Adaptive Load Modeling in Power Grids Using Voltage Adjustment Events
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Solution Overview
Problem
Current load modeling systems in electrical power networks use the same parameters for different conditions and fail to process field data accurately, leading to incorrect computations and inefficiencies due to the lack of adaptive load modeling parameters.
Innovation Solution
A method and system that utilize measurement data to identify voltage adjustment events and generate load models based on voltage factors, including voltage dependency and sensitivity, using a recursive least mean square filter to determine constant impedance, current, and power load coefficients, allowing for adaptive load modeling parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the same load modelling parameters are used for different conditions, then the system is simple to operate, but the accuracy of load modelling results deteriorates
Solution Approach 1:
The patent implements dynamic load modelling parameters that automatically adapt to different operating conditions. The system continuously updates impedance, current, and power load coefficients based on real-time voltage adjustment events and measurement data, transforming static parameters into dynamic ones that reflect actual grid conditions.
Solution Approach 2:
The patent changes the parameters themselves by introducing voltage-dependent load coefficients (impedance, current, and power coefficients) that vary based on voltage adjustment events. The recursive least mean square filter continuously adjusts these parameters based on measured data, ensuring accuracy across different operating conditions.
2Device complexity
If field data is not processed accurately, then the system complexity is reduced, but the reliability of voltage stability analysis deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where measurement data from the power grid is continuously processed through a recursive least mean square filter. The filter uses voltage adjustment events as feedback signals to update load modelling parameters, creating a closed-loop system that continuously improves accuracy based on actual grid behavior.
Solution Approach 2:
The patent replaces manual or simple data processing methods with an automated recursive least mean square filter algorithm. This computational approach automatically processes field data, identifies voltage adjustment events, and updates load coefficients without manual intervention, enhancing reliability while managing complexity through automation.
3Measurement precision
If adaptive load modelling parameters are implemented, then the accuracy of voltage stability analysis is improved, but the device complexity increases
Solution Approach 1:
The patent segments the load modelling into three distinct coefficient types (impedance, current, and power coefficients), each handled separately by the recursive least mean square filter. This segmentation allows the complex adaptive modelling to be broken down into manageable components, reducing overall system complexity while maintaining accuracy.
Data Source
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AI summary
A method (200) for modelling load in a power grid (10) is provided. The method includes obtaining (210) measurement data from a measurement device in the power grid, identifying (220) one or more voltage adjustment events in the power grid from the measurement data, and generating (230) a load model based on one or more voltage factors computed using the one or more voltage adjustment events.