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Distributed nodal water demand estimation for real-time modeling of large-scale water distribution systems using
Chengna Xu1, Yu Shao2, Tuqiao Zhang2
1College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China.
None:
Real-time hydraulic modeling of water distribution systems (WDS) is crucial for effective network operation and control. Nodal water demand, a key time-varying parameter, requires accurate real-time estimation to ensure reliable simulations. However, estimating nodal water demand in large-scale WDS is challenging due to high computational demands. This study presents an innovative distributed estimation approach that decentralizes the process into localized tasks across multiple compute nodes, using Bayesian decomposition. The method also incorporates sensor grouping and global information sharing to improve accuracy and prevent convergence to local optima. Evaluations on two large-scale WDSs show that this approach increases computational efficiency by up to eight times compared to traditional centralized methods, while maintaining comparable accuracy. This represents a significant advancement in real-time hydraulic modeling, offering scalable solutions with important implications for both research and engineering applications.
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