Cloudhive: A Cloud‐Based Framework for Smart Grid Co‐Simulation, Data, and Communication

ABSTRACT The integration of renewable energy has driven the need for smart grid frameworks that enable efficient co‐simulation, data management, and secure communication. This paper introduces CloudHive, a cloud‐native framework designed to address these challenges by unifying large‐scale power‐network co‐simulation, real‐time data communication, and big data analytics in a single modular architecture. Unlike existing co‐simulation tools or data platforms that operate in isolation, CloudHive uniquely enables bidirectional interaction between simulation environments (e.g., OpenDSS for power systems, OMNeT++ for communication networks) and real‐world smart grids, supported by message‐oriented middleware (RabbitMQ, Apache Kafka) for low‐latency data exchange and Kubernetes for dynamic scalability. We evaluate CloudHive's accuracy, scalability, and usability through three representative case studies. The results show that CloudHive achieves high accuracy, performs well in real‐world scenarios, and scales efficiently with growing workloads in cloud environments.

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Publication Details

Journal
Concurrency and Computation Practice and Experience
Published
2025-08-16
DOI
https://doi.org/10.1002/cpe.70238
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
0.00

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article

Cloudhive: A Cloud‐Based Framework for Smart Grid Co‐Simulation, Data, and Communication

Kenneth B. Kent, Yan Wang, M. Zhou, Gabriel Adeyemo
Concurrency and Computation Practice and Experience
Smart Grid Security and Resilience
article

Cloudhive: A Cloud‐Based Framework for Smart Grid Co‐Simulation, Data, and Communication

Kenneth B. Kent, Yan Wang, M. Zhou, Gabriel Adeyemo
article en

Abstract

ABSTRACT The integration of renewable energy has driven the need for smart grid frameworks that enable efficient co‐simulation, data management, and secure communication. This paper introduces CloudHive, a cloud‐native framework designed to address these challenges by unifying large‐scale power‐network co‐simulation, real‐time data communication, and big data analytics in a single modular architecture. Unlike existing co‐simulation tools or data platforms that operate in isolation, CloudHive uniquely enables bidirectional interaction between simulation environments (e.g., OpenDSS for power systems, OMNeT++ for communication networks) and real‐world smart grids, supported by message‐oriented middleware (RabbitMQ, Apache Kafka) for low‐latency data exchange and Kubernetes for dynamic scalability. We evaluate CloudHive's accuracy, scalability, and usability through three representative case studies. The results show that CloudHive achieves high accuracy, performs well in real‐world scenarios, and scales efficiently with growing workloads in cloud environments.

Concurrency and Computation Practice and ExperienceVol. 37(21-22)
University of New Brunswick (CA), University of Fredericton (CA), Shenzhen Institutes of Advanced Technology (CN), University of Chinese Academy of Sciences (CN)
Chinese Academy of Sciences, Atlantic Canada Opportunities Agency
Openalex Percentile: Top 74%
Smart Grid Security and Resilience
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Cloudhive: A Cloud‐Based Framework for Smart Grid Co‐Simulation, Data, and Communication — Kenneth B. Kent, Yan Wang, et al. · Concurrency and Computation Practice and Experience (2025) | TGRS Research Map | TGRS