Design of Cloud Edge Collaborative Scheduling Platform for Transmission and Transformation Engineering Construction Based on Holographic Digitization
DOI:
https://doi.org/10.13052/dgaej2156-3306.40567Keywords:
Holographic digitalization, cloud-edge collaborative computing, transmission and transformation engineering, quantum particle swarm optimization, network loss minimizationAbstract
Traditional scheduling methods used in power transmission and transformation engineering construction face significant challenges in dealing with the large-scale and complex data produced by modern power systems. This, in turn, results in higher network losses and reduced operational efficiency. Here, we present an innovative cloud-edge collaborative scheduling platform incorporating holographic digitalization technology to alleviate these problems. The platform integrates cloud-edge resources through a stratified architecture encompassing data persistence, service orchestration, resource management, and application deployment layers. A quantum-enhanced particle swarm algorithm optimizes scheduling decisions by exploiting superposition principles to escape local minima, achieving convergence rates superior to classical metaheuristics. Our platform employs a four-level architectural hierarchy comprising centralized cloud resources and decentralized edge computing nodes, supporting mass three-dimensional visualization and real-time monitoring of engineering processes. The holographic digitalization method acquires multidimensional engineering information by using advanced optical computing methods, while the quantum particle swarm optimization algorithm solves the complicated nonlinear scheduling problem with the objective of minimizing network losses in the system. Experimental verification on a large-scale 500 kV substation project shows that the proposed platform delivers network losses between 1.2% and 2.3% during the construction process, representing an average decrease of 48% over traditional systems that recorded between 2.1% and 5.5% losses. Additionally, an examination of the marginal loss coefficient demonstrates enhanced performance with 65% and 58% reductions compared to standard systems. Our results validate the effectiveness of the platform in minimizing network losses while improving scheduling efficiency and resource allocation in transmission and transformation engineering construction.
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