Big Data Analytics in Smart Energy Systems and Networks: A Review

Morteza Ghasemi () and Mohammad Sadra Rajabi ()
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Morteza Ghasemi: University of Tehran
Mohammad Sadra Rajabi: University of Tehran

A chapter in Handbook of Smart Energy Systems, 2023, pp 3201-3215 from Springer

Abstract: Abstract The increase in greenhouse gases (GHGs) in the world becomes more critical over time. One of the most effective dependent parameters of this problem is fossil energy use and the lack of efficient decision-support systems. The Kyoto Protocol and Paris Agreement are two examples of international agreements to limit global warming and counter emissions. Using renewable energy, managing energy consumption, and increasing its productivity are the most crucial solutions to this problem. With the passage of time and the advancement of technology, the volume and quality of historical data collection have expanded and the optimal use of this volume of data plays a key role in accurate and innovative forecasts in the energy industry and smart grids. The purpose of this chapter is to provide a review of the analytical methods of big data for researchers and practitioners while familiarizing themselves with these analyses (Descriptive, Diagnostic, Predictive, Prescriptive) so that they can determine and implement the best analysis according to their data and research objectives.

Keywords: Big data; Descriptive analysis; Diagnostic analysis; Predictive analysis; Prescriptive analysis (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-97940-9_203

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DOI: 10.1007/978-3-030-97940-9_203

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