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Domain-Specific Cloud Business Operating System for New Power Systems: Concept, Key Technologies and Initial Applications

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Domain-Specific Cloud Business Operating System for New Power Systems: Concept, Key Technologies and Initial Applications

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School of Electric Power, South China University of Technology, Guangzhou 510641, China
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Received: 17 November 2025 Revised: 05 January 2026 Accepted: 03 March 2026 Published: 16 March 2026

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© 2026 The authors. This is an open access article under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

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Smart Energy Syst. Res. 2026, 2(1), 10004; DOI: 10.70322/sesr.2026.10004
ABSTRACT: The deep digitization of power system business faces three major challenges: computational resources are prone to crashes, business response is slow, and platform maintenance is unsustainable. To address these issues, this paper proposes a domain-specific cloud Business Operating System (BOS) for new power systems. BOS establishes a unified management paradigm for four core digital objects—Containers, Tasks, Programs, and Data—through their standardized definition and indexed organization. Building upon this foundation, it implements three dedicated plugins to enable synergistic task-container co-scheduling, plug-and-play program integration, and optimized data access. This paper elaborates on BOS’s architecture and its rationale as an operating system, detailing the key technologies for object management. Case studies on a real-world regional power grid demonstrate that BOS effectively ensures the efficient execution of large-scale computational tasks, supports the agile integration of domain-specific models and algorithms, achieves seamless and efficient data connectivity across business chains, thereby providing a robust foundation for next-generation power system digitization.
Keywords: Power system business digitalization; Cloud computing architecture; Computational resilience; Operational efficiency; Platform maintainability; Task-container co-scheduling; Plug-and-play integration; Unified data foundation
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