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Sustainability, AI and the Evolution of Energy Infrastructure: Understanding the Intersection of Economics, Environment, and Society

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: 31 January 2026 | Viewed by 1184

Special Issue Editors

School of Economics, Hefei University of Technology, Hefei, China
Interests: carbon peaking and carbon neutral policies; energy and environment; economic development quality evaluation
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Economics, Hefei University of Technology, Hefei 230601, China
Interests: energy and environment policy analysis; enterprise green transformation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the age of artificial intelligence (AI), energy infrastructure is undergoing significant transformation since AI technologies hold great promise in terms of optimizing energy systems, enhancing efficiency, and integrating renewable energy sources more effectively. However, these technological advancements bring with them a complex set of economic, environmental, and social impacts. Understanding how AI influences energy infrastructure—both in terms of operational performance and broader societal implications—is crucial. While AI can drive economic growth, reduce environmental footprints, and improve energy accessibility, it also poses challenges, including potential job displacement, issues of equity, and the digital divide. This research area aims to investigate the multifaceted impacts of AI on energy infrastructure, offering insights into how these technologies can shape a sustainable and inclusive future.

The aim of this Special Issue is to explore the economic, environmental, and social impacts of AI on energy infrastructure. It will examine how AI technologies can optimize energy systems, improve efficiency, and enable renewable energy integration, while addressing challenges such as equity and social inclusion. This topic aligns with the journal’s scope by contributing to the understanding of how technological advancements, like AI, can shape sustainable and resilient energy systems, fostering innovation and addressing global sustainability challenges.

In this Special Issue, original research articles and reviews are welcome and research areas may include, but are not limited to:

  • AI in energy system optimization;
  • The economic impacts of AI on the energy markets;
  • AI and renewable energy integration;
  • Social impacts: equity and access to energy;
  • Environmental benefits and challenges;
  • AI and smart grids;
  • AI for energy storage and demand response;
  • The regulatory and policy implications of AI in energy;
  • AI, job displacement, and social transformation;
  • The environmental and economic impacts of energy infrastructure.

We look forward to receiving your contributions.  

Dr. Tao Ding
Prof. Dr. Ruipeng Tan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

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

  • artificial intelligence (AI)
  • energy infrastructure
  • economic impacts
  • renewable energy integration
  • smart grids
  • energy efficiency
  • environmental sustainability
  • social equity
  • energy transition
  • AI-driven optimization

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Published Papers (1 paper)

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Research

20 pages, 825 KiB  
Article
The Impact of Electricity Grid Development on Economic Growth and Energy Consumption in Anhui Province: A Seemingly Unrelated Regression-Based Analysis
by Xiaomin Shi, Xiang Gao, Rong Li, Ke Hou, Yang Song and Zhongjiang Lu
Sustainability 2025, 17(7), 3193; https://doi.org/10.3390/su17073193 - 3 Apr 2025
Viewed by 699
Abstract
Endogeneity is an important issue that needs to be addressed in research. By integrating infrastructure into the input–output system based on a profit function framework, this paper investigates the impact of electricity infrastructure on economic development and energy consumption. Using city-level data from [...] Read more.
Endogeneity is an important issue that needs to be addressed in research. By integrating infrastructure into the input–output system based on a profit function framework, this paper investigates the impact of electricity infrastructure on economic development and energy consumption. Using city-level data from Anhui Province spanning 2012 to 2022 and applying seemingly unrelated regression techniques for parameter estimation, this study finds that an increase in grid density leads to a reduction in energy consumption. While the short-term effect of increased grid density may cause a decline in output, a positive long-term effect on output is observed. This study concludes that the advantages of robust power infrastructure in lowering energy intensity manifest only over an extended time horizon. Based on our findings, we provide relevant recommendations that can be applied to other regions as well. Full article
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