Distributed Grid Sensors for Outage-Resilient Anomaly Detection
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Solution Overview
Problem
Current power grid monitoring systems face challenges due to high costs, delayed data reporting, loss of power and communication during grid failures, and fragmentation of data across multiple utility companies, leading to inefficiencies and safety issues.
Innovation Solution
A system of broadly distributed, secure, cloud-supported sensors connected to a power grid or network, capable of reporting measurements in real-time and providing situational awareness, with methods for determining consensus and anomaly detection across various geographies, using an adjacent communications network with secondary power sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional monitoring equipment is installed at power substations, then data collection coverage is achieved, but data resolution is coarse and reporting is delayed
Solution Approach 1:
The patent divides the monitoring system into distributed sensor nodes deployed at multiple locations including substations and customer premises. This segmentation enables fine-grained data collection with high spatial resolution, allowing precise local measurements to be aggregated into comprehensive grid-wide visibility, thereby improving both data resolution and reporting timeliness.
Solution Approach 2:
The patent adds a new dimension to monitoring by deploying sensors at customer premises equipment (CPE) in addition to traditional substation locations. This dimensional expansion from centralized to distributed monitoring points enables simultaneous high-resolution local measurements and aggregated regional analysis, eliminating the trade-off between coverage and precision.
2Reliability
If sensors are connected directly to the power network, then power grid metrics can be monitored, but sensors lose power and communication capabilities during grid failures
Solution Approach 1:
The patent introduces an intermediary power source architecture where sensors can draw power from both the power grid being monitored and alternative sources such as battery backups or local power supplies. This intermediary approach allows sensors to maintain operation during grid failures, ensuring continuous monitoring without complete dependency on the grid's power supply.
Solution Approach 2:
The patent implements dynamic power source switching that changes the operational parameters of sensors based on grid conditions. During normal operation, sensors draw power from the grid; during failures, the system automatically transitions to alternative power sources, maintaining monitoring reliability while adapting to changing energy availability conditions.
3Productivity
If new sensors with wireless communication capabilities are installed, then real-time data collection is improved, but installation costs increase significantly
Solution Approach 1:
The patent designs sensor nodes with multi-functionality that can operate in multiple modes: standalone wireless sensors for high-value locations and wired sensors leveraging existing communication infrastructure for cost-sensitive deployments. This universal design allows the system to achieve real-time data collection efficiency while adapting to different budget constraints and deployment scenarios.
Solution Approach 2:
The patent utilizes existing communication infrastructure (such as utility-owned wireless networks or fiber optic cables) as a copying alternative to deploying entirely new wireless sensor networks. By repurposing existing communication channels for sensor data transmission, the system achieves real-time monitoring capability without the full cost of dedicated wireless infrastructure.
4Loss of information
If data is collected from multiple utility companies, then comprehensive grid analysis is achieved, but data fragmentation occurs
Solution Approach 1:
The patent implements a centralized data aggregation platform that merges data from multiple utility companies into a unified analytical framework. This combining approach consolidates fragmented data sources while maintaining the ability to trace data to specific utility origins, achieving comprehensive grid analysis without being overwhelmed by data fragmentation through standardized data normalization and centralized processing.
Data Source
AI summary
A system and method for data collection and aggregation using a distributed network of communications enabled sensors connected to another primary network to achieve a secondary out-of-band monitoring perspective, for example, in power grids. The data collection system includes an aggregation and processing server configured to collect data from a variety of sensors adjacent to the monitored network each sensor includes secondary power such that it can continue data transmission even during power grid outages. The data collection system includes a method for secure real-time data ingest, machine learning enabled analysis, risk assessment, and anomaly detection on a broad geographic scale irrespective of isolated network boundaries.