Water Distribution Hydraulic Model Updating for Real-Time Control
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Solution Overview
Problem
Current hydraulic models for water distribution networks are labor-intensive and costly to maintain, often becoming outdated due to changes in network conditions, making it difficult to accurately simulate pressure and flow distribution over time.
Innovation Solution
A method involving data collection from sensors and flow meters to compare with existing hydraulic models, using error threshold determination and anomaly detection to update the model, incorporating adaptive sampling and sequential convex programming for efficient calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual calibration methods are used to maintain hydraulic models, then model accuracy can be improved, but the process becomes labor-intensive and costly
Solution Approach 1:
The system performs automatic self-calibration by utilizing existing sensor data from the water distribution network. The calibration process is autonomous, requiring no manual intervention, and continuously updates model parameters based on observed hydraulic states, thereby maintaining accuracy while eliminating labor-intensive operations
Solution Approach 2:
The patent replaces manual mechanical calibration processes with an automated computational system that uses optimization algorithms and sensor data processing. This substitution transforms the calibration from a labor-intensive physical process to an automated information-processing task, significantly improving efficiency
2Productivity
If hydraulic models are calibrated using limited time period data, then calibration cost is reduced, but model performance rapidly deteriorates due to changes in network conditions
Solution Approach 1:
The system implements continuous calibration by constantly incorporating new sensor data from the network into the model. Rather than periodic calibration with limited data, the system maintains an ongoing calibration process that continuously adapts to changing network conditions, ensuring long-term model reliability
Solution Approach 2:
The patent establishes a feedback loop where sensor measurements from the actual network are continuously compared with model predictions. The calibration algorithm uses this feedback to automatically adjust model parameters, ensuring the model remains accurate despite changes in network connectivity, demand patterns, or hydraulic states
3Measurement precision
If continuously acquired hydraulic data with high spatial and temporal resolution is used for calibration, then model accuracy is improved, but major computational challenges arise
Solution Approach 1:
The calibration process is segmented into manageable computational tasks. The system divides the large dataset into smaller time windows or spatial zones, processes them separately using optimization algorithms, and aggregates the results. This segmentation reduces the computational burden while maintaining the benefits of using comprehensive high-resolution data
Solution Approach 2:
The system selectively processes only the most relevant portions of the available data at any given time, rather than continuously processing all data. The calibration algorithm identifies and focuses on critical measurement points or time periods where the model most needs adjustment, reducing computational effort while maintaining accuracy
Data Source
AI summary
A computer-implemented method of controlling operation of a water distribution network, WDN, comprising obtaining data pertaining to parameters of the WDN; comparing the data with a hydraulic model of the WDN; determining an error value based on the comparing the data with the hydraulic model; determining that the error value is below a threshold; using the data to obtain an updated hydraulic model; and using the updated hydraulic model to control one or more elements of the WDN.