Asset Digital Twin for Transient Response Compliance
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Solution Overview
Problem
Current methods for testing the compliance of power generation assets with grid regulations during disruptive events are inadequate, as they often rely on deceptive field tests or offline simulations, which do not accurately reflect real-world conditions, making it difficult to determine the actual transient response capability and compliance with high confidence.
Innovation Solution
A system that generates a model of a target asset based on physical operation data during a defined event, simulating its transient response capability and determining compliance with defined parameters, using a combination of physics-based and data-driven models, and leveraging historical data from similar assets to improve accuracy and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If deceptive field tests or offline simulations are used to test asset compliance, then testing can be performed, but the accuracy and reliability of compliance determination deteriorates because they do not accurately reflect real-world conditions
Solution Approach 1:
The patent creates a digital twin (virtual model) of the physical asset that replicates its transient response characteristics. This virtual model is then used to simulate disruptive events and assess compliance without affecting the actual asset. The digital twin accurately copies the asset's behavior under various conditions, enabling reliable compliance determination while avoiding the limitations of deceptive field tests and offline simulations.
Solution Approach 2:
The system performs preliminary characterization of the asset's transient response capability by collecting and analyzing operational data before actual disruptive events occur. This pre-established knowledge base allows for accurate compliance assessment during real events without needing to perform deceptive tests that compromise reliability.
2Reliability
If traditional testing methods are used, then some compliance assessment can be obtained, but the confidence level in the assessment deteriorates due to inability to accurately reflect real-world transient response
Solution Approach 1:
The system continuously collects operational data from the asset during normal operation and uses this feedback to refine and update the digital twin model. This ongoing calibration ensures that the virtual model accurately reflects the actual asset's transient response characteristics, thereby improving measurement precision while maintaining high confidence in compliance assessments.
Solution Approach 2:
The patent replaces physical testing mechanisms (deceptive field tests) with computational modeling and data analysis. By substituting mechanical/physical test methods with digital simulation and machine learning-based characterization, the system achieves both high reliability and precision in assessing transient response capability without the drawbacks of traditional approaches.
3Productivity
If no formal testing is performed, then asset operation continues without disruption, but the ability to determine compliance with grid regulations deteriorates
Solution Approach 1:
The asset essentially performs its own compliance assessment through the digital twin system that utilizes its own operational data. The system continuously monitors and characterizes the asset's transient response using real-world operating conditions, eliminating the need for separate formal testing that would disrupt asset operation while maintaining precise compliance measurement capability.
Solution Approach 2:
The system enables continuous compliance assessment by utilizing operational data collected during normal asset operation. Rather than requiring periodic formal tests that interrupt productivity, the digital twin continuously evaluates compliance based on ongoing operational data, maintaining both asset productivity and measurement precision simultaneously.
Data Source
AI summary
Distribution network response capability monitoring and compliance determination is provided herein. A method can comprise generating, by a system comprising a processor, a model of a target asset based on operation data measured at the target asset during a defined event. The model is configured to simulate a transient response capability of the target asset. The method can also comprise determining, by the system, a compliance of the target asset to at least one defined parameter based on the transient response capability of the target asset during a simulated event and as a function of the operation data measured during the defined event.