Pipeline Pump Control Using Digital Twin Models for Viscous Liquids
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Solution Overview
Problem
Current liquid pumping systems face challenges in efficiently operating with liquids of varying viscosities and characteristics, as existing technologies lack effective means for dynamically simulating centrifugal pump performance that deviates from manufacturer specifications, particularly for variable speed, viscosity, and density applications.
Innovation Solution
Implementing a real-time simulation and modeling system using a programmable logic controller (PLC) to adjust pump operating parameters based on actual performance and liquid characteristics, creating a 'digital twin' of pumps to optimize energy usage and efficiency by simulating pump head as a function of speed and flow, and applying Affinity Laws and ANSI/Hydraulic Institute equations to adjust for viscous liquids.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manufacturer specifications are used for pump operation, then initial setup is simple, but the system cannot adapt to varying liquid viscosities and characteristics
Solution Approach 1:
The pump control system transitions from static manufacturer specifications to dynamic real-time adjustment based on actual liquid properties. The system continuously monitors viscosity, density, and flow rate, then dynamically adjusts pump speed and operating parameters to optimize performance for varying liquid characteristics.
Solution Approach 2:
The system implements closed-loop feedback by measuring actual liquid properties (viscosity, density, flow rate) and using this information to adjust pump operation. The controller receives sensor data and continuously modifies pump speed and configuration based on the measured liquid characteristics, creating a self-adjusting system.
2Productivity
If real-time simulation and modeling is implemented, then pump efficiency is optimized, but system complexity and computational requirements increase
Solution Approach 1:
The system creates a digital twin or virtual model of the physical pump that replicates its performance characteristics. This computational model allows real-time simulation of pump behavior under different operating conditions without requiring physical testing, enabling efficient optimization of pump performance.
Solution Approach 2:
The system performs preliminary computational analysis by executing pump models and simulations before actual pump operation. The controller calculates optimal operating parameters in advance based on predicted liquid properties, then implements these pre-computed settings to maximize efficiency.
3Use of energy by moving object
If pump operation is adjusted for optimal energy efficiency, then energy consumption is reduced, but response time to liquid property changes may increase
Solution Approach 1:
The system implements periodic monitoring and adjustment of pump parameters based on changing liquid properties. Rather than continuous full-scale optimization, the system performs energy-efficient adjustments at optimal intervals, balancing energy savings with adequate response to liquid property changes.
Solution Approach 2:
The system dynamically changes operating parameters (speed, flow rate, pressure) based on liquid properties to optimize energy efficiency. By adjusting multiple parameters simultaneously rather than single-parameter control, the system achieves energy savings while maintaining adequate response capability.
Data Source
AI summary
A method and controller for operating a pumping station. The method includes receiving (1102), by at least one controller (910, 952), sensor data (712) of a first pumping station (900) corresponding to a liquid being transported from the first pumping station (900). The method includes predicting (1104) arrival of the liquid, by the at least one controller (910, 952), at a second pumping station (900). The method includes executing (1106) one or more pump models (720), by the at least one controller (910, 952), according to the sensor data (712) to determine an optimal pumping configuration. The method includes operating (1108) one more pumps of the second pumping station (900), by the at least one controller (910, 952), according to the optimal pumping configuration.