Power Network Model Validation for Connectivity and Power-Flow Errors
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Solution Overview
Problem
Existing power network models are prone to errors, inconsistencies, and incompleteness due to human input, leading to sub-optimal operation and potential hazardous conditions in electric power networks, as they lack effective validation methods to ensure accuracy and reliability.
Innovation Solution
A validation system computes validation scores based on connectivity, asset, and power-flow scores to verify the accuracy of power network models, iteratively updating the model until a threshold score is reached, ensuring the model accurately reflects the actual network and is usable for control systems to identify and correct errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If power network models are generated using human input data, then the models can be created and used for basic operations, but the models become prone to errors, inconsistencies, and incompleteness
Solution Approach 1:
The system performs preliminary validation actions by computing connectivity scores, asset scores, and power-flow scores before the model is fully utilized. This advance validation identifies and flags potential errors, inconsistencies, and incompleteness in the model data, allowing corrections to be made before the model is deployed for critical operations.
Solution Approach 2:
The system implements feedback mechanisms by repeatedly computing validation scores for iteratively updated versions of the power network model. The validation scores provide continuous feedback on model quality, guiding corrections and improvements until a threshold is reached, thereby enhancing model reliability while maintaining ease of creation.
2Measurement precision
If validation scores are computed repeatedly for iteratively updated model versions, then the model accuracy is improved, but the computational time and resources increase
Solution Approach 1:
The system applies partial validation by focusing computational resources on computing three specific types of scores (connectivity, asset, and power-flow) rather than performing exhaustive validation. This targeted approach achieves sufficient model accuracy for operational use without the excessive computational time that would result from complete or redundant validation checks.
Data Source
AI summary
This disclosure involves verifying that a power network model corresponds to an electric power network providing electrical power in a geographical area. For instance, a validation device computes a validation score for a power network model based on a connectivity score, an asset score, and a power-flow score. The connectivity score indicates connectivity errors in the power network model as compared to the power network. The asset score indicates power-delivery errors in the power network model with respect to power-consuming assets serviced by the power network. The power-flow score indicates power-flow calculation errors in the power network model with respect to voltage ranges for the power network. The validation score is repeatedly computed for iteratively updated versions of the power network model until a threshold validation score is obtained. The validated power network model is provided to a control system for identifying and correcting errors in the power network.