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By: Gaurav Mahendra Keshari, Saad Nasser Ansari, and Kshitij Navale.
1- Student, Department of Artificial Intelligence, Shri Vile Parle Kelavani Mandal (SVKM) Narsee Monjee Institute of Management Studies (NMIMS), Navi Mumbai, Maharashtra, India
2- Student, Department of Artificial Intelligence, Shri Vile Parle Kelavani Mandal (SVKM) Narsee Monjee Institute of Management Studies (NMIMS), Navi Mumbai, Maharashtra, India
3- Student, Department of Artificial Intelligence, Shri Vile Parle Kelavani Mandal (SVKM) Narsee Monjee Institute of Management Studies (NMIMS), Navi Mumbai, Maharashtra, India
This paper reviews eight research studies on smart grids and their role in mitigating greenhouse gas (GHG) emissions, which have become a critical concern worldwide. Renewable energy sources such as solar, wind, and hydro produce minimal or no greenhouse gases and, unlike fossil fuels, are abundant, sustainable, and ensure a long-term energy supply. Large volumes of data have been produced by recent technical developments and thorough historical data collection. Efficient data utilization in the energy sector and smart grids are crucial for providing accurate forecasts and innovative solutions. Big data analytics offers powerful tools for researchers and practitioners to analyze and interpret this information. This review provides insights into the analytical methods of big data in the renewable energy domain, enabling researchers and practitioners to identify the most suitable analysis techniques based on their specific data and research objectives.
Keywords: Big data, descriptive analysis, diagnostic analysis, predictive analysis, prescriptive analysis.
Citation:
Refrences:
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