一种基于边缘计算的中水回用节能调控方法及系统
By constructing hysteresis features, rolling statistical features, and weighted cross features in the wastewater reuse system, and combining the GRU model and particle swarm optimization algorithm, high-precision prediction and dynamic optimization of energy consumption and water quality of the wastewater reuse system are achieved. This solves the problem of insufficient ability of existing models to capture dynamic characteristics and improves the energy efficiency and economy of the system.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TIANJIN ZEXI NEW MATERIAL CO LTD
- Filing Date
- 2026-01-13
- Publication Date
- 2026-07-17
AI Technical Summary
Existing methods for regulating and controlling wastewater reuse lack in-depth analysis of historical time-series information and multi-source data, resulting in limited ability of models to capture dynamic characteristics. Traditional prediction models are not accurate enough in predicting the synergistic effects of energy consumption and water quality, making it difficult to achieve dynamic optimization of energy consumption while meeting strict water quality constraints.
Based on edge computing, we construct hysteresis features, rolling statistical features, and weighted cross features, combine them with the GRU model for energy consumption and water quality prediction, and use the particle swarm optimization algorithm to solve the objective function to generate the optimal control vector for energy-saving regulation.
This approach achieves a refined reduction in energy consumption of the reclaimed water system while ensuring that the effluent quality meets standards, thereby improving overall energy efficiency and operational economy. It also solves the problems of slow response, high energy consumption, and insufficient water quality stability in traditional methods.
Smart Images
Figure CN121903301B_ABST