PQM Deployment Point Selection Using Power Data Clustering
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Solution Overview
Problem
The deployment of Power Quality Monitoring (PQM) devices is challenging due to high costs and the need for optimized placement, often relying on personal expertise, which can lead to inefficient distribution and neglect of critical regions.
Innovation Solution
A method and apparatus that determine the optimal deployment points for PQM devices by clustering historical power data using the silhouette coefficient to identify the most relevant categories and deploying devices at the center or closest point to these categories, optimizing the number of devices and reducing deployment difficulties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If PQM devices are deployed at multiple locations to ensure steady power supply, then power quality monitoring coverage is improved, but deployment cost increases
Solution Approach 1:
The patent transforms the deployment problem from a spatial arrangement task to a data-driven optimization problem by changing the parameter selection criteria from expert experience to quantitative analysis of historical power data characteristics, enabling optimal deployment configuration
Solution Approach 2:
The patent replaces the manual expert-based deployment decision-making process with an automated computational system that uses clustering algorithms and silhouette coefficients to objectively determine optimal deployment locations, eliminating subjectivity and reducing trial-and-error costs
2Ease of operation
If deployment points are decided by personal specialist knowledge, then deployment process is simplified, but deployment optimization is reduced leading to excessive monitoring in unimportant regions
Solution Approach 1:
The system enables self-service deployment optimization by automatically analyzing historical power data and generating optimal deployment point recommendations without requiring deep expert intervention, allowing the data itself to guide the deployment decisions
Solution Approach 2:
The patent incorporates feedback mechanisms where the clustering results and silhouette coefficients provide quantitative feedback on deployment quality, allowing continuous optimization of deployment points based on measured performance metrics from historical data
Data Source
AI summary
Various embodiments of the teachings herein include a method for deploying power quality monitoring (PQM) devices. The method may include: determining a maximum number of PQM devices and historical power data of candidate deployment points, wherein the number of the candidate deployment points is greater than the maximum number of the PQM devices; clustering the historical power data of the candidate deployment points, wherein a target number of categories is determined on the basis of a silhouette coefficient of each candidate number of categories and the maximum number of the PQM devices; and determining PQM device deployment points based on the center of each category in the target number of categories.