a Bulk heterojunction (BHJ) OSC, describing the manufacturing stages and subsequent device characterization. OSCs were created in this work using three active layer materials: P3HT:PCBM, PTB7:PCBM, and PCDTBT:PCBM. The comparative analysis revealed significant efficiency disparities, with PCDTBT:PCBM exhibiting superior performance and electrical properties, while challenges were encountered with aged materials, emphasizing the relevance of meticulous material handling and the use of cutting-edge fabrication machinery in achieving efficient solar cell production
Optimal control of the UPFC for the stability of electrical networks
Get PDFThe unified power flow controller (UPFC) is a crucial element in contemporary power systems, specifically engineered to augment the manageability and adaptability of power transmission in electrical networks. UPFC provides instantaneous modifications to voltage magnitude, phase angle, and line impedance by using sophisticated power electronics and control algorithms. This research examines the function of the unified power flow controller (UPFC) in enhancing the power quality of electrical networks. The UPFC's capacity to dynamically regulate and optimize power flow assists in minimizing voltage fluctuations, decreasing transmission line losses, and improving system stability. In addition, UPFC effectively addresses problems such as voltage sags, swells, and flickers, hence enhancing the resilience and dependability of the power supply. This research highlights the importance of unified power flow control (UPFC) technology in improving system performance and power quality of electrical networks via a thorough examination of its applications. This article presents research on the performance of the unified power flow controller (UPFC) device in a network, specifically focusing on the use of PID and FO-PID controllers for regulating active and passive power