Excitation System Modeling Using Frequency Response Data
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Solution Overview
Problem
The existing process for modeling excitation systems in synchronous generators is time-consuming, expensive, and error-prone, requiring multiple steps and expert personnel for data collection, analysis, and reporting, and lacks integration with the excitation system and its configuration tools, necessitating a more efficient method for selecting, tailoring, and verifying IEEE standard models.
Innovation Solution
A system and method for modeling excitation systems that involves selecting a standard IEEE model based on similarity, collecting data, determining parameter settings using an on-site maintenance computer, verifying the model by comparing outputs, and generating a report, with the ability to perform frequency response data production using a single test to reduce test time and optimize excitation system settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a tailored IEEE model is produced using traditional multi-step processes with expert personnel, then model accuracy is improved, but time consumption and cost increase significantly
Solution Approach 1:
The system performs preliminary actions by automatically selecting the appropriate IEEE standard model based on exciter type and pre-calculating parameter estimates before on-site testing. This preparation work is done in advance using manufacturer data and system specifications, reducing the time needed during actual commissioning while maintaining accuracy through pre-validated model selection criteria.
Solution Approach 2:
The invention creates a digital copy of the excitation system through automated data collection and modeling. The system replicates the physical exciter's behavior by collecting operational data and fitting it to IEEE standard models, eliminating the need for expert personnel to manually analyze and verify models on-site. This digital copying process maintains accuracy while significantly reducing time consumption.
2Measurement precision
If expert personnel are deployed for on-site verification testing, then model verification accuracy is improved, but operational complexity and cost increase
Solution Approach 1:
The system performs self-service by automatically collecting data from the excitation system, selecting appropriate IEEE models, determining parameter values, and verifying model accuracy without requiring expert personnel. The automated verification process compares model outputs with actual system responses, providing confidence in model accuracy while eliminating the complexity of coordinating expert visits and manual verification procedures.
3Measurement precision
If multiple iterative cycles of model tailoring and verification are performed, then model accuracy is improved, but productivity decreases
Solution Approach 1:
The system performs preliminary model selection and parameter estimation before on-site testing, establishing a strong initial model that requires minimal iterative refinement. By pre-calculating parameter estimates from manufacturer data and system specifications, the system reduces the number of iterative cycles needed during commissioning, thereby improving productivity while maintaining accuracy through targeted verification testing.
Data Source
AI summary
A system for collecting frequency response data from a generator system including: applying a perturbing signal to a signal input of an exciter system for a synchronous generator; collecting data regarding signal output from a multiplicity of signal points in the exciter system; transforming the collected data to predict a signal response at a signal output in the system different from the signal points used for collecting data, and analyzing the frequency response of the system.