Assessment of green hydrogen production by volatile renewable energy under different SSPs scenarios in China

• Published in: Renewable energy 2024-11, Vol.235, p.121296, Article 121296
• Main Authors: Liu, Bingchun, Lai, Mingzhao, Wang, Yajie, Wang, Yibo, Chen, Jiali, Song, Chengyuan
• Format: Article
• Language: English
• Subjects: Climate change; Deep learning; Green hydrogen; Hydrogen technology in energy storage; Renewable energy
• ISSN: 0960-1481
• DOI: 10.1016/j.renene.2024.121296

In the context of increasing global concerns about climate change and sustainable energy, the production of green hydrogen (GH) from volatile renewable energy (VRE) sources, such as solar and wind, is a natural choice for China to meet its climate change mitigation goals. However, there are a number of challenges in current research on the assessment of green hydrogen potential. This study evaluates the potential of GH production through VRE at the regional level in China, under the various scenarios of Shared Socioeconomic Pathways (SSPs). For this purpose, a power generation prediction model suitable for VRE is proposed to predict the energy supply capacity for GH production in six regions of China, which combined Multilevel Discrete Wavelet Decomposition and Bi-directional Long Short-Term Memory with attention mechanism (MDWD - AMBiLSTM). The total amount of GH could potentially reach up to 428.01 Mt under the SSP1, with the northern region leading at the regional level at 104.21 Mt. Furthermore, the study evaluated the potential for GH promotion in six regions of China between 2023 and 2035 b y combining the three dimensions of GH production potential, economic evaluation, and environmental contribution. This study tentative identify priority areas and development scenarios for promoting GH production in China, and made policy recommendations for the promotion of green hydrogen in disparate areas.