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Leveraging Artificial Intelligence to Bolster the Energy Sector in Smart Cities: A Literature Review

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Camacho, José de Jesús, Aguirre, Bernabé, Ponce, Pedro, Anthony, Brian, Molina, Arturo·2024·Energies
DOI 10.3390/en17020353
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Abstract

As Smart Cities development grows, deploying advanced technologies, such as the Internet of Things (IoT), Cyber–Physical Systems, and particularly, Artificial Intelligence (AI), becomes imperative for efficiently managing energy resources. These technologies serve to coalesce elements of the energy life cycle. By integrating smart infrastructures, including renewable energy, electric vehicles, and smart grids, AI emerges as a keystone, improving various urban processes. Using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and the Scopus database, this study meticulously reviews the existing literature, focusing on AI technologies in four principal energy domains: generation, transmission, distribution, and consumption. Additionally, this paper shows the technological gaps when AI is implemented in Smart Cities. A total of 122 peer-reviewed articles are analyzed, and the findings indicate that AI technologies have led to remarkable advancements in each domain. For example, AI algorithms have been employed in energy generation to optimize resource allocation and predictive maintenance, especially in renewable energy. The role of AI in anomaly detection and grid stabilization is significant in transmission and distribution. Therefore, the review outlines trends, high-impact articles, and emerging keyword clusters, offering a comprehensive analytical lens through which the multifaceted applications of AI in Smart City energy sectors can be evaluated. The objective is to provide an extensive analytical framework that outlines the AI techniques currently deployed and elucidates their connected implications for sustainable development in urban energy. This synthesis is aimed at policymakers, urban planners, and researchers interested in leveraging the transformative potential of AI to advance the sustainability and efficiency of Smart City initiatives in the energy sector.

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  • Entities or communication channels that were once controlled by humans are increasingly becoming AI-powered.

    “From business communication systems and financial trading networks to smart energy grids and logistical networks (Camacho et al., 2024; Ferreira et al., 2021; Mayorkas, 2024), entities or communication channels that were once controlled by humans are increasingly becoming AI-powered.”

    From Multi-Agent Risks from Advanced AI (2025) · cites this paper as Camacho et al., 2024

    The Introduction and §4.5 (Research Gaps) describe AI applications in energy-grid control and smart-grid management, supporting the smart-energy-grid example. The paper does not establish that these grids were previously controlled by humans or document a transition from human to AI control; the other sectors in the sentence are not the apparent subject of this citation. (LLM, conf=0.83)

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Cited by

Sorted by citations

Authors
Camacho, J. D. J., Aguirre, B., Ponce, P., Anthony, B., & Molina, A.
Affiliations
  • Institute of Advanced Materials for Sustainable Manufacturing, Tecnológico de Monterrey, Monterrey 64849, Mexico
  • Tecnológico de Monterrey (MX)
  • Massachusetts Institute of Technology (US)
Corresponding author
Ponce, Pedro
ORCID
Venue
Energies
Publisher
MDPI AG
Published
2024-01-10
Volume
17
Issue
2
Pages
353
ISSN
1996-1073 (ISSN-L)
DOI
10.3390/en17020353
OpenAlex
W4390702006
Cited by
42
References
4
Citations by year
2026: 15 · 2025: 19 · 2024: 8
FWCI
6.91
Type
journal article
Language
en
Open access
Licence
Locations
  • Energies (publishedVersion, cc-by)
  • RePEc: Research Papers in Economics (acceptedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Institute of Advanced Materials for Sustainable Manufacturing at Tecnologico de Monterrey
Topics
  • Physical Sciences › Engineering › Media Technology › Smart Cities and Technologies
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid and Power Systems
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
Keywords
artificial intelligence, smart cities, urban energy management, energy production, energy transmission, energy distribution, energy consumption, renewable energy, electric vehicles, smart grid, predictive maintenance, anomaly detection, grid stabilization, Internet of Things, cyber-physical systems, sustainable urban development

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