Achieving the quantum advantage across smart grid: delineating challenges, opportunities, and future crosswalks

Quantum computing (QC) has established itself as a disruptive technology that has the potential to enhance computational capabilities across next-generation energy systems. Its integration into smart grids can enable intelligent decision-making, secure control mechanisms, and advanced optimization strategies. However, existing research remains methodologically fragmented and lacks a unified discussion for practical adoption. This highlights the need for a systematic assessment of the current research landscape to establish structured pathways for effective integration. To address this gap, we have presented a scientometric review that examines the intersection of QC and smart grids based on 133 articles published between 2020 and 2025. The study investigates publication trends, keyword co-occurrence networks, and centrality–density interactions to trace the intellectual evolution of Quantum-enabled Smart Grids (QmSGs). The findings identify post-quantum cryptography and quantum key distribution as dominant motor themes within the field. In parallel, emerging research frontiers include hybrid quantum–classical optimization, federated quantum learning, and AI-driven quantum energy management. The thematic analysis reveals several critical challenges, including scalability constraints, interoperability gaps, and the lack of standardized benchmarking frameworks. Based on these insights, we have proposed a forward-looking research pathway that highlights actionable opportunities for future development. In particular, stronger integration efforts are needed in areas such as explainable quantum learning, adaptive resource orchestration, and sustainable grid governance. These insights can help to enhance the practical relevance and understanding of the field.

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Publication Details

Journal
Artificial Intelligence Review
Published
2026-07-28
DOI
https://doi.org/10.1007/s10462-026-11642-2
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Achieving the quantum advantage across smart grid: delineating challenges, opportunities, and future crosswalks

Keshav Singh Rawat, Tarun Sharma
Artificial Intelligence Review
Smart Grid Energy Management
article

Achieving the quantum advantage across smart grid: delineating challenges, opportunities, and future crosswalks

Keshav Singh Rawat, Tarun Sharma
article en

Abstract

Quantum computing (QC) has established itself as a disruptive technology that has the potential to enhance computational capabilities across next-generation energy systems. Its integration into smart grids can enable intelligent decision-making, secure control mechanisms, and advanced optimization strategies. However, existing research remains methodologically fragmented and lacks a unified discussion for practical adoption. This highlights the need for a systematic assessment of the current research landscape to establish structured pathways for effective integration. To address this gap, we have presented a scientometric review that examines the intersection of QC and smart grids based on 133 articles published between 2020 and 2025. The study investigates publication trends, keyword co-occurrence networks, and centrality–density interactions to trace the intellectual evolution of Quantum-enabled Smart Grids (QmSGs). The findings identify post-quantum cryptography and quantum key distribution as dominant motor themes within the field. In parallel, emerging research frontiers include hybrid quantum–classical optimization, federated quantum learning, and AI-driven quantum energy management. The thematic analysis reveals several critical challenges, including scalability constraints, interoperability gaps, and the lack of standardized benchmarking frameworks. Based on these insights, we have proposed a forward-looking research pathway that highlights actionable opportunities for future development. In particular, stronger integration efforts are needed in areas such as explainable quantum learning, adaptive resource orchestration, and sustainable grid governance. These insights can help to enhance the practical relevance and understanding of the field.

Artificial Intelligence Review
University of Delhi (IN), Central University of Haryana (IN)
Openalex Percentile: Top 16%
Smart Grid Energy Management
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