scholarly journals Application of Digital Twin Technology in Energy and Power Industry

2021 ◽  
Vol 2108 (1) ◽  
pp. 012040
Author(s):  
Xueqing Liang ◽  
Shuming Du ◽  
Xiaofan Zhao ◽  
Chao Liu
Keyword(s):  
Energy Demand ◽  
Building Energy ◽  
Power Industry ◽  
Duty Ratio ◽  
Physical Entity ◽  
Control Effect ◽  
Digital Twin ◽  
Adaptive Pid Control ◽  
And Control ◽  
Fuzzy Adaptive

Abstract Constructing digital twin of physical entity and analyzing twin data, and transfer learning method can be used to transfer the characteristics of twin to physical entity for analysis. This paper mainly studies the application of digital twinning technology in the energy and power industry. Aiming at the energy saving and control problem of building energy demand terminal, the fuzzy adaptive PID control algorithm is used to simulate the indoor HVAC system and lighting system, so as to solve the indoor temperature and illumination intensity are greatly affected by the weather, time-varying and unpredictable factors. By comparing with the conventional PID, we can see that the fuzzy adaptive PID controller adjusts faster, the output duty ratio is more accurate, and can achieve better control effect.

Research on Intelligent Soft Starting Method for Three-Phase Asynchronous Motor Based on MATLAB

2011 ◽  
Vol 299-300 ◽  
pp. 828-831
Author(s):  
Yan Feng Zhu
Keyword(s):  
Pid Control ◽  
Control Method ◽  
Design Method ◽  
Asynchronous Motor ◽  
Control Effect ◽  
Starting Current ◽  
Soft Starter ◽  
Three Phase ◽  
Adaptive Pid Control ◽  
Fuzzy Adaptive

Considering the very large direct starting current of three-phase asynchronous motor, this paper presents a design method of asynchronous motor soft starter based on a intelligent control- fuzzy adaptive PID control. The simulation model of the soft starting control system is established with the power system blockset in MATLAB/SIMULINK software. The simulation results show that the fuzzy adaptive PID control method can effectively limit the motor starting current and it is better than the control effect of traditional PID control. Therefore, the fuzzy adaptive PID control scheme presented in this paper is correct and feasible.

Study on the Electro-Hydraulic Power Steering System Based on AMESim and Simulink

2011 ◽  
Vol 422 ◽  
pp. 610-613 ◽  
Author(s):  
Wen Chang Lu ◽  
Geng Sen Niu ◽  
Chen Long ◽  
Ruo Chen Wang
Keyword(s):  
Steering System ◽  
Power Steering System ◽  
Integrated Simulation ◽  
Power Steering ◽  
Mechanical Dynamics ◽  
Adaptive Pid Control ◽  
And Control ◽  
Hydraulic Power Steering System ◽  
Hydraulic Power Steering ◽  
Fuzzy Adaptive

In this paper, the model of EHPS is built on AMESim and MATLAB / Simulink software platform, co-simulation is carried out in the AMESim and Simulink integrated simulation environment with the use of fuzzy adaptive PID control strategy. The results show that EHPS mechanical dynamics model and control algorithm in the paper are correct.

scholarly journals Digital Twin: Origin to Future

2021 ◽  
Vol 4 (2) ◽  
pp. 36
Author(s):  
Maulshree Singh ◽  
Evert Fuenmayor ◽  
Eoin Hinchy ◽  
Yuansong Qiao ◽  
Niall Murray ◽  
...  
Keyword(s):  
Real Time ◽  
Remote Access ◽  
Physical Entity ◽  
Industrial Systems ◽  
Digital Twin ◽  
Planning Optimization ◽  
Different Types ◽  
Pros And Cons ◽  
Number Of Publications ◽  
Digital Shadow

Digital Twin (DT) refers to the virtual copy or model of any physical entity (physical twin) both of which are interconnected via exchange of data in real time. Conceptually, a DT mimics the state of its physical twin in real time and vice versa. Application of DT includes real-time monitoring, designing/planning, optimization, maintenance, remote access, etc. Its implementation is expected to grow exponentially in the coming decades. The advent of Industry 4.0 has brought complex industrial systems that are more autonomous, smart, and highly interconnected. These systems generate considerable amounts of data useful for several applications such as improving performance, predictive maintenance, training, etc. A sudden influx in the number of publications related to ‘Digital Twin’ has led to confusion between different terminologies related to the digitalization of industries. Another problem that has arisen due to the growing popularity of DT is a lack of consensus on the description of DT as well as so many different types of DT, which adds to the confusion. This paper intends to consolidate the different types of DT and different definitions of DT throughout the literature for easy identification of DT from the rest of the complimentary terms such as ‘product avatar’, ‘digital thread’, ‘digital model’, and ‘digital shadow’. The paper looks at the concept of DT since its inception to its predicted future to realize the value it can bring to certain sectors. Understanding the characteristics and types of DT while weighing its pros and cons is essential for any researcher, business, or sector before investing in the technology.

scholarly journals Overcapacity Risk of China’s Coal Power Industry: A Comprehensive Assessment and Driving Factors

2021 ◽  
Vol 13 (3) ◽  
pp. 1426
Author(s):  
Delu Wang ◽  
Xun Xue ◽  
Yadong Wang
Keyword(s):  
Evaluation Model ◽  
Supply And Demand ◽  
Correlation Effect ◽  
Power Industry ◽  
Environmental Benefits ◽  
Risk Level ◽  
Correlation Based Feature Selection ◽  
Coal Power ◽  
And Control ◽  
The Impact

The comprehensive and accurate monitoring of coal power overcapacity is the key link and an important foundation for the prevention and control of overcapacity. The previous research fails to fully consider the impact of the industry correlation effect; making it difficult to reflect the state of overcapacity accurately. In this paper; we comprehensively consider the fundamentals; supply; demand; economic and environmental performance of the coal power industry and its upstream; downstream; competitive; and complementary industries to construct an index system for assessing coal power overcapacity risk. Besides; a new evaluation model based on a correlation-based feature selection-association rules-data envelopment analysis (CFS-ARs-DEA) integrated algorithm is proposed by using a data-driven model. The results show that from 2008 to 2017; the risk of coal power overcapacity in China presented a cyclical feature of “decline-rise-decline”, and the risk level has remained high in recent years. In addition to the impact of supply and demand; the environmental benefits and fundamentals of related industries also have a significant impact on coal power overcapacity. Therefore; it is necessary to monitor and govern coal power overcapacity from the overall perspective of the industrial network, and coordinate the advancement of environmental protection and overcapacity control.

scholarly journals A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 156
Author(s):  
Paige Wenbin Tien ◽  
Shuangyu Wei ◽  
John Calautit
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Energy Demand ◽  
Energy Savings ◽  
Internal Heat ◽  
Electrical Equipment ◽  
Building Energy ◽  
Hvac Systems ◽  
Equipment Usage

Because of extensive variations in occupancy patterns around office space environments and their use of electrical equipment, accurate occupants’ behaviour detection is valuable for reducing the building energy demand and carbon emissions. Using the collected occupancy information, building energy management system can automatically adjust the operation of heating, ventilation and air-conditioning (HVAC) systems to meet the actual demands in different conditioned spaces in real-time. Existing and commonly used ‘fixed’ schedules for HVAC systems are not sufficient and cannot adjust based on the dynamic changes in building environments. This study proposes a vision-based occupancy and equipment usage detection method based on deep learning for demand-driven control systems. A model based on region-based convolutional neural network (R-CNN) was developed, trained and deployed to a camera for real-time detection of occupancy activities and equipment usage. Experiments tests within a case study office room suggested an overall accuracy of 97.32% and 80.80%. In order to predict the energy savings that can be attained using the proposed approach, the case study building was simulated. The simulation results revealed that the heat gains could be over or under predicted when using static or fixed profiles. Based on the set conditions, the equipment and occupancy gains were 65.75% and 32.74% lower when using the deep learning approach. Overall, the study showed the capabilities of the proposed approach in detecting and recognising multiple occupants’ activities and equipment usage and providing an alternative to estimate the internal heat emissions.

Pressing speed stability control of a special ceramic roller bearing press based on fuzzy adaptive PID

2021 ◽  
pp. 1-16
Author(s):  
Lijie Yang ◽  
Guimei Wang ◽  
Huadong Zhang ◽  
Jiehui Liu ◽  
Yachun Zhang
Keyword(s):  
Pid Control ◽  
Simulation Analysis ◽  
Roller Bearing ◽  
Speed Control ◽  
Stability Control ◽  
Interference Signal ◽  
Ceramic Roller ◽  
Speed Stability ◽  
Adaptive Pid Control ◽  
Fuzzy Adaptive

A special ceramic roller bearing press (SCRBP) is developed to press two bearings efficiently and precisely at the same time. A speed control mathematical model of the bearing press is built to obtain stability bearing pressing speed. The fuzzy adaptive PID controller of the bearing pressing speed of SCRBP is designed. The simulation model is also built. Fuzzy adaptive PID control is compared with conventional PID control. By simulation analysis, the simulation results show that adjusting time of fuzzy adaptive PID control is short, and its overshoot is very small, almost coincides with the set pressing speed. Moreover, fuzzy adaptive PID is suitable for the pressing speed control of the bearing pressing speed system with step interference signal. The pressing stability speed is obtained by fuzzy adaptive PID control.

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