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Daily Peak Load Forecast of Banda Aceh City Using Adaptive Neuro Fuzzy Inference System (ANFIS) Method

Daily Peak Load Forecast of Banda Aceh City Using Adaptive N...

引用

computer System, Information Technology, and electrical engineering (COSITE), International Conference on

作者： Heldi Tindra Ira Devi Sara Ramzi Adriman Graduate program of Electrical Engineering Universitas Syiah Kuala Banda Aceh Aceh Dept. of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Aceh

electrical energy has become a fundamental need for society to achieve economic and technical efficiency. To meet the demand for electrical energy, the thing that is done is Electric Load Forecast. In this study, we developed a daily peak load forecast model for Banda Aceh City by considering data on temperature, humidity, and today’s electricity load data at peak hours. Forecasts are made using artificial intelligence, namely, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. Software used Matlab R2015a to create a daily peak load forecast model based on the neuro-fuzzy designer toolbox. The ANFIS model developed is a variation of triangular, trapezium, and Gaussian membership function types, with each membership function equipped with 3 and 4 variable fuzzy sets. This study uses the MAPE instrument to measure the accuracy of the developed ANFIS model. The results obtained through simulations that have been carried out, all ANFIS Models produce MAPE values below 10%. This indicates that the developed ANFIS Model is very appropriate to be used for Daily Peak Load Forecast in Banda Aceh.

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Achieving Zero Cache-Miss based on the Control Flow Graph 1

Achieving Zero Cache-Miss based on the Control Flow Graph

引用

1st IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer engineering, MI-STA 2021

作者： Elahresh, Musbah Mohammed Ali Elaraby, Abed Elatie College of Electronic Technology Department of Post Graduate Studies Tripoli Libya Elmergb University Department of Electrical and Computer Engineering Alkhoms Libya

ISBN: (纸本)9781665418560

This paper provides a design of a control circuit for cache memory with no time overhead for cache miss conditions. this type of circuits is very important in modern computers design to enhance program execution time and increase the processor performance. The main objective of the designed circuit is to provide a high performance of program execution and avoiding cache miss. The focus is on finding an optimal method that provides fast program execution. This is due to the fact that most of the existing methods are still producing cache miss. The proposed method is based on utilizing the control flow graph (CFG) of the program being executed. The proposed solution works with dividing the program into basic blocks of instructions. The program blocks and the execution paths are modeled by the CFG. A program traverses an execution path according to its current state which is represented by its data variables. If a block is required to be entered from the current block, that block is already available in the cache. This leads to eliminating cache miss. In this paper we provide the design for a cache memory control circuit that manages the cache according to the information of the CFG. Many experiments were run and tested using simulation that evaluated the proposed control circuit. © 2021 IEEE.

关键词： Cache memory

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Comparative Analysis between Three-Leg Interleaved and Conventional Bidirectional Converters Applied in Battery of Wind Power-Battery Unit Supplying an Islanded Microgrid

Comparative Analysis between Three-Leg Interleaved and Conve...

引用

IEEE General Meeting Power& Energy Society

作者： André C. Do Nascimento Giusep M. S. Ribeiro Lindemberg R. de Lima Pedro A. de Alcântara Luana C. S. Soares Luciano S. Barros Camila M. V. Barros Electrical Engineering Graduate Program Federal Institute of Pará Belém Brazil Electrical Engineering Graduate Program Federal University of Paraíba João Pessoa Brazil Mathematics and Computational Modeling Graduate Program Federal University of Paraíba João Pessoa Brazil Computer Systems Department Federal University of Paraíba João Pessoa Brazil

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

Battery energy storage systems (BESS) are crucial for microgrids, enhancing dynamic performance and mitigating uncertainties inherent to isolated environments characterized by intermittent power generation. When microgrid is supplied by wind power in connection with BESS, the bidirectional DC-DC converter associated with BESS assumes a critical responsibility—ensuring the control of a wind power supplied DC-link. This permits the Voltage Source Inverter (VSI) to synthesize consistent voltages for the connected AC load. However, challenges emerge, particularly in arduous stress on switches of the bidirectional converter attributed to elevated current ripple. This stress does not only prejudice the overall system’s functioning but can also potentially leading it to shutdown in case of switch failure. Traditionally, the conventional buck-boost converter topology has been the go-to choice for this application, nevertheless, exploring novel converter topologies, such as interleaved bidirectional DC-DC converter (IBDC) has garnered attention, promising enhanced performance. This paper’s goal is to conduct a comparative analysis of the operation of these converters in an islanded microgrid supplied by a single Permanent Magnet Synchronous Generators (PMSG) small-scale wind turbine with a BESS system. Load variation with Maximum Power Point Tracking (MPPT) operation of the PMSG is performed during MATLAB/Simulink environment simulations. The results suggest significant advantages for the interleaved three-phase converter, such as reduced battery charging current ripple, switch disturbance, and voltage ripple in the DC-link.

关键词： Maximum power point trackers Magnetic separation Microgrids DC-DC power converters Wind power generation Permanent magnets Batteries Topology Wind turbines Stress

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BAQET: BRAM-aware Quantization for Efficient Transformer Inference via Stream-based Architecture on an FPGA 25

BAQET: BRAM-aware Quantization for Efficient Transformer Inf...

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Proceedings of the 2025 ACM/SIGDA International Symposium on Field programmable Gate Arrays

作者： Ling-Chi Yang Chi-Jui Chen Trung Le Bo-Cheng Lai Scott Hauck Shih-Chieh Hsu Institute of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan Graduate Degree Program of College of Electrical and Computer Engineering in National Yang Ming Chiao Tung University Hsinchu Taiwan Electrical and Computer Engineering in University of Washington Seattle USA Electrical and Computer Engineering University of Washington Seattle USA Physics University of Washington Seattle USA

ISBN: (纸本)9798400713965

FPGAs are a compelling substrate for supporting machine learning inference. Tools such as High-Level Synthesis and hls4ml can shorten the development cycle for deploying ML algorithms on FPGAs, but can struggle to handle the large on-chip storage needed for many of these models. In particular the high BRAM usage found in many of these flows can cause Place & Route failures during synthesis. In this paper we propose using a Simulated-Annealing based flow to perform BRAM-aware quantization. This approach trades off inference accuracy with BRAM usage, to provide a high-quality inference engine that still meets on-chip resource constraints. We demonstrate this flow for Transformer-based machine learning algorithms, which include Flash Attention in a Stream-based Dataflow architecture. Our system imposes minimal accuracy drops, yet can reduce BRAM usage by 20%-50%, and improve power efficiency by 264%-812% compared to existing Transformer-based accelerators on FPGAs

关键词： efficient transformer

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Ti02-based Flexible Integrated Photonics for High-sensitivity Temperature Sensing

Ti02-based Flexible Integrated Photonics for High-sensitivit...

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2022 Conference on Lasers and Electro-Optics, CLEO 2022

作者： Zhao, Xuan Fan, Bo Veeraraghavan, Ashok Robinson, Jacob Applied Physics Graduate Program Smattey-Curl Institute Rice University HoustonTX77005 United States Electrical & Computer Engineering Rice University HoustonTX77005 United States

We report a flexible temperature sensor based on Ti02 photonics that shows double the sensitivity compared to silicon photonics. This high sensitivity and biocompatibility pave the way towards point-of-care temperatur... 详细信息

ISBN: (纸本)9781957171050

关键词： Biocompatibility

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Light-induced tunable optical properties of 1T-TaS2 at different temperatures

Light-induced tunable optical properties of 1T-TaS2 at diffe...

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CLEO: QELS_Fundamental Science, QELS 2022

作者： Li, Weijian Naik, Gururaj V. Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Electrical and Computer Engineering Rice University HoustonTX77005 United States

The c-axis permittivity of 1T-TaS2 - a quasi-2D charge-density-wave material - changes upon illumination due to light-induced reorganization of CDW stacking. Here we probe the mechanism of this reorganization and find... 详细信息

ISBN: (纸本)9781557528209

关键词： Charge density

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Application of Artificial Neural Network Method for Forecasting Weekly Electricity Load Based on Daily Pattern Classification

Application of Artificial Neural Network Method for Forecast...

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computer System, Information Technology, and electrical engineering (COSITE), International Conference on

作者： Husni Ramzi Adriman Ira Devi Sara Rio Syahputra Graduate program of Electrical Engineering Faculty of Engineering Universitas Syiah Kuala Banda Aceh Aceh Department of Electrical and Computer Engineering Faculty of Engineering Universitas Syiah Kuala Banda Aceh Aceh

Accurate weekly electricity load prediction is of utmost importance for electricity providers to ensure uninterrupted power supply to customers. This study applies an Artificial Neural Network (ANN) to achieve precise weekly electricity load prediction. The dataset used for the ANN model consists of three months’ worth of data, including daily workload profiles, holiday work profiles, temperature, and humidity. For model training, 90% of the data is utilized with the Levenberg-Marquardt algorithm, while the remaining 10% is used for testing. The Mean Average Percentage Error (MAPE) is employed as the error metric. Based on the test results, the weekly load prediction error rate using ANN is determined to be 1.78% based on the MAPE value.

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1T-TaS2 based dynamically tunable plasmonic metasurface

1T-TaS2 based dynamically tunable plasmonic metasurface

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CLEO: QELS_Fundamental Science, QELS 2022

作者： Li, Weijian Naik, Gururaj V. Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Electrical & Computer Engineering Rice University HoustonTX77005 United States

We demonstrate a dynamically tunable plasmonic metasurface enabled by light-tunable optical constants of a quantum material - 1T-TaS2. We observe a relative reflectance change of 10% under low-intensity incoherent ill... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781557528209

关键词： Reflectivity MIM devices Lighting Lasers and electrooptics Metasurfaces Plasmons Optical materials

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TiO2-based Flexible Integrated Photonics for High-sensitivity Temperature Sensing

TiO2-based Flexible Integrated Photonics for High-sensitivit...

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CLEO: Science and Innovations, S and I 2022

作者： Zhao, Xuan Fan, Bo Veeraraghavan, Ashok Robinson, Jacob Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Electrical & Computer Engineering Rice University HoustonTX77005 United States

We report a flexible temperature sensor based on TiO2 photonics that shows double the sensitivity compared to silicon photonics. This high sensitivity and biocompatibility pave the way towards point-of-care temperatur... 详细信息

ISBN: (纸本)9781557528209

关键词： Titanium dioxide

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AI-driven Maintenance Tool for Synchronous Power Generator Temperature Monitoring Using Fiber Bragg Gratings

AI-driven Maintenance Tool for Synchronous Power Generator T...

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SBMO/IEEE MTT-S International Conference on Microwave and Optoelectronics (IMOC)

作者： Uilian José Dreyer Erlon V. da Silva Wilian Oliveira Paulo H. R. Mazzo Kleiton de M. Sousa André Biffe Di Renzo Cicero Martelli Jean Carlos Cardozo da Silva Graduate Program in Energy Systems (PPGSE) ENGlE Brasil Energia Universidade Tecnologica Federal do Parana-UTFPR Curitiba Parana Brazil Graduate Program in Electrical and Computer Engineering (CPGEI)

The carbon brushes and slip rings of a hydrogen-erator are the main components guiding the excitation current from the bridge to the rotor windings. The brushes' temperature are crucial to infer their operational condition and, the generator status. This work presents the temperature measurement of six Fiber Bragg Gratings (FBG) sensors installed in a 370 MVA electric generator brushes. The results show the sensors' capacity to monitor the brushes' temperature in accordance with the current flowing through them. Together with the sensors, an Artificial Intelligence (AI) technique was applied to the measured temperature to detect anomalous events regarding the current supplied to the rotor windings. The optical sensors combined with the AI could detect five events of abnormal current behaviour. One is presented in detail in this paper. This sensing system can be further applied to online fault detection using the temperature measured by the FBGs as a brush condition indicator and a generator operation and maintenance tool.

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