Synchronized Grid Sensor Network for High-Resolution Power Data
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Solution Overview
Problem
Existing power grid monitoring systems face challenges with low accuracy and coarse timescale data collection, inadequate data handling, and inefficiencies in managing high-volume electrical measurements, which hinder effective control, diagnosis, and optimization of power flows and equipment performance.
Innovation Solution
A sensor network combining micro-synchrophasors and power quality monitors with a time-series database, providing high-resolution data collection and storage, and secure telemetry, along with a novel time-series matrix database architecture, to enhance data handling and analysis capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing SCADA systems and legacy instrumentation are used for power grid monitoring, then system simplicity is maintained, but measurement precision and data resolution deteriorate with only ±5-7% accuracy and half-hourly data points
Solution Approach 1:
The patent combines multiple sensing functions (voltage, current, power quality, synchrophasor measurements) into integrated sensor nodes that communicate through a unified network infrastructure. This merging approach achieves high measurement precision while managing complexity through consolidation rather than separate systems for each measurement type.
Solution Approach 2:
The sensor nodes are designed to perform multiple measurement functions simultaneously - capturing both traditional SCADA measurements and high-resolution synchrophasor data through the same hardware platform. This multi-functionality improves measurement precision without proportionally increasing system complexity.
2Loss of information
If high-resolution data collection at quadrillions of data points per year is implemented, then information completeness is improved, but data handling and storage complexity worsens
Solution Approach 1:
The patent extracts and separates the data storage and handling functions into dedicated time-series database systems, removing the burden from the sensor nodes themselves. This allows high-resolution data collection while managing complexity by dedicating specific system components to specific functions.
Solution Approach 2:
The patent introduces intermediary data aggregation and preprocessing layers between the sensor nodes and the final storage/analysis systems. These intermediaries manage the complexity of quadrillions of data points by implementing efficient data structures, compression, and selective storage strategies.
3Measurement precision
If measurement sampling rate is increased from 2-4 seconds to high-resolution sampling, then measurement precision is improved, but data volume and processing requirements worsen
Solution Approach 1:
The patent merges multiple measurement streams (voltage, current, power, frequency, synchrophasor data) into a unified high-resolution time-series database. This consolidation manages the volume of high-rate data by implementing efficient storage schemas that exploit temporal correlations and redundancies across different measurement types.
Solution Approach 2:
The patent changes the temporal parameter of data collection from coarse half-hourly intervals to continuous high-resolution sampling. This parameter change is managed through efficient data compression and selective storage strategies that maintain precision while controlling data volume through intelligent retention policies and aggregation methods.
4Productivity
If advanced time-series database and cloud-based Data-as-a-Service platform are deployed, then data analysis capability is improved, but system infrastructure complexity worsens
Solution Approach 1:
The patent introduces a cloud-based Data-as-a-Service platform as an intermediary layer between the sensor network and end-user applications. This intermediary handles the complexity of quadrillions of data points through specialized time-series database infrastructure, allowing high productivity without proportionally increasing overall system complexity.
Solution Approach 2:
The cloud-based platform provides multiple functions (data storage, processing, analysis, visualization, and application development) through a unified infrastructure. This multi-functionality improves productivity while managing complexity by consolidating diverse data handling requirements into a single versatile platform.
Data Source
AI summary
Provided is a sensor network and method for monitoring electric power systems, collecting high-resolution data, and securely feeding it into an advanced time-series database. An apparatus for monitoring a power grid by collecting high-resolution electrical measurement data comprises an operative pair of signal analysers, the operative pair comprising: a micro-synchrophasor configured to operate in the frequency-domain to process an electrical signal and collect a first set of data points; and a power quality monitor configured to operate in the time-domain to process the electrical signal and collect a second set of data points; wherein the apparatus is configured to apply the same synchronised timestamp to the collected first and second sets of data points. A method for monitoring a power grid and collecting high-resolution electrical measurement data comprises the steps of collecting (101) a first set of data points using a micro-synchrophasor operating in the frequency-domain, collecting (102) a second set of data points using a power quality monitor operating in the time-domain, and applying (103) a synchronised timestamp to the collected first and second sets of data points.