Renewable Energy Utilization and Natural Resource Management in the Era of Big Data
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Resources and Sustainable Utilization".
Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 229
Special Issue Editor
Special Issue Information
Dear Colleagues,
In recent times, the interest in alternative cost-effective, sustainable, and clean energy sources has increased significantly due to the technical, economical, and environmental consequences of conventional power plants. Thus, renewable energy sources, such as solar, wind, biomass, hydrogen, tidal, and geothermal, have attracted much attention and are widely utilized in power systems. Meanwhile, the existence of natural resources in abundance is important for economic growth. However, the abundance of resources is not enough as their proper exploitation is required.
Big data offers unprecedented opportunities for further development of renewable energy utilization and natural resource management. By making full use of big data, we can make smarter decisions and management choices, such as improving energy efficiency and reducing carbon emissions. The use of renewable energy and the management of natural resources have been at the forefront of using and implementing big data.
This Special Issue aims to provide a collection of articles related to trends in renewable energy utilization and natural resource management in the era of big data to share the latest research findings. Topics of interest include (but are not limited to) the following:
- Grey prediction model;
- Deep learning prediction model;
- Renewable energy sources (wind, solar, biomass, hydrogen, geothermal, tidal, hydro, etc.) forecasting;
- Renewable energy utilization;
- Natural resources (oil, natural gas, coal, etc.) forecasting;
- Natural resources utilization;
- Natural resources management;
- Energy economics and energy efficiency.
Prof. Dr. Yong Wang
Guest Editor
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- grey prediction model
- deep learning prediction model
- renewable energy sources (wind, solar, biomass, hydrogen, geothermal, tidal, hydro, etc.) forecasting
- renewable energy utilization
- natural resources (oil, natural gas, coal, etc.) forecasting
- natural resources utilization
- natural resources management
- energy economics and energy efficiency
