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.

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.

2021 ◽  
Vol 3 (1) ◽  
pp. 65-82
Author(s):  
Sören Henning ◽  
Wilhelm Hasselbring ◽  
Heinz Burmester ◽  
Armin Möbius ◽  
Maik Wojcieszak

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.


2021 ◽  
Author(s):  
Takahiro Sakai ◽  
Ryuta Imanishi ◽  
Shouma Yasuda ◽  
Hiroshi Sugimura ◽  
Masao Isshiki

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