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Convolutional Neural Network for Microhydro Power Forecasting

Convolutional Neural Network for Microhydro Power Forecastin...

引用

2024 International Conference on Sustainable Energy: Energy Transition and Net-Zero Climate Future, ICUE 2024

作者： Aprillia, Happy Utami, Amalia Rizqi Salam, Anjas Nur Jaya Marindra, Adi Mahmud Saputra, Riza Hadi Institut Teknologi Kalimantan Electrical Engineering Study Program Industrial Technology & Process Department Balikpapan Indonesia

ISBN: (纸本)9798331517076

The demand for electrical energy is always fluctuating, influenced by several factors such as household, industrial, commercial, and other public service electricity usage. Moreover, estimates of future electricity demand play a crucial role in the operation of the power system, ranging from power generation planning to power flow analysis and energy system operation costs. electrical power forecasting aims to prevent sudden decreases or increases in electricity demand. Moreover, in tropical countries, the wet season and rivers offer many opportunities for micro-hydro potentials that can be harnessed in combination with solar energy. To manage the forecasting modeling, Convolutional Neural Network (CNN) is utilized CNN for short-term forecasting in Microhydro Power Plants. The anticipated outcomes aim to contribute to effective electricity demand management, facilitating the estimates of variation in microhydro power generation. © 2024 IEEE.

关键词： Demand response

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Design and Development of Electric Motor Torque Meter Using Microcontroller 5

Design and Development of Electric Motor Torque Meter Using ...

引用

5th Research, Invention, and Innovation Congress: Innovative electricals and Electronics, RI2C 2024

作者： Meesuk, Peerawat Nak-Udom, Natthaphong Phimyotha, Kittiphong Bansomdejchaopraya Rajabhat University Program of Electrical Engineering and Automation Control System Faculty of Engineering and Industrial Technology Bangkok10600 Thailand Bansomdejchaopraya Rajabhat University Program of Electromechanic Manufacturing Engineering Faculty of Engineering and Industrial Technology Bangkok10600 Thailand

ISBN: (纸本)9798331505998

This article presents the development of electric motor torque meter using microcontroller together with dynamometer process and application of light process to find out revolutions per minute (RPM) which torque is a variable that affects the effectiveness of electrical machine. A torque meter is, therefore, a tool that has an important role to work with mechanical part. The torque meter and RPM was tested and found that there is an error of torque measure at 13.74 percent and found that the torque has higher errors when it exceeds 2 N-m and there is an error of RPM at 5.36 percent. © 2024 IEEE.

关键词： Torque meters

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The study of Materials for Electric Field Protection of Power Transformer Testing 9

The Study of Materials for Electric Field Protection of Powe...

引用

9th International Conference on engineering, Applied Sciences, and Technology, ICEAST 2023

作者： Meesuk, Peerawat Bunpakdee, Prajak Sorn-In, Sirirat Bansomdejchaopraya Rajabhat Univrtsity Electrical Engineering and Automation Control System Program Faculty of Engineering and Industrial Technology Bangkok Thailand

ISBN: (纸本)9798350322040

This paper proposes the analysis of the material can be protected from transformer testing and presents a mathematical model of the power transformer. In this research, transformers were study in four protective materials, wood, rubber, glass and acrylic that are used in between the electric field measurement and the transformer. By simulating the test results of a transformer with a voltage of 230 kV. Computer-based simulation utilizing the finite element method (FEM) is exploited as a tool for visualizing electric fields distribution volume a power transformer. The simulation results showed that the material with the best protection against the electric field was wood insulation and the best installation location was a distance of 5 m from the transformer. © 2023 IEEE.

关键词： Finite element method

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Exploring Bess Services for Transformer Energization on Offshore Oil and Gas Platforms

Exploring Bess Services for Transformer Energization on Offs...

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2024 IEEE Petroleum and Chemical Industry Conference Brasil, PCIC Brasil 2024

作者： Banda, Joseph K. Araujo, Lucas S. Brandao, Danilo I. Marafao, Fernando P. Tedeschi, Elisabetta Department of Electric Power Engineering Trondheim Norway Graduate Program in Electrical Engineering Belo Horizonte Brazil Department of Control and Automation Engineering Sorocaba Brazil University of Trento Department of Industrial Engineering Trento Italy

ISBN: (纸本)9798350368154

The electrification of offshore oil and gas platforms (OOGPs), using offshore wind turbines, is now a reality, aimed at minimizing carbon emissions. In this scenario, the utilization of battery energy storage systems (BESS) improves both efficiency and power quality. As this integration comes with a high CAPEX, industries demand exploring BESS for multiple ancillary services on OOGPs. Thus, this paper proposes an alternative approach to energizing a power transformer (PT) using the BESS power conversion system (PCS) on the platform, aiming to minimize inrush currents. This avoids the necessity for additional bulky devices, converters, or dc voltage sources specifically designated for this purpose. The strategy consists of manipulating residual core flux using BESS PCS followed by a controlled switching, which reduces inrush currents during PT energization. The results show effective reduction of the inrush current from 2.31 pu to 0.16 pu for the presented case study. © 2024 IEEE.

关键词： Power transformers

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Human Following Robot Based on Object Detection for Aerospace Application 1

Human Following Robot Based on Object Detection for Aerospac...

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1st International Conference of Adisutjipto on Aerospace electrical engineering and Informatics, ICAAEEI 2024

作者： Sumari, Arwin Datumava Wahvudi Aryandika, Ahnaf Bagus Purnami, Ndaru Atmi Dermawan, Denny Syamsiana, Ika Noer State Polytechnic of Malang Cognitive Artificial Intelligence Research Group Department of Electrical Engineering Malang Indonesia Adisutjipto Institute of Aerospace Technology Electrical Engineering Study Program Yogyakarta Indonesia Adisutjipto Institute of Aerospace Technology Aerospace Navigation Instrumentation Control Automation and Robotics System Research Group Electrical Engineering Study Program Yogyakarta Indonesia Adisutjipto Institute of Aerospace Technology Electrical Engineering Study Program Aerosp. Digit. Syst. Microprocessor Microcontroller and Programmable Logic Devices Research Group Yogyakarta Indonesia

ISBN: (纸本)9798331507930

In this research, the Human Following Robot (HFR) prototype has been designed and implemented using YOLO v3-Tiny and Tensor Flow Lite on Raspberry Pi hardware named Rewang. The HFR Rewang is designed to assist aircraft technicians by bringing maintenance tool kits to aircraft shelters. Rewang's movement is based on a camera as a vision sensor following the movement of human entities. Image input is processed by YOLO v3-Tiny through the determination of the bounding box, the calculation of Euclidean Distance, and the determination of the pixel value of the camera as the basis of Rewang's movement which is regulated by an L298N driver motor that controls two Direct Current (DC) motors for the left and right wheels. The test results show that Rewang can move at an average speed of 0.18 m/s at 2 m with a travel time of 11 seconds with a light intensity of more than 250 lux. The minimum and maximum distance of object detection is as far as 120 cm and 400 cm, with an object detection accuracy of 95.8%. Rewang allows the HFR to have a larger carrying capacity to bring more complete aircraft maintenance tools and is prospective for other aerospace and general applications. © 2024 IEEE.

关键词： Travel time

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Enhancing Industry's Role in Vocational Education: An Analysis of Challenges and Opportunities Based on a Literature Review

Enhancing Industry's Role in Vocational Education: An Analys...

引用

STEM Education Conference (iSTEM-Ed), International

作者： Maman Somantri Resa Pramudita Electrical Engineering Education Study Program Universitas Pendidikan Indonesia Bandung Indonesia Industrial Automation and Robotic Engineering Education Study Program Universitas Pendidikan Indonesia Bandung Indonesia

ISBN: (数字)9798350365979

ISBN: (纸本)9798350365986

Enhancing industry engagement in vocational education is a crucial strategy for refining the quality of graduates to meet the continuously evolving job market needs. This article conducts a systematic review of the existing literature to identify the challenges and opportunities in industry involvement in vocational education. Through in-depth analysis of various sources, the article reveals that the skill gap between the vocational education curriculum and industry needs remains a significant issue. This challenge is exacerbated by assessment and certification systems that often do not accurately reflect the actual competencies required by the industry. Furthermore, the article explores opportunities through internship and work placement programs that enable students to gain relevant experience, as well as strategic partnerships between educational institutions and industries to develop responsive curricula. The article also recommends enhancing the synergy between vocational education and industry through policies that support this integration, which will not only improve the quality of vocational education but also expand employment opportunities for graduates. This research indicates that more integrated and sustained cooperation between vocational education and the industrial sector is key to ensuring the relevance of education with the dynamics of the global job market.

关键词： Industries Systematics Bibliographies Education Refining Employment Globalization

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Optimizing Methylammonium Tin Iodide-based Perovskite Solar Cells with Different Hole Transport Materials

Optimizing Methylammonium Tin Iodide-based Perovskite Solar ...

引用

IEEE International Conference on Semiconductor Electronics (ICSE)

作者： Budi Mulyanti Jahril Nur Fauzan Chandra Wulandari Lilik Hasanah Roer Eka Pawinanto Study Program of Electrical Engineering Universitas Pendidikan Indonesia Bandung Indonesia Study Program of Electrical Engineering Education Universitas Pendidikan Indonesia Bandung Indonesia Study Program of Physics Institut Teknologi Bandung Bandung Indonesia Study Program of Physics Universitas Pendidikan Indonesia Bandung Indonesia Study Program of Industrial Automation and Robotics Engineering Education Universitas Pendidikan Indonesia Bandung Indonesia

ISBN: (数字)9798350378313

ISBN: (纸本)9798350378320

Perovskite materials have garnered significant attention in the field of solar cell applications due to their highly promising performance. However, the utilization of lead (Pb) as the primary material in perovskite solar cells has been associated to health and environmental hazards. Consequently an alternative material for lead is necessary in order to develop environmentally friendly and high-efficiency solar cells. The reported efficiency value still necessitates further enhancement, indicating that the development of lead-free solar cells requires improvement. Methylammonium tin iodide (MaSnI 3 ), a lead-free perovskite compound, can be utilized as a substitute for lead halide-based solar cells. This substitution is possible since MaSnI 3 is stable, non-toxic, and has a high efficiency. The simulation was conducted by the Solar Cell Capacitance Simulator (SCAPS-1D), employing the AM 1.5G spectrum. The primary objective of this research is to enhance the performance of the hole transport layer materials in order to achieve a high power conversion efficiency (PCE) using MaSnI 3 material. Organic and inorganic HTL such as CuSBS, PEDOT:PSS+WO 3 , Spiro-OMeTAD, P3HT, NiO, Cul, SrCu 2 O 2 and PTAA are required in our simulations. These materials were selected to explore their potential in optimizing device performance due to their distinct properties, such as conductivity, stability, and compatibility with MaSnI3. Regarding HTM performance for device construction, our modelling results indicate that the 100 nm CuSBS 2 layer works better. We have found that by using the configuration of ITO/TIO 2 /MASnI 3 /CuSBS 2 /Au, a PCE of 27.67% with a Voc of 0.97 V can be achieved.

关键词： Performance evaluation Semiconductor device modeling Photovoltaic cells Lead Tin Perovskites Stability analysis

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Real-Time Hand Gesture Recognition for Humanoid Robot Control Using Python CVZone 7th

Real-Time Hand Gesture Recognition for Humanoid Robot Contro...

引用

7th International Conference on Smart City Applications, SCA 2022

作者： Baihaqi, Muhammad Yeza Vincent Simatupang, Joni Welman Graduate Institute of Automation and Control College of Engineering National Taiwan University of Science and Technology Taipei Taiwan School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Study Program of Electrical Engineering President University Bekasi Indonesia

ISBN: (纸本)9783031268519

Humanoid robot is able to mimic repetitive activities done by human. By having them, humans can focus on tasks that require extra focus, while leaving the simple one to be done by humanoid robot. To extend the functionality of the 3D-printed upper-body humanoid robot, a camera along with a machine learning algorithm is implemented. In this case, their responses can be categorized based on the gesture it sees. In this paper, the authors evaluate the performance of an upper-body humanoid robot that implements CVZone. The method of evaluation is conducted under three different distances, and each distance has three different brightness levels. It is found that the success rate is highest at the shortest distance which is 50 cm, and under medium-lighted environment. As the distance increases, the hand gesture gets harder to differentiate. At the same time, low or high brightness environment makes the image that contain hand gesture hard to interpret, thus lowering the success rate. Finally, hand gesture that involves third and little finger has the lowest success rate of 75%, while the movement that involves three fingers simultaneously has the second lowest success rate of 80.9%. Meanwhile, simple hand gesture such as clenched-fist or lifting a thumb has 100% success rate under all condition. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Anthropomorphic robots

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Optimizing Indoor Vertical Farming with DDPG Reinforcement Learning: Enhancing Control of Nutrient Levels, Climate Conditions, and Plant Health 5

Optimizing Indoor Vertical Farming with DDPG Reinforcement L...

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5th IEEE International Conference on Technology, Informatics, Management, engineering and Environment, TIME-E 2024

作者： Albert Panggabean, Good Fried Romadhon, Rahmat Lubis, Ramot Joelianto, Endra Institut Teknologi Bandung Doctoral Program in Engineering Physics Bandung Indonesia Institut Teknologi Del Faculty of Informatics and Electrical Engineering Toba Indonesia Institut Teknologi Bandung Engineering Physics Study Program Bandung Indonesia Institut Teknologi Bandung Instrumentation Control and Automation Research Group Bandung Indonesia

ISBN: (纸本)9798350364743

In indoor vertical farming systems, managing dynamic and complex environments poses significant challenges. Traditional control strategies often fall short in adapting to rapid changes in critical parameters such as nutrient levels, climate conditions, and plant health indicators. To address these challenges, this paper presents a novel approach for optimizing indoor vertical farming using Deep Deterministic Policy Gradient (DDPG), a reinforcement learning algorithm well-suited for environments with continuous action spaces. Our study focused on the control and monitoring of key parameters, including nutrient levels (pH and EC), climate conditions (temperature, humidity, light, and CO2 levels), and plant health indicators (biomass accumulation and leaf size structure). By defining a comprehensive state and action space, we simulated an indoor farming environment and trained the DDPG model to maximize crop yield and health. © 2024 IEEE.

关键词： DDPG indoor vertical farming precision agriculture reinforcement learning smart farming

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Convolutional Neural Network for Microhydro Power Forecasting

Convolutional Neural Network for Microhydro Power Forecastin...

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Energy and Sustainable Development

作者： Happy Aprillia Amalia Rizqi Utami Anjas Nur Salam Adi Mahmud Jaya Marindra Riza Hadi Saputra Industrial Technology & Process Department Electrical Engineering Study Program Institut Teknologi Kalimantan Balikpapan Indonesia

ISBN: (数字)9798331517076

ISBN: (纸本)9798331517083

关键词： Microhydro power Accuracy Electricity Systems operation Solar energy Predictive models Rivers Convolutional neural networks Forecasting Root mean square

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