scholarly journals Efficiency Evaluation of the Dual System Power Inverter for On-Grid Photovoltaic System

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 161
Author(s):  
Jonas Vaicys ◽  
Povilas Norkevicius ◽  
Arturas Baronas ◽  
Saulius Gudzius ◽  
Audrius Jonaitis ◽  
...  
Keyword(s):  
Potential Benefit ◽  
Renewable Energy Sources ◽  
Dual System ◽  
Energy Utilization ◽  
Constant Current ◽  
Process Data ◽  
The Real ◽  
Digital Twin ◽  
Twin Model ◽  
System Power

The implementation of a dual electric system that is capable of operating with either constant current and variable voltage, or constant voltage and variable current appliances, is one of the possible options to solve low-intensity stochastic energy utilization problems from renewable energy sources. This research paper analyzes the potential benefit of a novel three-phase dual system power inverter over the conventional inverter used in a solar power plant. The concept of such a power inverter is explained, and the digital twin model is created in a MATLAB Simulink environment. The efficiency characteristic of the simulated inverter is compared to the efficiency characteristic of a real conventional inverter. A standalone data logging system and an additional data acquisition system were used to collect and process data from the real inverter. Comparison of the digital twin inverter and the real conventional inverter shows the potential benefit of this novel inverter technology. It is shown that the novel inverter can operate in a wider range of DC input power. The potential economic benefit is also presented and discussed in the paper.

scholarly journals Construction of Intelligent Integrated Model Framework for the Workshop Manufacturing System Via Digital Twin

2021 ◽  
Author(s):  
Zhongyu Zhang ◽  
Zhenjie Zhu ◽  
Jinsheng Zhang ◽  
Jingkun Wang
Keyword(s):  
Real Time ◽  
Production System ◽  
Manufacturing System ◽  
System Optimization ◽  
Production Cycle ◽  
Model Framework ◽  
The Real ◽  
Digital Twin ◽  
Twin Model ◽  
Information Layer

Abstract With the drastic development of the globally advanced manufacturing industry, transition of the original production pattern from traditional industries to advanced intelligence is completed with the least delay possible, which are still facing new challenges. Because the timeliness, stability and reliability of them is significantly restricted due to lack of the real-time communication. Therefore, an intelligent workshop manufacturing system model framework based on digital twin is proposed in this paper, driving the deep inform integration among the physical entity, data collection, and information decision-making. The conceptual and obscure of the traditional digital twin is refined, optimized, and upgraded on the basis of the four-dimension collaborative model thinking. A refined nine-layer intelligent digital twin model framework is established. Firstly, the physical evaluation is refined into entity layer, auxiliary layer and interface layer, scientifically managing the physical resources as well as the operation and maintenance of the instrument, and coordinating the overall system. Secondly, dividing the data evaluation into the data layer and the processing layer can greatly improve the flexible response-ability and ensure the synchronization of the real-time data. Finally, the system evaluation is subdivided into information layer, algorithm layer, scheduling layer, and functional layer, developing flexible manufacturing plan more reasonably, shortening production cycle, and reducing logistics cost. Simultaneously, combining SLP and artificial bee colony are applied to investigate the production system optimization of the textile workshop. The results indicate that the production efficiency of the optimized production system is increased by 34.46%.

Modeling and Control of Real Flow Calibration System

2020 ◽  
Author(s):  
Kai Wen
Keyword(s):  
Process Control ◽  
Calibration System ◽  
Process Data ◽  
Flow Meters ◽  
Digital Twin ◽  
Twin Model ◽  
Scada System ◽  
Human Operators ◽  
Real Flow ◽  
And Control

Abstract The calibration of large-diameter flow meters is performed in the calibration station where real flow passes through. The typical calibration process is manipulated by human operators, which is time-consuming and easily affected. Since most of the process parameters are detectable, the smart calibration system was aided by the on-line modeling process and consisted of three parts: the digital twin model, the process controller, and the human-machine interface (HMI). The digital twin model was based on the basic partial differential equations of the gas flow in pipelines and was meant for the flow behavior prediction over short periods and provided decision-making assistance for human operators. The verification of the digital model was based on both the historical process data and the real-time process data. The process controller represented the manipulator meant to replace the human operator. The function of the controller included process control and calibration flow point adjustment. The HMI was designed based on the industrial supervisory control and data acquisition (SCADA) system. Since the process control was essential, the scheduling scheme and command sequence feedback to the SCADA system was rechecked by human operators via the HMI. The result of the active control was displayed in the HMI based on the digital twin model. Since smart control was the tendency in the piping system, the automated process verification and control formed the basis of the smart system. By entering the size and range of the flow meters into the HMI, the entire industrial system inside the calibration station was executed automatically.

scholarly journals Agricultural Residue Management for Sustainable Power Generation: The Poland Case Study

2021 ◽  
Vol 11 (13) ◽  
pp. 5907
Author(s):  
Valerii Havrysh ◽  
Antonina Kalinichenko ◽  
Anna Brzozowska ◽  
Jan Stebila
Keyword(s):  
Power Generation ◽  
Spatial Distribution ◽  
Renewable Energy ◽  
Renewable Energy Sources ◽  
Agricultural Waste ◽  
Energy Utilization ◽  
Evaluation Methodology ◽  
Energy Sources ◽  
Energy Potential ◽  
Agricultural Residue

The European Union has set targets for renewable energy utilization. Poland is a member of the EU, and its authorities support an increase in renewable energy use. The background of this study is based on the role of renewable energy sources in improving energy security and mitigation of climate change. Agricultural waste is of a significant role in bioenergy. However, there is a lack of integrated methodology for the measurement of its potential. The possibility of developing an integrated evaluation methodology for renewable energy potential and its spatial distribution was assumed as the hypothesis. The novelty of this study is the integration of two renewable energy sources: crop residues and animal husbandry waste (for biogas). To determine agricultural waste energy potential, we took into account straw requirements for stock-raising and soil conservation. The total energy potential of agricultural waste was estimated at 279.94 PJ. It can cover up to 15% of national power generation. The spatial distribution of the agricultural residue energy potential was examined. This information can be used to predict appropriate locations for biomass-based power generation facilities. The potential reduction in carbon dioxide emissions ranges from 25.7 to 33.5 Mt per year.

Engine Fleet-Management: The Use of Digital Twins From a MRO Perspective

2017 ◽  
Author(s):  
Joern Kraft ◽  
Stefan Kuntzagk
Keyword(s):  
Multilevel Models ◽  
Operating Cost ◽  
Maintenance Cost ◽  
Fleet Management ◽  
Component Level ◽  
The Real ◽  
Digital Twin ◽  
Digital Twins ◽  
The Individual ◽  
Life Consumption

Engine operating cost is a major contributor to the direct operating cost of aircraft. Therefore, the minimization of engine operating cost per flight-hour is a key aspect for airlines to operate successfully under challenging market conditions. The interaction between maintenance cost, operating cost, asset value, lease and replacement cost describes the area of conflict in which engine fleets can be optimized. State-of-the-art fleet management is based on advanced diagnostic and prognostic methods on engine and component level to provide optimized long-term removal and work-scoping forecasts on fleet level based on the individual operation. The key element of these methods is a digital twin of the active engines consisting of multilevel models of the engine and its components. This digital twin can be used to support deterioration and failure analysis, predict life consumption of critical parts and relate the specific operation of a customer to the real and expected condition of the engines on-wing and at induction to the shop. The fleet management data is constantly updated based on operational data sent from the engines as well as line maintenance and shop data. The approach is illustrated along the real application on the CFM56-5C, a mature commercial two-spool high bypass engine installed on the Airbus A340-300. It can be shown, that the new methodology results in major improvements on the considered fleets.

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