Revistas UTB ( Universidad Tecnológica de Bolívar)
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UniSchedApi: A comprehensive solution for university resource scheduling and methodology comparison
Full text linkThis paper introduces UniSchedApi, an API-based solution that revolutionizes optimized university resource scheduling. The primary focus of the research is the detailed evaluation of two automatic resource allocation methods: Tabu Search (TS) and Genetic Algorithm (GA). The paper thoroughly explores how these methods address challenges associated with resource allocation in university environments, considering critical factors such as teacher availability, student time constraints, classroom features (including computers, projectors, TV's, specialized laboratories, specialized equipment, etc.), among others. The evaluation is carried out meticulously, measuring the performance and memory resource usage of both algorithms, considering the comparison with the manual scheduling. The results reveal that the TS algorithm excels in terms of temporal efficiency and computational resource usage. Based on these findings, UniSchedApi implements GA and TS but uses TS as the default algorithm, ensuring more efficient and optimized management of academic resources. This research not only presents a practical solution with UniSchedApi but also provides a deep understanding of the methods for evaluating and selecting algorithms to address specific challenges in university resource allocation. These results lay the groundwork for future improvements in academic resource management
Optimization of combustion characteristics on a diesel engine fueled by Mahua biodiesel with dispersion of graphene oxide and zinc oxide nanoparticles as additives using design of experiment
Full text linkThe current research investigates the effects of adding metallic graphene oxide (GO) and non-metallic zinc oxide (ZnO) nanoparticles to Mahua biodiesel blend (B20) on the combustion parameters of a diesel engine. GO and ZnO nanoparticles were utilized at a concentration of 75 mg/L, combined with a 1:1 mixture of the surfactant CTAB and the dispersant TWEEN 80. When nanoparticles were introduced to blended biofuel, combustion parameters such as cumulative heart rate, mean gas temperature, mass percent burnt, and rise of pressure increase (RoPR) greatly improved at higher injection pressures. When compared to clean diesel, utilizing B20+ZnO Nanoparticles+ NIS dispersant at 250 bar resulted in 6%, 15%, 7%, and 7.6% improvements in CHRR, MGT, MFB, and RoPR, respectively. The correlation coefficient (R2) for B20+ZnO NPs+ NIS (1:1) for CHRR, MGT, MFB and RoPR is 0.975, 0.978, 0.966 and 0.9883 when compared to GO nanoparticle inclusions, considering it as optimum combination and an efficient fuel. When compared to other fuel samples, the CHRR, MGT, MFB and RoPR for B20+ZnO NPs+ NIS are 2.484%, 3.2%, 2.6% and 1.25% higher, respectively, according to a statistical analysis conducted by design expert
Classification of opening/closing hand motor imagery induced by left and right robotic gloves through EEG signals
Full text linkThis study presents a novel strategy for classifying Motor Imagery (MI) related to hand opening/closing actions using electroencephalography signals. This approach combines the passive motion induced by a robotic glove and action observation. Two groups of subjects executed a protocol based on left and right hand movement MI to address this. Subsequently, spectral features were used on and bands, and machine-learning algorithms were used for classification. The results showed better performance for right-hand motion recognition using k-Nearest Neighbors (kNN), which achieved the highest performance metrics of 0.71, 0.76, and 0.28 for Accuracy (ACC), true positive rate, and false positive rate, respectively. These findings demonstrate the feasibility of the proposed methodology for improving the recognition of MI tasks of the same limb, which can contribute to the design of more robust brain-computer interfaces for the enhancement of rehabilitation therapy for post-stroke patients
Multi-objective grounding system optimisation using NSGA-II
Full text linkThis study investigates the optimisation of grounding infrastructure in substations by implementing the philosophy of the multi-objective algorithm NSGA-II Elite. A complete description of the operating scheme and the characteristic mechanisms that support the behaviour and development of optimal Pareto solutions is provided. A detailed comparison was made with the optimisation method used in the GMAT program of Aplicaciones Tecnológicas, based on a semi-optimization process derived from the correlation of semi-precision optimisation solutions. The results show that multi-objective optimisation using NSGA-II results in a significant cost reduction compared to the semi-optimization method, although the computational time required to reach the final solution increases significantly. This approach allows a more adequate understanding of optimising the terrestrial substation grid. It highlights its ability to generate more cost-effective and performance-efficient solutions by carefully considering the computing time required
Performance improvement of PV systems during dynamic partial shading conditions using optimization algorithms
Full text linkPV power plants encounter varying levels of irradiance, temperature fluctuations, and partial shading because of the differences in sunlight conditions. Partial shading can cause an increase in the power loss, leading to a reduction in efficiency. Maximum Power Point Tracking (MPPT) is of utmost importance in the functioning of photovoltaic (PV) systems for electricity generation because it is indispensable for maximizing power extraction from PV modules, thereby increasing the overall power output. In situations where partial shading is present, the utilization of MPPT algorithms to achieve maximum power output becomes complex because of the existence of multiple distinct peak power points, each having a unique local optimum. To overcome this issue, a method is proposed that uses Darts Game Optimization (DGO), a game-based optimization process, to efficiently determine and extract the maximum power from various local optimal peaks. A population-based optimization method known as the Darts Game Optimization algorithm exists. In this approach, the optimization process begins by creating a population of random players. Then, the algorithm iteratively updates and improves the population to search for the best player or solution. In this study, the DGO algorithm was applied to the MPPT process for voltage optimization in the PV procedure. The DC-DC converter is utilized to capture the maximum available power, and the findings demonstrate that the DGO algorithm efficiently identifies the global maximum, resulting in accelerated convergence, reduced settling time, and minimized power oscillation. Through simulations, the feasibility and effectiveness of the DGO centered MPPT approach was confirmed and compared with MPPT algorithms relying on perturb and observe (P&O) and Particle Swarm Optimization (PSO). The simulation results offer compelling evidence that the DGO algorithm, as proposed in this study, proficiently traces the global maximum, thereby substantiating its practicality and efficiency
Economic scheduling and dispatching of distributed generators considering uncertainties in modified 33-bus and modified 69-bus system under different microgrid regions
Full text linkThis paper presents a comprehensive framework for the economic scheduling and dispatching of Distributed Generators (DGs) in modified 33-bus and 69-bus systems across multi-microgrid regions. The framework introduces two key techniques: a novel dispatch strategy for optimizing the charging and discharging of Electric Vehicle (EV) batteries, and a robust power dispatch method for islanded distribution systems. The EV dispatch strategy uses a multi-criteria decision analysis method, Probabilistic Elimination and Choice Expressing Reality (p-ELECTRE), to maximize profits for EV owners while meeting power system requirements. This strategy is tested on fleets of 100 and 200 EVs with random travel plans within the modified 33-bus and 69-bus systems, and employs the BAT Optimization Algorithm (BOA) for optimal power dispatch. The second technique addresses the power dispatch in islanded systems by sectionalizing them into self-supplied microgrids, aiming to minimize operational costs, system losses, and voltage deviation using the Jaya algorithm. Additionally, a multi-objective cost-effective emission dispatch is evaluated using Whale Optimization Algorithm (WOA), showing superior performance over Differential Evolution (DE), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO). Comparative analysis highlights the scalability and adaptability of the proposed approach, making it a valuable tool for efficient microgrid management. Simulation results confirm significant improvements in cost savings, system reliability, and operational efficiency under various uncertainty scenarios
A Computer vision based system for human detection and automatic people counting
Full text linkOccupancy control is a fundamental aspect of managing spaces and services effectively. It aims to ensure safety, compliance with regulations, emergency preparedness, and overall satisfaction for individuals and businesses. To align with the described need, this paper presents a computer vision based system for automatic people counting in gates. The system is divided in five stages: video capture, motion analysis, human detection, human tracking and people counting. An RGB camera captures the top-view image of the gate and analyze the change or movement in the objects in scene. When motion is detected, the frame is sent to the object detector, which is a convolutional neural network. Then, a tracking algorithm analyzes the movement patterns of people. According to the route, it is determined whether the person arrives or leaves and the count is updated. Two test scenarios are analyzed: the entry of a public bus and a building gate. The people detection module is tested, showing a mAP of 95.2% and a mean IoU (50%) of 55.9%. Also, the counting is tested showing an average precision of 96.8%, a recall of 92% and an F1-Score of 94.3%. Finally, the system performance is evaluated, showing an average processing time of 34.2 ms and 29.2 FPS
Impact of high blends of Madhuca Logifolia biodiesel on the performance, combustion and emission parameters in a CRDI diesel engine at variable compression ratio
Full text linkThe country today uses a variety of industrial and transportation facilities that are fueled by diesel fuel. However, because of its non-sustainable and polluting nature, there is an urgent need for a more environmentally acceptable substitute that can be utilized in existing engines with no or little modification. Madhucalongifolia (Mahua) was considered a main source for biodiesel production based on its availability and its nature to not impact the food chain. The raw oil was converted to biodiesel using the process of transesterification. The higher blends of B80 (80% mahua biodiesel, 20% diesel by vol.) and B90 (90% mahua biodiesel, 10% diesel by vol.) were prepared. The experiment was carried out using an eddy current dynamometer and involved a Kirloskar 4-stroke single-cylinder which was water-cooled, CRDI diesel engine. The base run was generated using 18:1 compression ratio diesel fuel. These outcomes were contrasted with identical engine conditions using blends of B80 and B90 biodiesel as fuel. The most favourable results in terms of the engine parameters ie. BTE, SFC, cylinder pressure, HC, NOx and CO were as stated here. There was an increase of 8.87% in BTE for the B90 blend. A minor increase of 2.77% in SFC was observed with the B90 blend. The cylinder pressure for B90 was decreased by 0.024%. The emissions for B80 and diesel were lesser in comparison to B90. Diesel showed the lowest CO (7.9%) emissions whereas HC and NOx for B80 decreased by 24.39% and 3.42% respectively. The engine was made to run at two lower compression ratios of 16 and 17. When using a fuel blend of B80 at a compression ratio of 16, the performance metrics were significantly better. It could be concluded that, the compatible results were found with B80 biodiesel blend with compression ratio of 16. The BTE, SFC, cylinder pressure, HC, NOx and CO were quantified as 25.61%, 0.34kg/kWh, 30.27 bar, 50ppm, 1204 ppm and 0.24% by volume respectively. In comparison to the base run (diesel fuel and compression ratio of 18), there was 15.98% increase in the BTE, 5.55% decrease in the SFC, 16.07% decrease in the cylinder pressure, 21.95% decrease in the emission of HC, 23.55% decrease in NOx and 9.09% increase in CO emissions
Pioneering Renewable Energy Solutions: Insights from ICARGET 2023
Full text linkArjunan et al., Guest Editors, proudly present the selected papers from ICARGET 2023, showcasing cutting-edge advancements and diverse perspectives in this special issue of the Transactions on Energy Systems and Engineering Applications (TESEA). This collection covers a broad array of topics including solar, wind, bioenergy, and energy storage solutions, each offering significant insights, methodologies, and practical applications. The research underscores the critical need for sustainable energy solutions, interdisciplinary collaboration, and the socio-economic and environmental impacts of renewable energy deployment. The editorial team extends sincere gratitude to TESEA, the authors, reviewers, and readers for their invaluable contributions to advancing renewable and green energy technologies
Design of PV fed single-switch transformer less topology powered electric vehicle
Full text linkAs a result of an increase in the availability of resources that were not harmful to the environment, solar energy applications shot to popularity. Photovoltaic cells power systems that necessitate DC-DC converters because of their low voltage output. This investigation uses photovoltaic cells (PV) to power a high-voltage gain design with just one switch and no transformer. The proposed circuit utilizes a single regulated switch, which contributes to a reduction in switching losses. It requires fundamental pulse regulation. The network used a switched capacitor cell and an LC passive filter to provide an accurate step-up voltage. We can obtain the equation for the step-up voltage gain from the steady-state continuous conduction mode. The equations used for the theoretical design of converters include energy. To show that the topology is comparable with other modern converters that have been published, a comparison was made between it and other converters. In order to validate the converter's effectiveness, simulations built in MATLAB and Simulink are used