Integrating the IoT and New Energy to Promote a Sustainable Low-Carbon Economy
This study explores the complex interaction between the Internet of Things (IoT) and the new energy sector and analyzes how their integration can catalyze a transition toward a sustainable low-carbon economy. Through the full-sample and rolling sub-sample methods, we empirically examine the dynamic interrelationship between China’s IoT index (IoT) and the New Energy Index (NEI). Quantitative analysis reveals significant time-varying characteristics and bidirectional causal complexity in the interaction between the IoT and new energy. The IoT has a dual-edged impact on the development of new sources of energy. In the long run, the IoT plays a dominant role in incentivizing new energy, helping to enhance its stability and economic value. However, during stages characterized by technological bottlenecks or resource competition, the high energy consumption of IoT infrastructure may suppress the investment returns of new energy. Simultaneously, new energy has both positive and negative impacts on the IoT. On the one hand, new energy provides low-cost, sustainable power to support the IoT, driving the construction of the IoT ecosystem. On the other hand, it may threaten the continuity of IoT power supply, and the complexity of standardization and regulation in the sector may constrain the development of the IoT. This study provides a fresh perspective on promoting the integration of digital technology and green energy, uncovering nonlinear trade-offs between innovation-driven growth and carbon reduction goals, and offering policy insights for cross-sectoral collaboration to achieve sustainability.
Authors
- Jiayi Lyu (ORCID: https://orcid.org/0000-0001-8517-3346)
- Yan Chen (ORCID: https://orcid.org/0000-0003-2827-3660)
- Yuqi Hou
Institutions
- Beijing University of Posts and Telecommunications (CN)
Publication Details
- Journal
- Sustainability
- Published
- 2025-07-24
- DOI
- https://doi.org/10.3390/su17156755
- Citations
- 1
- Primary Topic
- Smart Grid Energy Management
- Type
- article
- Field-Weighted Citation Impact
- 0.73
Funders
- Swansea University
- National Natural Science Foundation of China
- Chinese Academy of Engineering