Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856039
Q. Pan, Wei Li, Peilu Li, Lang Xu, Sa Li, Yunmiao Zhang, X. Zhou, Haoshen Yu
Residual stress is a very important factor among many factors such as structural failure and fracture of key components of mechanical structures. It is necessary to study accurate measurement and characterization techniques for residual stress. The LCR (Longitudinal critically refracted) wave method has the characteristics of non-destructiveness, high efficiency and accuracy, and has high application value in industrial stress detection. In the LCR wave method, the sound path and the thickness of the tested sample will affect the time-of-flight obtained by the subsequent cross-correlation algorithm, resulting in inaccurate final stress detection values. In this paper, the ultrasonic nondestructive testing system is used to detect the sound path of different sizes and the thickness of the tested sample, and the sound path range and the thickness range of the tested sample for the LCR wave method are obtained. The obtained experimental results promote the development of non-destructive testing technology.
{"title":"Research on The Optimal Sound Path of LCR Wave Detection Method and The Optimal Thickness Range of The Tested Sample","authors":"Q. Pan, Wei Li, Peilu Li, Lang Xu, Sa Li, Yunmiao Zhang, X. Zhou, Haoshen Yu","doi":"10.1109/ICMA54519.2022.9856039","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856039","url":null,"abstract":"Residual stress is a very important factor among many factors such as structural failure and fracture of key components of mechanical structures. It is necessary to study accurate measurement and characterization techniques for residual stress. The LCR (Longitudinal critically refracted) wave method has the characteristics of non-destructiveness, high efficiency and accuracy, and has high application value in industrial stress detection. In the LCR wave method, the sound path and the thickness of the tested sample will affect the time-of-flight obtained by the subsequent cross-correlation algorithm, resulting in inaccurate final stress detection values. In this paper, the ultrasonic nondestructive testing system is used to detect the sound path of different sizes and the thickness of the tested sample, and the sound path range and the thickness range of the tested sample for the LCR wave method are obtained. The obtained experimental results promote the development of non-destructive testing technology.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115229357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9855927
Kai Zhao, Jian Guo, Shuxiang Guo, Qiang Fu
With the deepening of the aging of China’s population, more and more people suffer from stroke. Stroke has three characteristics: high morbidity, high mortality, and high disability rate. At present, stroke has become one of the main causes of human death, and the population suffering from a stroke in China is gradually becoming younger, many patients can not work and live normally, destroying many happy families. However, stroke is not invincible. Once suffering from stroke, patients can still live and work independently as long as they actively carry out rehabilitation training. The surface EMG signal contains abundant physiological information and has remarkable effects on nerve rehabilitation and orthopedic rehabilitation. Patients with rehabilitation training less training can not play a rehabilitation effect, and excessive training is easy cause secondary injuries, therefore, this paper will design a fatigue state classification system based on surface EMG signals of human lower limb muscles, and analyze the fatigue state of patients’ lower limbs by collecting surface EMG signals of target muscles of human lower limbs, to ensure that patients can not only carry out effective training but also not cause secondary injuries due to excessive training.
{"title":"Design of Fatigue Grade Classification System Based on Human Lower Limb Surface EMG Signal","authors":"Kai Zhao, Jian Guo, Shuxiang Guo, Qiang Fu","doi":"10.1109/ICMA54519.2022.9855927","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9855927","url":null,"abstract":"With the deepening of the aging of China’s population, more and more people suffer from stroke. Stroke has three characteristics: high morbidity, high mortality, and high disability rate. At present, stroke has become one of the main causes of human death, and the population suffering from a stroke in China is gradually becoming younger, many patients can not work and live normally, destroying many happy families. However, stroke is not invincible. Once suffering from stroke, patients can still live and work independently as long as they actively carry out rehabilitation training. The surface EMG signal contains abundant physiological information and has remarkable effects on nerve rehabilitation and orthopedic rehabilitation. Patients with rehabilitation training less training can not play a rehabilitation effect, and excessive training is easy cause secondary injuries, therefore, this paper will design a fatigue state classification system based on surface EMG signals of human lower limb muscles, and analyze the fatigue state of patients’ lower limbs by collecting surface EMG signals of target muscles of human lower limbs, to ensure that patients can not only carry out effective training but also not cause secondary injuries due to excessive training.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115240396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, spherical robots are used for the detection and identification of lobsters in aquaculture. Lobster farmers are often faced with tasks such as observation, feeding, and fishing, which are all done manually, with low efficiency and high operating costs. Therefore, this paper proposes a real-time underwater lobster detector based on Generative Adversarial Networks and Convolutional Neural Networks, implemented by a spherical amphibious robot. Firstly, the underwater lobster image dataset is established, and the improved GAN algorithm and data increment method are used for data enhancement preprocessing. Secondly, the single-shot multi-frame detector (SSD) is improved as follows, using the lightweight network MobileNetV2 as the backbone of the SSD network; in the network prediction layer, using depthwise separable convolution instead of standard convolution to accelerate inference; compressing the fully connected layer The parameters construct a lightweight model. Finally, the model is trained on the underwater lobster dataset and deployed on a spherical amphibious robot, and the changes in the loss function value during training before and after image enhancement and algorithm improvement are plotted. Two sets of experimental test results show that the model optimizes the target recognition accuracy of underwater lobsters, and the recognition accuracy reaches 90.32%. The reduced model size facilitates model deployment and is only 24MB in size. The model has good stability and high recognition accuracy in identifying lobsters in complex situations.
{"title":"Study on Real-time Recognition of Underwater Live Shrimp by the Spherical Amphibious Robot Based on Deep Learning","authors":"Shaolong Wang, Jian Guo, Shuxiang Guo, Qiang Fu, Jigang Xu","doi":"10.1109/ICMA54519.2022.9856265","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856265","url":null,"abstract":"In this paper, spherical robots are used for the detection and identification of lobsters in aquaculture. Lobster farmers are often faced with tasks such as observation, feeding, and fishing, which are all done manually, with low efficiency and high operating costs. Therefore, this paper proposes a real-time underwater lobster detector based on Generative Adversarial Networks and Convolutional Neural Networks, implemented by a spherical amphibious robot. Firstly, the underwater lobster image dataset is established, and the improved GAN algorithm and data increment method are used for data enhancement preprocessing. Secondly, the single-shot multi-frame detector (SSD) is improved as follows, using the lightweight network MobileNetV2 as the backbone of the SSD network; in the network prediction layer, using depthwise separable convolution instead of standard convolution to accelerate inference; compressing the fully connected layer The parameters construct a lightweight model. Finally, the model is trained on the underwater lobster dataset and deployed on a spherical amphibious robot, and the changes in the loss function value during training before and after image enhancement and algorithm improvement are plotted. Two sets of experimental test results show that the model optimizes the target recognition accuracy of underwater lobsters, and the recognition accuracy reaches 90.32%. The reduced model size facilitates model deployment and is only 24MB in size. The model has good stability and high recognition accuracy in identifying lobsters in complex situations.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115312293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856032
Pinzheng Ni, Haoyang Liu, H. Yuan, Mengqi Cheng, Nan Xiao
Studies have shown that the prevalence of adult hypertension in my country is 23.2%, the treatment rate is 40.7%, the control rate is 15.3%, the treatment rate is 37.5%, 60% of patients who are receiving hypertensive treatment Blood pressure did not obtain significant control, including those with refractory hypertension. The carotid sinus electrical stimulation method is a new way to treat hypertension in recent years. Our carotid sinus electrical stimulator includes pulse generation modules, battery management modules, neural electrical signal sampling modules, and wireless communication modules. This paper focuses on the design of the pulse generating module, using the STM32L433 as the core circuit system of the central control unit, which produces an amplitude adjustable, pulse width, flexible, and pulse width-adjustable pulse generating circuit.
{"title":"Design And Simulation Of Implantable Carotid Sinus Electrical Stimulator","authors":"Pinzheng Ni, Haoyang Liu, H. Yuan, Mengqi Cheng, Nan Xiao","doi":"10.1109/ICMA54519.2022.9856032","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856032","url":null,"abstract":"Studies have shown that the prevalence of adult hypertension in my country is 23.2%, the treatment rate is 40.7%, the control rate is 15.3%, the treatment rate is 37.5%, 60% of patients who are receiving hypertensive treatment Blood pressure did not obtain significant control, including those with refractory hypertension. The carotid sinus electrical stimulation method is a new way to treat hypertension in recent years. Our carotid sinus electrical stimulator includes pulse generation modules, battery management modules, neural electrical signal sampling modules, and wireless communication modules. This paper focuses on the design of the pulse generating module, using the STM32L433 as the core circuit system of the central control unit, which produces an amplitude adjustable, pulse width, flexible, and pulse width-adjustable pulse generating circuit.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123130238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856045
C. Chiang, Yu-Hsiang Wu, Ching-Hsien Chao
A real-time artificial intelligence (AI) recognition system is newly used for applications of selecting unqualified in chicken cages. The proposed recognition system can detect dirty eggs from those clean ones by using the developed artificial intelligence. Furthermore, the recognition system can classify those contaminated eggs into three categories by a covered contamination area. Performing this functionality of the proposed real-time AI recognition system, the system can successfully detect unqualified eggs in cage. In addition, by deleting the unnecessary predicted bounding boxes and performing the non-maximum suppression algorithm utilized in the experiment, the time spending on every picture will be fewer than normal videos. The proposed recognition system could be used for selecting unqualified eggs applications.
{"title":"A Real-time Artificial Intelligence Recognition System on Contaminated Eggs for Egg Selection","authors":"C. Chiang, Yu-Hsiang Wu, Ching-Hsien Chao","doi":"10.1109/ICMA54519.2022.9856045","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856045","url":null,"abstract":"A real-time artificial intelligence (AI) recognition system is newly used for applications of selecting unqualified in chicken cages. The proposed recognition system can detect dirty eggs from those clean ones by using the developed artificial intelligence. Furthermore, the recognition system can classify those contaminated eggs into three categories by a covered contamination area. Performing this functionality of the proposed real-time AI recognition system, the system can successfully detect unqualified eggs in cage. In addition, by deleting the unnecessary predicted bounding boxes and performing the non-maximum suppression algorithm utilized in the experiment, the time spending on every picture will be fewer than normal videos. The proposed recognition system could be used for selecting unqualified eggs applications.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123070361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856339
R. Liu, Zhiwei Guan, Bin Li, Guoqiang Wen, B. Liu
Real-time localization and map construction (SLAM) is a key technology to realize autonomous navigation of smart cars, which mainly solves the problems of mobile robots in mapping, positioning and path planning. This paper introduces and analyzes SLAM. By comparing three different mapping algorithms, gmapping, hector, and cartographer, and through analysis and comparison experiments, the gmapping-based algorithm is finally used for mapping. On the basis of AMCL positioning, global and local path planning is carried out through A* algorithm and DWA algorithm to realize autonomous navigation and obstacle avoidance functions. And the experimental verification was carried out under the autolabor smart car. The experiment proved that using this algorithm, autolabor can perform accurate pose estimation, map construction and autonomous navigation in an unfamiliar environment.
{"title":"Research on real-time positioning and map construction technology of intelligent car based on ROS","authors":"R. Liu, Zhiwei Guan, Bin Li, Guoqiang Wen, B. Liu","doi":"10.1109/ICMA54519.2022.9856339","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856339","url":null,"abstract":"Real-time localization and map construction (SLAM) is a key technology to realize autonomous navigation of smart cars, which mainly solves the problems of mobile robots in mapping, positioning and path planning. This paper introduces and analyzes SLAM. By comparing three different mapping algorithms, gmapping, hector, and cartographer, and through analysis and comparison experiments, the gmapping-based algorithm is finally used for mapping. On the basis of AMCL positioning, global and local path planning is carried out through A* algorithm and DWA algorithm to realize autonomous navigation and obstacle avoidance functions. And the experimental verification was carried out under the autolabor smart car. The experiment proved that using this algorithm, autolabor can perform accurate pose estimation, map construction and autonomous navigation in an unfamiliar environment.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116677689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9855989
Ma You, Yanjuan Wu, Yunliang Wang, Xiyang Xie, Chen Xu
Aiming at the problem that the traditional PID controller was not ideal, the parameters could not be adjusted to the best state, and the control system could not achieve good control effect, an improved seagull optimization algorithm (SOA) based on improved Sine chaotic mapping was proposed to optimize the parameters of PID controller. Sine mapping strategy was adopted to make the initial seagull population evenly distributed in the search space, to improve the shortcomings of the seagull optimization algorithm, such as low solution accuracy, slow convergence speed and easy to fall into premature convergence, and improve the convergence speed and convergence accuracy of the algorithm. Eight standard test functions were tested, and the improved gull optimization algorithm was compared with the unimproved gull algorithm, particle swarm optimization algorithm (PSO), beetle antennae search algorithm (BAS), particle swarm optimization -beetle antennae search algorithm (PSO-BAS) and the seeker optimization algorithm (TSOA), to verify that the improved gull optimization algorithm has better optimization effect. The improved algorithm is applied to a second-order system and double closed-loop DC motor speed regulation system to optimize the parameters of PID controller. The results show that the algorithm has high precision, simple principle, better convergence precision and faster convergence speed.
{"title":"Parameter Optimization of PID Controller Based on Improved Sine-SOA Algorithm","authors":"Ma You, Yanjuan Wu, Yunliang Wang, Xiyang Xie, Chen Xu","doi":"10.1109/ICMA54519.2022.9855989","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9855989","url":null,"abstract":"Aiming at the problem that the traditional PID controller was not ideal, the parameters could not be adjusted to the best state, and the control system could not achieve good control effect, an improved seagull optimization algorithm (SOA) based on improved Sine chaotic mapping was proposed to optimize the parameters of PID controller. Sine mapping strategy was adopted to make the initial seagull population evenly distributed in the search space, to improve the shortcomings of the seagull optimization algorithm, such as low solution accuracy, slow convergence speed and easy to fall into premature convergence, and improve the convergence speed and convergence accuracy of the algorithm. Eight standard test functions were tested, and the improved gull optimization algorithm was compared with the unimproved gull algorithm, particle swarm optimization algorithm (PSO), beetle antennae search algorithm (BAS), particle swarm optimization -beetle antennae search algorithm (PSO-BAS) and the seeker optimization algorithm (TSOA), to verify that the improved gull optimization algorithm has better optimization effect. The improved algorithm is applied to a second-order system and double closed-loop DC motor speed regulation system to optimize the parameters of PID controller. The results show that the algorithm has high precision, simple principle, better convergence precision and faster convergence speed.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117210749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856137
Defu Zhang, Tongyu Hou, J. Yang, Jianjiang Xiao
In order to further improve the accuracy and real-time of Marine diesel engine fault identification, an intelligent identification method based on Shffled Frog Leaping algorithm and Harmonic search algorithm and optimized RBF neural network was proposed to diagnose Marine diesel engine fault. This method optimizes the hidden node, center vector and width parameters of RBF neural network, and carries out simulation experiment on Marine diesel engine fault identification under MATLAB environment. In the experimental process, the RBF neural network was built, and the HS algorithm was used to optimize the hyperparameters of the RBF network, and the SFLA algorithm was used to optimize the harmony memory library to further improve the accuracy of fault identification. Experimental results show that the RBF neural network trained by this method has good convergence effect and high diagnostic accuracy, which verifies the validity and rationality of the proposed method.
{"title":"Study on Marine Diesel Engine Fault Identification Based on Neural Network","authors":"Defu Zhang, Tongyu Hou, J. Yang, Jianjiang Xiao","doi":"10.1109/ICMA54519.2022.9856137","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856137","url":null,"abstract":"In order to further improve the accuracy and real-time of Marine diesel engine fault identification, an intelligent identification method based on Shffled Frog Leaping algorithm and Harmonic search algorithm and optimized RBF neural network was proposed to diagnose Marine diesel engine fault. This method optimizes the hidden node, center vector and width parameters of RBF neural network, and carries out simulation experiment on Marine diesel engine fault identification under MATLAB environment. In the experimental process, the RBF neural network was built, and the HS algorithm was used to optimize the hyperparameters of the RBF network, and the SFLA algorithm was used to optimize the harmony memory library to further improve the accuracy of fault identification. Experimental results show that the RBF neural network trained by this method has good convergence effect and high diagnostic accuracy, which verifies the validity and rationality of the proposed method.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127139116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856389
Qiang Gao, Ziyu Du, Yu Song, Yuehui Ji
The open communication network environment brings potential security trouble to the power grid. In this paper, a state model for the load frequency control is described, and it is studied under DoS attacks. Firstly, the limitation conditions of DoS attacks and control targets are given. An $H_{infty}$ observer and event triggering mechanism are added to the sensor system. A predictor is designed in the controller system. Due to the existence of the maximum transmission interval, Lyapunov stability theorem is used to prove that the input to the state of the system is stable. Finally, a two-area model is used to proof availability of the control scheme.
{"title":"Periodic Event-Triggered Resilient Control for Multiarea Interconnected Power Systems under Denial-of-Service Attacks","authors":"Qiang Gao, Ziyu Du, Yu Song, Yuehui Ji","doi":"10.1109/ICMA54519.2022.9856389","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856389","url":null,"abstract":"The open communication network environment brings potential security trouble to the power grid. In this paper, a state model for the load frequency control is described, and it is studied under DoS attacks. Firstly, the limitation conditions of DoS attacks and control targets are given. An $H_{infty}$ observer and event triggering mechanism are added to the sensor system. A predictor is designed in the controller system. Due to the existence of the maximum transmission interval, Lyapunov stability theorem is used to prove that the input to the state of the system is stable. Finally, a two-area model is used to proof availability of the control scheme.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125058628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856118
Yang Zhang, Yunfei Ma, Shuang Zhang, Lixian Chen, Hongda Liu
In this paper, an improved building-level demand-side management method is proposed based on load classification and real-time electricity pricing. Firstly, the loads are classified into uncontrollable loads, interruptible loads and transferable loads. The uncontrollable loads are forecasted as a part of the system state. The interruptible loads are controlled all the time. The transferable loads can be managed to work in proper periods in a day. Then, the user’s electricity consumption is managed by the energy consumption controller, which solves a game problem between the user and the others. At last, we generate users’ electricity consumption conditions using the Monte Carlo method and simulate the proposed managed system. Proved by experiments, the proposed method effectively reduces both the system cost and the users’ payment, and improves the temporal distribution of the system load.
{"title":"Building-level Demand-side Energy Management Based on Game Theory","authors":"Yang Zhang, Yunfei Ma, Shuang Zhang, Lixian Chen, Hongda Liu","doi":"10.1109/ICMA54519.2022.9856118","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856118","url":null,"abstract":"In this paper, an improved building-level demand-side management method is proposed based on load classification and real-time electricity pricing. Firstly, the loads are classified into uncontrollable loads, interruptible loads and transferable loads. The uncontrollable loads are forecasted as a part of the system state. The interruptible loads are controlled all the time. The transferable loads can be managed to work in proper periods in a day. Then, the user’s electricity consumption is managed by the energy consumption controller, which solves a game problem between the user and the others. At last, we generate users’ electricity consumption conditions using the Monte Carlo method and simulate the proposed managed system. Proved by experiments, the proposed method effectively reduces both the system cost and the users’ payment, and improves the temporal distribution of the system load.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125151070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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