Academic Journal

Analytics framework for optimal smart meters data processing.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Analytics framework for optimal smart meters data processing.
Συγγραφείς: Alquthami, Thamer, AlAmoudi, Ahmed, Alsubaie, Abdullah M., Jaber, Abdulrahman Bin, Alshlwan, Nassir, Anwar, Murad, Al Husaien, Shafi
Πηγή: Electrical Engineering; Sep2020, Vol. 102 Issue 3, p1241-1251, 11p
Θεματικοί όροι: Smart meters, Electronic data processing, Load forecasting (Electric power systems), Visual analytics, Structural frames, Test validity
Περίληψη: Utilities around the world have realized the importance of wide installation smart meters (SMs) as they are considered to be a corner stone of any step toward grid modernization. These meters are expected to rely on to improve gird reliability, efficiency and enhance grid economic operation. With large rate of SMs integration, flood of smart meter data is being gathered on hourly basis. This paper presents an integrated data framework that incorporates tools and data preprocessing techniques for SM data analytics. This framework uses real data of smart meters installed by the Saudi Electricity Company (SEC) and is for different load profiles, such as residential, governmental, commercial, agriculture and industrial. The developed framework receives raw data from SM, preprocess it and then performs the required analysis using the applications layer. Benefits of such a framework are many: standardized data streamlining, unified different data spectrum and at the end create a trustworthy and validated real-based data that can be used to execute many of smart grid applications. This paper describes the structure of the framework, the function of each component and then presents results of several applications to test the validity and performance of the framework. [ABSTRACT FROM AUTHOR]
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Βάση Δεδομένων: Complementary Index