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5th IEEE advanced Information Management, Communicates, Electronic and Automation control conference, IMCEC 2022

作者： Qing, Song Xie, Tuo Bai, Qingjun Li, Pai Institute of Water Resources and Hydro-Electric Engineering Xi'An University of Technology Xi'an710048 China China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems Beijing102401 China

ISBN: (纸本)9781665479677

In order to further improve the ecological environment in desert areas and actively respond to the development of the 'dual carbon' policy, numerous distributed photovoltaics have been connected to the distribution network in recent years. Network loss caused a greater impact. For the location and capacity planning of distributed photovoltaic access to the distribution network, this paper proposes a distributed photovoltaic location and capacity model that considers investment costs, distribution network losses, voltage stability, and environmental protection costs. the improved multi-objective genetic algorithm is used to solve the optimization model, which is verified by example simulation. After the optimized configuration, the power supply quality and network loss of the distribution network are significantly improved, which verifies the feasibility of the model. this research provides a certain reference and reference for the location and capacity determination of the distribution network with distributed photovoltaics. © 2022 IEEE.

关键词： Genetic algorithms

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Design of Mobile Robot control System Based on EMG Signal 5

Design of Mobile Robot Control System Based on EMG Signal

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5th international conference on Intelligent Autonomous Systems, ICoIAS 2022

作者： Wang, Xinjie Bai, Wei Zheng, Huadong Wang, Caidong Wu, Benjie Han, Longxiang College of Mechanical and Electrical Engineering Zhengzhou University of Light Industry Zhengzhou China

ISBN: (数字)9781665498388

ISBN: (纸本)9781665498388

In the current research, there are three main control methods for intelligent robot car, which are manual control, remote control and automatic control. And in the field of remote control, whether it is the direct use of remote control or the remote control keys are virtually installed in the mobile phone APP, there is a lack of direct interaction with human. To solve this problem, an intelligent robot car control system was developed to wirelessly control the intelligent car based on electromyography(EMG) signals in this paper. the intelligent robot car responds to the operator's different gestures by moving forward, backward, turning left and turning right. Firstly, EMG signals of different gestures of the forearm are collected, and the collected EMG signals are amplified, filtered and de-noised in MATLAB. then, the data are processed by corresponding algorithms such as active segment detection, feature extraction and pattern classification on PC to obtain the recognition results of various gestures. Finally, different gestures are analyzed into corresponding commands and the signals are transmitted to the robot car through Bluetooth transmission so as to realize the real-Time control of gestures to the robot car motion state. After several experiments, the intelligent car control system based on EMG can effectively control the robot car motion state according to the operator's gesture, and the recognition rate of the selected four gestures is more than 95%, the recognition rate is high, the system performance is good, and has good operability and stability. © 2022 IEEE.

关键词： Bluetooth

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Machine learning forecasts of Scandinavian numerical weather prediction wind model residuals with control theory for wind energy

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ENERGY REPORTS 2022年 8卷 661-668页

作者： Chen, Hao Zhang, Qixia Birkelund, Yngve UiT Arctic Univ Norway Dept Technol & Safety N-9019 Tromso Norway UiT Arctic Univ Norway Dept Comp Sci N-9019 Tromso Norway UiT Arctic Univ Norway Dept Phys & Technol N-9019 Tromso Norway UiT Arctic Univ Norway Arctic Ctr Sustainable Energy N-9019 Tromso Norway

the quality of wind data from the numerical weather prediction significantly influences the accuracy of wind power forecasting systems for wind parks. therefore, an in-depth investigation of these wind data themselves is essential to improve wind power generation efficiency and maintain grid reliability. this paper proposes a novel framework based on machine learning for concurrently analyzing and forecasting predictive errors, called residuals, of wind speed and direction from a numerical weather prediction model versus measurements over a while. the performance of the framework is testified by a wind farm inside the Arctic. It is demonstrated that the residuals still contain significant meteorological information and can be effectively predicted with machine learning and the linear autoregression works well for multi-timesteps predictions of overall, East-West, and North-South wind speeds residuals by comparing the four forecast learning algorithms' performance. the predictions may be applied to correct the NWP wind model, making quality feedback improvements for inputs for wind power forecasting systems. (C) 2022 the Author(s). Published by Elsevier Ltd.

关键词： Autoregressive forecast Machine learning Residual analysis Statistical inference Wind energy Feedback

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A Decentralized control Strategy for Voltage Regulators and Energy Storage Devices in Active Unbalanced Distribution Systems 5

A Decentralized Control Strategy for Voltage Regulators and ...

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5th international conference on Smart Energy Systems and Technologies (SEST)

作者： Ahmadi, Bahman Giraldo, Juan S. Hoogsteen, Gerwin Gerards, Marco E. T. Hurink, Johann L. Univ Twente Dept EEMCS Enschede Netherlands

ISBN: (数字)9781665405577

ISBN: (纸本)9781665405577

this paper studies a multi-objective optimization problem that optimizes unbalanced distribution networks with high penetration of photovoltaic power generation whereby the aim is to find the optimal tap positions of voltage regulators (VRs) and locally optimized charging and discharging power profiles for energy storage devices (ESDs) based on a decentralized coordination process. the corresponding objective function is based on the voltage profile of the network and the lifetime improvement of the VRs and ESDs. the advanced Arithmetic Optimizer (AAO) algorithm combined with the profile steering approach is used to find a near-optimal solution for the problem. the decentralized process is compared to a centralized approach for the IEEE 13 and 123 bus systems. Results show that the proposed decentralized method is able to resolve all voltage problems and find good quality solutions in lower computational time compared to the centralized approach and other optimization algorithms.

关键词： Distributed generation Voltage control Regulators Optimal control Profile steering Heuristic algorithm

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Research Progress of Coordination control Strategy for Flywheel Array Energy Storage System 5th

Research Progress of Coordination Control Strategy for Flywh...

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5th international conference on Energy Storage and Intelligent Vehicles, ICEIV 2022

作者： Zhao, Yongming Qiu, Qingquan Nie, Zipan Institute of Electrical Engineering Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Institute of Electrical Engineering and Advanced Electromagnetic Drive Technology Qilu Zhongke Jinan250000 China

ISBN: (纸本)9789819910267

Restricted by cost and technology, increasing the power of a single flywheel energy storage device is difficult. Using flywheel array can not only increase the total energy storage capacity of the flywheel system, but also reduce the development and production cost of the unit. For the flywheel array energy storage system, the research on the control strategy of coordinated control and mutual cooperation of each energy storage unit is the solution to realize the efficient and safe operation of the array. this paper firstly discusses the research progress of coordinated control strategies for flywheel array energy storage systems internationally in recent years, and summarizes and analyzes the advantages and disadvantages of various control strategies in flywheel energy storage power distribution and array parallel control. By summarizing and researching the coordinated control strategies of flywheel array energy storage systems in the fields of grid regulation, UPS, rail transit energy recovery, pulse power supply, and integrated energy storage technology, the paper provides reference for the design and innovation of array control strategy of the integrated physical energy storage system. © 2023, Beijing Paike Culture Commu. Co., Ltd.

关键词： Flywheels

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A Framework for Automatic Identification of Neural Network Structural Redundancy Based on Reinforcement Learning 5

A Framework for Automatic Identification of Neural Network S...

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5th international conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Wu, Tingting Song, Chunhe Zeng, Peng State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510662520

the increasing structure of neural networks makes it difficult to deploy on edge devices with limited computing resources. Network pruning has become one of the most successful model compression methods in recent years. Existing works usually compress models by removing unimportant filters based on the importance. However, the importance-based algorithms tend to ignore the parameters that extract edge features with small criterion values. And recent studies have shown that the existing criteria rely on norm and lead to similar model compression structures. Aiming at the problems of ignoring edge features and manually specifying the pruning rate in current importance-based model pruning algorithms, this paper proposes an automatic recognition framework for neural network structure redundancy based on reinforcement learning. First, we perform cluster analysis on the filters of each layer, and map the filters into a multidimensional space to generate similar sets with different functions. We then propose a criterion for identifying redundant filters within similar sets. Finally, we use reinforcement learning to automatically optimize the cluster dimension, and then determine the optimal pruning rate for each layer to reduce the performance loss caused by pruning. Extensive experiments on various benchmark network architectures and datasets demonstrate the effectiveness of our proposed framework. © 2023 SPIE.

关键词： Reinforcement learning

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Repetitive control-Based Torque Ripple Reduction Method for SRM Drive 5

Repetitive Control-Based Torque Ripple Reduction Method for ...

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5th IEEE international Electrical and Energy conference, CIEEC 2022

作者： Wu, Yiying Wang, Shuanghong Li, Longchun He, Miao Zhong, Cheng Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology Wuhan China Shaanxi Aero Electric Co. Ltd Xian China Guizhou Aerospace Linquan Motor Co. Ltd Guizhou China Aerospace Heavy Industry Co. Ltd Wuhan China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

In this paper, a torque ripple suppression strategy of SRM based on repetitive control was proposed. Due to the doubly salient structure of SRM, the rate of rising current and falling current is different in the current commutation period, which leads to a large fluctuation of electromagnetic torque. In the conventional current chopping control, the current would exceed the hysteresis range in practical application due to the insufficient switching frequency. therefore, a repetitive controller has been used in the speed loop to generate a periodic current reference signal, which can improve the reference current in advance. And the improved soft current chopper control combined with PWM is adopted in current loop to reduce the torque ripple caused by current overshoot in the single-phase excitation stage. In this paper, an SRM control system based on repetitive control has been constructed. the proposed control strategy is verified by simulation, and the FFT analysis is used to illustrate the effect of the strategy on the suppression of torque ripple, which proves that the proposed control method can effectively reduce the torque ripple. © 2022 IEEE.

关键词： Torque

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Sensorless Firefly Algorithm for Speed control of BLDC Motors 5

Sensorless Firefly Algorithm for Speed Control of BLDC Motor...

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5th international conference on Contemporary Computing and Informatics, IC3I 2022

作者： Pandya, Dharmesh J. Singh, Akanksha Vinothkumar, T. Raturi, Anuj Deepak, A. Khan, Irfan Atmiya University Department of Electrical Engineering Gujarat Rajkot India Amity University Uttar Pradesh Greater Noida India RVS College of Engineering and Technology Department of Electrical and Electronics Engineering Kumaran kottam campus Kannampalayam Coimbatore641402 India Graphic Era Deemed to Be University Department of Mechanical Engineering Uttarakhand Dehradun248002 India Saveetha Institute of Medical and Technical Sciences SIMATS Saveetha School of Engineering Tamilnadu Chennai India Lloyd Institute of Engineering and Technology Greater Noida India

ISBN: (纸本)9798350398267

the speed of a brushless direct current (BLDC) motor can be controlled in a way inspired by the workings of the natural world. To obtain the best proportional integral (PID) derivative parameters that also produce the lowest possible value for the time domain objective function, the proposed speed controller design is reformatted as a optimization challenge and the firefly FFA algorithm used. Population-based algorithms have many advantages over traditional methods when it comes to solving difficult optimization problems. the proposed FFA-PID controller's performance has been assessed for sudden changes in setpoint, load torque at speeds below rated speed, and rated speed in comparison to rated speed. A brushless DC motor's drive is simulated using the MATLAB/SIMULINK software suite. the simulation outcomes demonstrate that the proposed method outperforms the artificial bee colony method in terms of controlling the engine's operating speed when the particular time domain parameters are altered. FOPID and PID controllers were contrasted in this proposal using the artificial swarm method and the firefly technology. the firefly and artificial bee algorithms for choosing the right PID parameters to drive a brushless DC motor. After comparing a wide range of controllers and algorithms, we came to the conclusion that the PID controller will function best in hardware. © 2022 IEEE.

关键词： Brushless DC motors

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Multi-Agent control of a Virtual Power Plant in the Context of the Environmental Rating 1

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5th international Russian Automation conference, RusAutoCon 2023

作者： Sosnina, E. Shalukho, A. Erdili, N. Nizhny Novgorod State Technical University N.a. R.E. Alekseev 24 St. Minina Nizhny Novgorod603155 Russia

ISBN: (数字)9783031511271

ISBN: (纸本)9783031511264

there is a tendency to expand the list of types of distributed generation sources (DG) and increase their total installed capacity. Much attention is paid to the introduction of renewable energy sources (RES), which are environmentally friendly compared to traditional power plants. their integration into power systems can be achieved with the help of a virtual power plant (VPP). the object of study is the VPP which connects DG power plants through electrical networks with a voltage of 0.4–10 kV. the VPP uses a multi-agent system (MAS) to control energy exchange. the agents are defined: generation, load and a centralized power system. When developing algorithms for the functioning of the generation and load agents, the rating of generation agents criterion in terms of environmental friendliness is primarily taken into account. this provides the advantage of consuming electricity from the most environmentally friendly power plants. A methodology has been developed for determining the environmental friendliness rating of DG sources, taking into account the life cycle of power plants. the environmental rating is determined by the installed power, the materials used, the fuel used, the service life and the location of the DG sources. Several approaches to the application of the environmental rating in the management of the VPP are considered. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Virtual Power Plants

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Predictive cruise control for 4WD electric vehicle based on dynamic weight factors

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ENERGY REPORTS 2022年 8卷 237-246页

作者： Wu, Dongmei Yuan, Quan Du, Changqing Yan, Fuwu Li, Yang Wuhan Univ Technol Hubei Key Lab Adv Technol Automot Components Wuhan 430070 Peoples R China Foshan Xianhu Lab Adv Energy Sci & Technol Guangdong Lab Foshan 528200 Peoples R China Wuhan Univ Technol Hubei Res Ctr New Energy Intelligent Connected Ve Wuhan 430070 Peoples R China Tech Ctr Dongfeng Commercial Vehicle Wuhan 430056 Peoples R China

By computing the velocity trajectory based on the advancing road and traffic information, the predictive cruise control (PCC) system can significantly reduce vehicle energy consumption. As the weight factors of different objective item have an important influence on the control results of PCC system, this paper proposed a novel optimization method with dynamic weight factors according to the classification of road slope for 4 wheel drive intelligent (4WD) electric vehicles. In order to determine the weight coefficient adjustment method, the influence of road slope on the PCC performance was analyzed and a road category identification method was presented. the results of simulation indicated that the proposed PCC based on dynamic weight coefficients can improve the adaptability of PCC on different categories of road. Compared with the traditional PCC with constant weight coefficient, the maximum energy-saving rate can reach 32.3% at a small cost of driving distance 3.86% on rapid downhill road. For other type of road, uphill and continuously undulating road, the energy-saving rate was low, where it was more important to improve the driving efficiency by 1.46%. (C) 2022 the Author(s). Published by Elsevier Ltd.

关键词： Predictive cruise control Energy saving Dynamic weight factors MPC 4WD electric vehicle

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