Remote Pressure Modeling for Flow-Free Water Network Control
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Solution Overview
Problem
Existing water supply networks face challenges in effectively controlling pressure regulating systems without flow sensors and with unknown pump characteristics, as existing solutions require flow sensors or exact knowledge of pump characteristics, which are often not available, and fail to adapt to changes over time.
Innovation Solution
A model formation module that creates a pressure control model using remote pressure sensors and load-dependent variables, such as pump speed and power consumption, to control the pressure regulating system without measuring flow values, allowing for detection of leaks and adaptation to changes in pump efficiency over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If flow sensors are installed to obtain flow values for controlling the pressure regulating system, then the control accuracy is improved, but the device complexity and cost increase
Solution Approach 1:
The patent extracts the flow measurement function from physical flow sensors and implements it virtually through a flow determination device that calculates flow values from electrical parameters (voltage, current, frequency) of the pump system, eliminating the need for physical flow sensors while maintaining control accuracy
Solution Approach 2:
The patent replaces the mechanical/physical flow sensing system with an electrical measurement and calculation system, where flow values are determined from electrical parameters of the pump motor, substituting physical flow measurement with electrical parameter-based calculation
2Measurement precision
If exact knowledge of pump characteristics is used to determine flow from electrical parameters, then the control precision is improved, but the adaptability deteriorates when pump characteristics change over time
Solution Approach 1:
The system performs self-characterization by automatically determining pump characteristics through measurements during operation, and continuously adapts to changing pump characteristics without external intervention, making the system self-adjusting to degradation or changes over time
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors electrical parameters and pressure values, compares them with model predictions, and adjusts the flow determination and control strategies accordingly, enabling real-time adaptation to changing conditions
3Reliability
If a flow-dependent model is used for controlling pumps, then the pressure control effectiveness is improved, but the device complexity increases due to required flow sensors or exact pump characteristics
Solution Approach 1:
The patent creates a universal control approach that works with different pump types (centrifugal, axial, mixed flow) and different pressure regulating systems (PRV, pump speed control) by using a unified method of determining flow from electrical parameters and applying pressure control, making the system broadly applicable without requiring specific pump characteristics
Data Source
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AI summary
The present disclosure is directed to a model formation module (25) for creating a model for controlling a pressure regulating system (7) of a water supply network (5), wherein the water supply network (5) is equipped with one or more pressure sensors of which at least one remote pressure sensor (17a,b) is arranged remotely from the pressure regulating system (7), the model formation module (25) being configured to communicate with the at least one remote pressure sensor (17a,b). The model formation module (25) is configured to create said model without a measured, determined or estimated flow value on the basis of at least one remote pressure value determined by the at least one remote pressure sensor (17a,b) and on the basis of at least one load-dependent variable of the pressure regulating system (7), said model representing at least one pressure control curve for controlling the pressure regulating system (7).