AUTHOR=Liu Bingchun , Chen Jiali , Wang Hui , Wang Qingshan TITLE=Renewable Energy and Material Supply Risks: a Predictive Analysis Based on An LSTM Model JOURNAL=Frontiers in Energy Research VOLUME=8 YEAR=2020 URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2020.00163 DOI=10.3389/fenrg.2020.00163 ISSN=2296-598X ABSTRACT=

In response to climate change and continued reliance on traditional high-carbon fossil fuels, promoting the transition toward sustainable energy systems by development of low-carbon energy resources has been seen as the main strategy for mitigating and solving global climate change. However, the promotion of low-carbon energy also faces material supply risks. To provide a reference for the steady and rapid development of renewable energy and other energy in the future energy market, this paper considers renewable energy prediction based on a long- and short-term memory network model as well as the growth rate changes of crude oil, natural gas, nuclear energy, financial revenues, and expenditure. In the prediction process, it is found that natural gas will be a strong competitor for the development of renewable energy in the future. When natural gas grows too quickly, the growth of renewable energy will be negative. On the other hand, when the monthly growth rate of natural gas and crude oil is smaller than that of nuclear energy, renewable energy will display a growth trend, and the rate will increase with the growth of natural gas and nuclear energy. What is more, wind and solar energy will be limited by metallic materials, such as Dy, Nd, Te, and In. Improving the energy density of metals plays a key role in China’s transition to a low-carbon energy structure.