-, Rajni and Banerjee, Tuhin (2023) A time series analysis of renewable energy production in United States. In: 5th International Conference on Computational Intelligence and Networks (CINE), 01-03 December 2022, Bhubaneswar, India.
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Abstract
With increase in demand for electricity worldwide, the world is facing a shortage of fossil fuels for energy production. Also, use of fossil fuels has led to increase in carbon emissions and global warming leading to long term climate changes. With advancements in science and technology, renewable energy efficiency has increased which has led to many countries now adopting them as one of the means for their energy production. In this paper, we investigate the renewable energy production for the United States. A time series analysis using the exponential smoothing techniques is used for investigating the monthly data of energy production from January 1973-December 2019 and then forecast for the next 10 time-period from January 2020 to December 2020. This analysis will help to predict the demand and production of renewable energy for any region. In this investigation, the total renewable energy production is taken into consideration.
Item Type: | Conference or Workshop Item (Paper) |
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Keywords: | Renewable Energy | Time Series | Exponential Smoothing | Forecasting |
Subjects: | Social Sciences and humanities > Business, Management and Accounting > General Management |
JGU School/Centre: | Jindal Global Business School |
Depositing User: | Amees Mohammad |
Date Deposited: | 14 Feb 2023 05:57 |
Last Modified: | 09 Mar 2023 07:09 |
Official URL: | https://doi.org/10.1109/CINE56307.2022.10037293 |
URI: | https://pure.jgu.edu.in/id/eprint/5593 |
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