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3rd international conference on Laser, Optics, and Optoelectronic Technology, LOPET 2023

作者： Ke, Yousheng Xu, Shuang Tang, Qing Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Precision Manufacturing Institute Wuhan University of Science and Technology Wuhan430081 China

ISBN: (纸本)9781510667624

To improve the security and efficiency of the image message transmission. This paper propose an optical image encryption scheme based on random phase mask and four-step phase shift digital holography. In the process of image encryption, the low frequency sub-band of the original images are superimposed by wavelet transform to increase the encryption efficiency. In this paper, Henon mapping generates two random phase masks. The initial values and control parameters of Henon mapping can be used as the main keys. The use of random phase mask makes the transmission and storage of the keys of sender and receiver more convenient. Moreover, the wavelength and diffraction distance are also used as the keys, which can enhance the security of encryption. With the help of random phase masks and four-step phase-shifting digital holography, the original image is encrypted into four cipher holograms. The simulation results show that the encryption algorithm proposed in this paper can reconstruct high-quality decrypted images and effectively resist various noise attacks. © 2023 SPIE.

关键词： Cryptography

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Learning in Load Frequency control for Stochastic Power Systems with Renewable Energy Integration 1

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3rd international conference on Innovation in Energy Management and Renewable Resources, IEMRE 2023

作者： Das, Sayanee Chattopadhyay, Paramita Indian Institute of Engineering Science and Technology Shibpur India

ISBN: (数字)9789819763900

ISBN: (纸本)9789819763894

Load Frequency control has remained as one of the challenging tasks in modern power systems due to the integration of low inertia renewable energy. This paper presents a preliminary report of a data-driven, model-free Deep Reinforcement Learning (DRL)-based approach for control of frequency of a single area power system integrated with wind energy. The proposed intelligent controller has interacted with the environment and learnt the control strategy to combat with the stochasticity and uncertainty of the power system. The results obtained under MATLAB-SIMULINK environment clearly indicates the superiority of the DRL-based controller over traditional PSO-tuned PID controller and has a promising future for applications in next generation power system with high penetration of renewable energy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Wind power integration

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control of Distributed Generation System with Grid Synchronization Capability Feeding Uninterrupted Power to Local Loads 3

Control of Distributed Generation System with Grid Synchroni...

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3rd IEEE international conference on Smart Technologies for Power, Energy and control, STPEC 2023

作者： Tiwari, Kripa Singh, Bhim Indian Institute of Technology Delhi Department of Electrical Engineering New Delhi110016 India

ISBN: (纸本)9798350304732

This paper's primary goal is to continuously supply power to local loads while employing a coordinated control technique for voltage source converters in standalone and grid-interfaced operation modes when microgrid is susceptible to dynamics. The energy from the solar and wind renewable energy sources is extracted using DC-DC converters and powering local loads, that are connected to a common AC bus via parallel voltage source converters. To feed the sinusoidal grid current in case of grid interfaced mode of operation with unity power factor, the fundamental component of load current is generated using generalized soft root sign adaptive filtering approach to deal with high steady-state misalignment due to significant weight update. The converter integrated into the wind energy conversion system (WECS) functions as a grid-forming converter, and the battery energy storage is tied to the DC link to work as a power regulation entity amid interruptions in the event of standalone operational mode. The capability of both the converters operating parallel and overall microgrid response using robust control approach are corroborated in MATLAB Simulink platform and obtained results are proving the efficacy is presented in this work. © 2023 IEEE.

关键词： Adaptable control Algorithm BLDC Generator GSRS Algorithm SECS WECS

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LSTM-based MPC Method for Stochastic Energy Management of Microgrid 3

LSTM-based MPC Method for Stochastic Energy Management of Mi...

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3rd international conference on New Energy and Power engineering, ICNEPE 2023

作者： An, Na Liu, Tingxiang Chen, Ke Huang, Haojiang Yang, Libin Li, Zhengxi Gao, Jin Zhu, Jianquan Clean Energy Development Research Institute of State Grid Qinghai Electric Power Company Economic and Technological Research Institute of State Grid Qinghai Electric Power Company Xining China South China University of Technology Guangzhou China

ISBN: (纸本)9798350393224

The intermittency and randomness of renewable energy sources (RESs) bring great challenge to the stochastic energy management (SEM) problem of microgrids (MGs). To solve this problem, we embed long short-term memory (LSTM) networks into model predictive control (MPC). The performance of the MPC method relies on the efficiency of real-time prediction and rolling optimization. Therefore, during the real-time prediction stage, a prediction network is constructed to improve the accuracy of prediction for random variables. Furthermore, during the rolling optimization stage, since commercial solvers achieve better performance when solving nonlinear programming (NLP) problems compared to mixed-integer nonlinear programming (MINLP) problems, a policy network is constructed to convert the MINLP into an NLP problem, reducing the complexity of the problem. In this paper, a LSTM-based MPC method is proposed for SEM of MG. Compared to traditional MPC methods, the proposed method demonstrates superior computational efficiency in addressing the SEM problem. Finally, case studies on the given test system fully verifies the accuracy and effectiveness of the proposed method. © 2023 IEEE.

关键词： long short-term memory network microgrid MINL model predictive control stochastic energy management

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Multicarrier Space Vector Pulse Width Modulation for Enhanced Performance of Field Oriented controlled Open End Winding Induction Motor 3

Multicarrier Space Vector Pulse Width Modulation for Enhance...

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3rd IEEE international conference on Smart Technologies for Power, Energy and control, STPEC 2023

作者： Jain, Sachin Ch, S V S Phani Kumar Sonti, Venu Kumar, Sushant Nit Raipur Electrical Engineering Department Raipur India

ISBN: (纸本)9798350304732

This paper presents the enhanced operation of a field-oriented controlled open-end winding induction motor (FOC-OEWIM) drive. In the enhanced operation, the number of levels in the phase voltages of two-level inverters used in the OEWIM is increased. By employing the multicarrier space vector pulse width modulation (SVPWM) additional levels will be obtained in the phase voltages of the OEWIM. Due to the increase in the number of levels in phase voltage, phase voltage total harmonic distortion (THD) also improves, and the motor parameters like stator phase currents and its THD, torque and flux ripples will also improve. An analysis using the switching function concept is also provided in the paper. Using the analytical analysis, the analytical waveforms of pole voltages, common-mode voltage, and phase voltages are obtained. The simulation results of MATLAB Simulink software are also presented in the paper to further justify the enhanced performance of a three-phase dual two-level inverter fed Field oriented controlled open-end winding induction motor (FOC-OEWIM) drive along with the switch function analysis. During the operation, OEWIM is operated at the rated speed, and a speed reversal operation is also performed. Stator flux trajectory is also presented in this paper. © 2023 IEEE.

关键词： Field oriented control (FOC) Open-ended winding induction motor Switching function concept Two-level inverter

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Prediction method of primary frequency modulation capability of power system based on MEA-BP algorithm

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ENERGY REPORTS 2023年 9卷 111-118页

作者： Zhang, Yudong Tang, Fan Liang, Xiaobin Sun, Jian Li, Hongxun Ru, Hang State Grid Corp China Southwest Branch 299 shuxiu West Rd Chengdu 610000 Peoples R China Southwest Jiaotong Univ Sch Elect Engn 999 Xian Rd Chengdu 610000 Peoples R China

In order to accurately predict the primary frequency modulation capability of power system when frequency deviation occurs, a method for predicting primary frequency modulation performance of power system based on improved neural network with thought evolution algorithm (MEA) is presented. Nine-dimensional parameters, such as frequency deviation before and after disturbance, system backup capacity, load level, mechanical power and electrical power, are selected as input eigenvalues, and the output is the system power change curve. This paper takes CEPRI36v8 system as an example of simulation, obtains the primary frequency modulation curve of the system by setting the shear load disturbance with PSASP, uses the disturbance data and the primary frequency modulation response data as training set, test set and validation set data, trains the prediction model of primary frequency modulation capability based on MEA-BP, and finds the prediction error is about 0.5% compared with the actual data, which proves that the proposed method can accurately and quickly predict the primary frequency modulation capability after the frequency deviation of the power network. This method can assist power dispatcher to analyze the primary frequency modulation response of power grid after power disturbance.(c) 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Primary frequency Prediction analysis Power system disturbance BP neural network Mind evolutionary algorithm

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BER Improvement of Cooperative Spectrum Sharing of NOMA in 5G Network 3

BER Improvement of Cooperative Spectrum Sharing of NOMA in 5...

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3rd IEEE international Maghreb Meeting of the conference on Sciences and Techniques of Automatic control and Computer engineering, MI-STA 2023

作者： Hassan, Mohamed Saeed, Rashid A. Mokhtar, Rania A. Hamid, Khalid Ali, Elmustafa Sayed Odeh, Nidhal Singh, Manwinder Khalifa, Othman O. Islam, Shayla Lovely Professional University Department of Wireless Communication Punjab Phagwara144001 India Taif University Department of Computer Engineering College of Computers and Information Technology Taif21944 Saudi Arabia University of Science & Technology Department of Communication Systems Engineering Omdurman Sudan Department of Electronics Engineering Khartoum Sudan University of Wollongong School of Electrical Computer and Telecommunications Engineering Australia International Islamic University Malaysia Department of Electrical and Computer Engineering Gombak Malaysia Libyan Center for Engineering Resarch and Information Technology Bani Waleed Libya Institute of Computer Science and Digital Innovation Ucsi University Malaysia Department of Computer Science Kuala Lumpur56000 Malaysia

ISBN: (纸本)9798350319897

Non-orthogonal multiple access is one of the best methods for addressing the needs of 5G wireless services (NOMA). The proliferation of mobile devices in recent years has increased the importance of cooperative spectrum sharing and utilization in wireless communication due to increases in the bit error rate (BER) brought on by collisions and interference. In this study, MIMO and Massive MIMO (M-MIMO) in the downlink (DL) NOMA power domain (PD) in conjunction with the Cooperative Cognitive Radio Network are proposed as two new ways for improving and evaluating BER in the 5G network (CCRN). Customers of NOMA compete for available channels on the CCRN in this first strategy. The second approach creates a dedicated channel for NOMA users. Three scenarios with varying distances, power location coefficients, and transmission power are used to evaluate the proposed methods in the MATLAB software program. It is assumed that four users will share a 90 MHz BW using QPSK modulation in all three scenarios. When evaluating the performance of the suggested system under the presumption of frequency-selective Rayleigh fading, concurrent interference cancellation (SIC) and unstable channel conditions are also considered. © 2023 IEEE.

关键词： 5G mobile communication systems

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Missing Values Imputation Using Auto-associative Neural Network with Local Neighborhood Information 3

Missing Values Imputation Using Auto-associative Neural Netw...

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3rd international conference on Neural Networks, Information and Communication engineering, NNICE 2023

作者： Lai, Xiaochen Chen, Hui Zhang, Liyong School of Software Dalian University of Technology Dalian China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province Dalian China School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798350335972

Missing values of real-world datasets bring challenges to data mining. Popular methods for handling missing values are to replace missing values in a dataset using predicted values, called imputation, which is a fundamental task in many research fields. In this paper, we propose an auto-associative neural network with local neighborhood information for missing values imputation. Specifically, we introduce local neighborhood information into auto-associative neural network to make the spatial relationships among samples work. With the spread of neighbor information, the similarity of samples is used to supplement the missing attributes of incomplete samples, which facilitates network analysis of attributes associations. Besides, we propose a training method to iteratively update estimation by treating missing values as variables, in which the imputation error and the incomplete model inputs are continuously optimized during training. The training method allows incomplete samples to participate in the network training as well, enabling all known attributes to be useful. Experiments based on several public datasets validate the effectiveness of the proposed method. © 2023 IEEE.

关键词： Data mining

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Development of Home-Bot with Accident-Sensory System Using IOT and Android Application for control 3rd

Development of Home-Bot with Accident-Sensory System Using I...

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3rd international conference on Computer and Communication engineering, CCCE 2023

作者： Caalim, Patricia Louraine R. Calanao, Rexan Myrrh Masaga, Earl John Alagao, Stephen Paul L. Electronics Engineering Program University of Mindanao Davao City Philippines Computer Engineering Program University of Mindanao Davao City Philippines

ISBN: (纸本)9783031352980

The Internet-of-Things (IoT) and robotics, individually, has been widely used in promoting better home security and quality of life to its users. This study aims to design and develop a home-bot’s accident-sensory system to monitor flame, smoke, and earthquake detection through the use of IoT;and develop an android application to monitor the transmitted data from the device (hubs) and even control the home-bot using Bluetooth. The real-time readings from all the hubs will be sent to the cloud Backend-as-a-Service real-time database. This data will then be reflected in real-time in the android application and when either of the hubs detected any warning from any of the parameters, it will trigger an alarm to the hub itself and the android application for its user to react immediately. The system uses a nested loop algorithm to make sure that a detection is true in a span of time, together with a voting algorithm to avoid false alarms. The data gathered from the functionality tests was statistically analyzed using the confusion matrix method and resulted a 95.5% sensor accuracy for flame detection, 90.0% sensor accuracy for both the smoke and earthquake detection, and a successful transmission of data to the database to the android application in all the tests. The results showed significance accuracy and the system performed with accordance to its objectives and purpose. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Internet of things

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Underwater Fuzzy Image Enhancement Method Based on CycleGAN 24

Underwater Fuzzy Image Enhancement Method Based on CycleGAN

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3rd international Symposium on control engineering and robotics, ISCER 2024

作者： Wang, Gang Fu, Bofeng Zhuang, Sheng Zhao, Qiang Jilin Communications Polytechnic Mechanical and Control engineering Changchun130015 China BaiCheng Normal University Mechanical and Control engineering Jilin Baicheng137099 China Jilin Institute of Chemical Technology Information and Control engineering Jilin Jilin132022 China

ISBN: (纸本)9798400709951

In order to addressing color inaccuracies and insufficient contrast in submerged photography caused by light absorption and scattering effects, this paper presents an enhanced image enhancement methodology based on a modified Cycle-consistent Generative Adversarial Network (CycleGAN) tailored for complex aqueous turbidity conditions. The innovation in our algorithm lies in the augmentation of the generator network module within CycleGAN, wherein we integrate a channel-spatial attention mechanism and a multi-scale cross-dimensional interaction module. Furthermore, a novel joint loss function is introduced to optimize the training process comprehensively. To systematically assess the efficacy of our proposed algorithm, a qualitative and quantitative comparison was conducted against multiple advanced image enhancement algorithms. The experimental outcomes revealed a marked improvement over the baseline approach, with Peak Signal-to-Noise Ratio (PSNR) increasing by 3.8% and Structural Similarity Index (SSIM) ascending by 4.4%. These enhancements surpass those achieved by competing algorithms, demonstrating not only a superior enhancement capability but also a heightened robustness across varying depths and levels of water turbidity. Consequently, the proposed algorithm is poised to effectively enhance underwater images characterized by diverse degradation profiles. © 2024 ACM.

关键词： Underwater photography

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