Dynamic Water Production Control Using Real-Time Sensor Data
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Solution Overview
Problem
Traditional municipal water production control methods do not utilize real-time field sensor data and fail to adapt to changes in the water distribution network topology, leading to inefficiencies in water supply management.
Innovation Solution
A method and system that query and process real-time sensor data, historical data, and user input to model the water distribution network dynamically, determining optimal water flow and production plans by incorporating constraints and dependencies, and using a slack variable to manage demand and supply imbalances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional demand-driven water production control is used, then water supply planning is simple, but it cannot utilize real-time sensor data and cannot adapt to network topology changes
Solution Approach 1:
The patent implements dynamic water production control by continuously querying sensor data at predetermined time intervals and updating the water distribution model in real-time. The system dynamically adjusts production plans based on current network topology changes, sensor readings, and demand variations, transitioning from static traditional control to adaptive dynamic control that responds to actual field conditions.
2Productivity
If real-time sensor data and historical data are integrated with optimization algorithms, then water production optimization is improved, but computational complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-querying and storing sensor data at predetermined time intervals, pre-processing historical data, and pre-establishing the water distribution network model with nodes and connections. This preparation work is done before the actual optimization calculation, allowing the optimization algorithm to work with pre-organized data and reduce computational complexity during the optimization execution phase.
3Measurement precision
If the water distribution network is modeled with nodes and connections and optimization calculations are performed, then optimal water flow determination is improved, but calculation time increases
Solution Approach 1:
The system implements periodic action by querying sensor data at predetermined time intervals rather than continuously. The optimization calculation is performed periodically at these intervals, determining optimal water flow based on the most recent sensor data and network conditions. This periodic approach balances the need for accurate optimization with the constraint of calculation time, avoiding excessive computational burden while maintaining up-to-date control.
Data Source
AI summary
A method and a system control the water production for a water distribution network. The method includes collecting field sensor data from a water distribution network, using the received data to model the water distribution network and determining an optimal water flow, and generating the optimal water production plan for controlling the water production in the water distribution network based on received data including the sensor data and the historical data. The system includes a process and memory and processor executable instructions to carry out the above method.