Water Supply Pumping Station Control for Pressure and Flow Optimization
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Solution Overview
Problem
Existing water supply systems operate manually or based on rules, which are resource-intensive and inefficient in terms of energy and cost, and lack a systematic approach to optimize pressure and flow distribution across multiple pumping stations.
Innovation Solution
A computer-implemented method that uses a two-level optimization approach, first determining resource-optimized pressure and flow target values for pumping stations over a forecast period using a hydraulic model, and then adjusting operating parameters for individual pumps based on these targets, while updating the model to adapt to dynamic changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual or rule-based control is used for water supply systems, then operation simplicity is maintained, but energy efficiency and cost-effectiveness deteriorate
Solution Approach 1:
The system performs self-optimization by automatically determining operating parameters for pumping stations based on forecasted water usage and system state, eliminating the need for manual intervention while achieving energy-efficient operation through continuous adaptive control
Solution Approach 2:
The system uses feedback from the hydraulic model that continuously updates based on actual system performance and forecasted demands, allowing the control system to adjust operating parameters dynamically to optimize energy efficiency while maintaining simple operation through automated decision-making
2Device complexity
If rule-based control is used, then implementation complexity is low, but resource optimization deteriorates
Solution Approach 1:
The system automatically optimizes resource usage by having the hydraulic model and control algorithms continuously determine the most efficient operating parameters for pumping stations, eliminating manual optimization efforts while achieving superior resource efficiency through self-directed control
Solution Approach 2:
The system transitions from static rule-based control to dynamic optimization where operating parameters are continuously adjusted based on real-time system state and forecasts, allowing the system to adapt to changing conditions and maximize resource efficiency without excessive implementation complexity
3Productivity
If centralized control specifies outlet pressure for each pumping station, then flow distribution is achieved, but energy consumption increases
Solution Approach 1:
The system dynamically determines outlet pressure specifications for each pumping station based on the current system state, forecasted demands, and hydraulic model predictions, allowing pressure to be optimized in real-time rather than maintained at fixed centralized setpoints, thereby reducing energy consumption while maintaining effective flow distribution
Solution Approach 2:
The system changes the operating parameters (outlet pressure, flow rates) of pumping stations based on optimized calculations from the hydraulic model, adjusting these parameters dynamically to achieve flow distribution goals at minimum energy cost rather than using fixed centralized specifications
4Manufacturing precision
If detailed pumping models are used for each station, then operational precision is improved, but computational complexity increases
Solution Approach 1:
The system segments the optimization problem into two levels: system-level optimization that determines overall flow distribution and pressure targets, and station-level optimization that determines specific pump operating parameters. This segmentation allows detailed modeling at the pumping station level without requiring the entire system to be re-optimized, reducing computational complexity while maintaining operational precision
Solution Approach 2:
The system adds a hierarchical dimension to the optimization approach, separating system-wide considerations from local pumping station decisions. This dimensional separation allows detailed local models to be used without proportionally increasing overall computational complexity, as the system-level model operates at a higher abstraction level
Data Source
AI summary
A method for controlling distribution of pressure and flow in a water supply system which includes a plurality of pumping stations is provided, including: (a) reading in a computer-assisted hydraulic model of the water supply system, the hydraulic model mapping a time-dependent distribution of pressure and flow, (b) determining resource-optimized pressure and flow target values for the pumping stations for a specified forecast period using the computer-assisted hydraulic model by a first method of optimization, (c) reading in a pumping model behavior for a pumping station, the pumping model mapping an operational behavior of pumping devices of the pumping station, (d) determining resource optimized operating parameters for the pumping devices of the pumping station by the pumping model at a specified time by a second method of optimization, and (e) outputting the resource-optimized operating parameters for controlling the pumping devices of the pumping station.