Research on Line and Transformer Relationship Identification Based on Limited Power Consumption Data

2021 ◽  
Author(s):  
Hong Wang ◽  
Qian Chen ◽  
Wei Ma ◽  
Hu Fei-Hu ◽  
Jean Leonard Habinshuti
Keyword(s):  
Power Consumption ◽  
Consumption Data ◽  
On Line ◽  
Limited Power ◽  
Relationship Identification

scholarly journals Goals and measures for analyzing power consumption data in manufacturing enterprises

2021 ◽  
Vol 3 (1) ◽  
pp. 65-82
Author(s):  
Sören Henning ◽  
Wilhelm Hasselbring ◽  
Heinz Burmester ◽  
Armin Möbius ◽  
Maik Wojcieszak
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Manufacturing Industry ◽  
Fog Computing ◽  
Electrical Power ◽  
Time Data ◽  
Manufacturing Enterprises ◽  
Computing Paradigm ◽  
Consumption Data ◽  
Analyzing Power

AbstractThe Internet of Things adoption in the manufacturing industry allows enterprises to monitor their electrical power consumption in real time and at machine level. In this paper, we follow up on such emerging opportunities for data acquisition and show that analyzing power consumption in manufacturing enterprises can serve a variety of purposes. In two industrial pilot cases, we discuss how analyzing power consumption data can serve the goals reporting, optimization, fault detection, and predictive maintenance. Accompanied by a literature review, we propose to implement the measures real-time data processing, multi-level monitoring, temporal aggregation, correlation, anomaly detection, forecasting, visualization, and alerting in software to tackle these goals. In a pilot implementation of a power consumption analytics platform, we show how our proposed measures can be implemented with a microservice-based architecture, stream processing techniques, and the fog computing paradigm. We provide the implementations as open source as well as a public show case allowing to reproduce and extend our research.

Research on the Visualization of Living Conditions from the Power Consumption Data using the ECHONET Lite Standard

2021 ◽  
Author(s):  
Takahiro Sakai ◽  
Ryuta Imanishi ◽  
Shouma Yasuda ◽  
Hiroshi Sugimura ◽  
Masao Isshiki
Keyword(s):  
Power Consumption ◽  
Living Conditions ◽  
Consumption Data

scholarly journals A Tool for Energy Consumption Monitoring and Analysis of the Android Terminal

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Deguang Li ◽  
Zhanyou Cui ◽  
Chenguang Bai ◽  
Qiurui He ◽  
Xiaoting Yan
Keyword(s):  
Power Consumption ◽  
Rapid Development ◽  
Mobile Terminal ◽  
Power Model ◽  
Power Modeling ◽  
Application Layer ◽  
Consumption Data ◽  
Android Platform ◽  
Instrument Measurement ◽  
Original Information

With the rapid development of communication technology, the intelligent mobile terminal brings about great convenience to people’s life with rich applications, while its power consumption has become a great concern to researchers and consumers. Power modeling is the basis to understand and analyze the power consumption characteristics of the terminal. In this paper, we analyze the Bluetooth and hidden power consumption of the android platform and fix the power model of open-source Android platform. Then, a power consumption monitoring tool is implemented based on the model; the tool is divided into three layers, which are original information monitor layer, power consumption calculation layer, and application layer. The original monitor layer gets the power consumption data and running time of the different components under different states, the calculation layer calculates the power consumption of each hardware and each application based on the power model of each component, and the application layer displays the real-time power consumption of the software and hardware. Finally, we test our tool in real environment by using Xiaomi 9 Pro and perform comparison with actual instrument measurement; the error between the monitored value and the measured value is less than 5%.

scholarly journals Complex statistical data analysis of electric power consumption, consumption of energy resources and production volumes

2020 ◽  
pp. 22-28
Author(s):  
А. Voloshko ◽  
Ya. Bederak ◽  
T. Dzheria
Keyword(s):  
Statistical Analysis ◽  
Power Consumption ◽  
Electric Power ◽  
Distribution Systems ◽  
Energy Resources ◽  
Compressed Air ◽  
Electric Power Consumption ◽  
Supply And Distribution ◽  
Consumption Data ◽  
Complex Statistical Analysis

Aims of this research are development of a complex statistical analysis algorithm for active electric power consumption data, consumption of energy resources and manufacturing products, implementation of statistical analysis in practice. Proposed parameters and criteria, which can help to technical staff in factories, to provide optimal and economical operating of supply and distribution systems as electricity, water, gas, heat, compressed air, etc. for production facilities, based on the collected active electric power consumption data for previous periods, information about consumption dynamic. It is concluded that the statistical analysis of the data, obtained for each type of engineering equipments (water supply and sewage, supply systems of compressed air, gas, electricity and steam) and various consumables coefficients (in the proposed algorithm) make possible to identify "weak areas" and to determine the most rational ways to optimize energy usage.

scholarly journals Efficient Planning of Electrical Distribution System for Consumers in Sarawak, Malaysia

2014 ◽  
Vol 72 (1) ◽  
Author(s):  
Ibrahim S.H. ◽  
Baharun A. ◽  
Nawi M.N.M ◽  
Chai C.J.
Keyword(s):  
Power Consumption ◽  
Distribution System ◽  
Load Distribution ◽  
Consumption Pattern ◽  
Load Factor ◽  
Cluster Sampling ◽  
Distribution Transformer ◽  
Consumption Data ◽  
Efficient Planning ◽  
Load Characteristics

This study presents a method to determine power consumption pattern for several types of consumers in Sarawak, Malaysia. The power consumption data for consumers has been recorded using EDMI Mk.6 Genius polyphase electronic (E3) meters installed at their premises. The multistage cluster sampling is used to design the sample size to determine the sufficient amount of meters required. The data obtained from the meters has been analysed to obtain the pattern of power consumption for different types of consumers. This power consumption pattern has been applied to determine load factor, diversity factor for the calculation of After Diversity Maximum Demand (ADMD). ADMD is also used to determine the optimal amount of load, distribution transformer size and 11kV cable size. Temperature sensitivity analysis related to the demand has been investigated as well. It is found that power consumption pattern model is beneficial in finding the total electrical load, distribution transformer size and 11kV cable size needed by the consumers. Thus through this study the load characteristics had been determined to support utility operation and planning efficiently.

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