Cloud-Based Smart Grid Data Management for Transformer Monitoring
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Solution Overview
Problem
Current smart grid networks, especially in urban and remote locations with limited infrastructure, face challenges in deploying a comprehensive smart grid or internet infrastructure due to insufficient communication with transformers, residential, and commercial meters, necessitating advanced data management and visualization systems.
Innovation Solution
A cloud-based system that integrates transformer monitoring devices with a wireless mesh network, enabling bi-directional data flow and allowing for both scheduled and transactional commands, along with data visualization through a centralized analytics platform and user interfaces, facilitating efficient data processing and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a comprehensive smart grid infrastructure is deployed in urban and remote locations, then communication capability with transformers and meters is improved, but infrastructure complexity and deployment difficulty increase
Solution Approach 1:
The system segments the smart grid infrastructure into distributed components: transformer monitoring devices at transformation points, smart meters at consumer premises, and a centralized cloud platform. Each segment operates semi-independently, reducing deployment complexity while maintaining comprehensive communication capability across the grid.
Solution Approach 2:
A wireless communication network acts as an intermediary layer between physical grid assets (transformers, meters) and the centralized monitoring system. This intermediary enables communication capability improvement without requiring direct physical infrastructure connections to every asset, thereby reducing overall infrastructure complexity.
2Productivity
If advanced data management and visualization systems are implemented, then data processing capability is improved, but system complexity increases
Solution Approach 1:
Complex data processing, analytics, and visualization functions are extracted from local edge devices and relocated to a centralized cloud-based data management platform. This extraction enables advanced data processing capability while keeping individual field devices simple, thereby managing overall system complexity through functional separation.
Solution Approach 2:
The centralized data management platform provides universal data processing capabilities that serve multiple functions: real-time monitoring, historical analysis, predictive maintenance, and reporting. This multi-functional platform improves data processing capability across the entire system without requiring separate complex systems for each function.
3Adaptability or versatility
If cloud-based systems with hardware interaction are deployed, then data retrieval flexibility is improved, but cloud design complexity increases
Solution Approach 1:
The cloud-based system implements dynamic data retrieval mechanisms that adapt to different operational needs: scheduled automated data collection during normal operation and on-demand random retrieval during events or anomalies. This dynamic approach provides data retrieval flexibility while managing cloud design complexity through a unified architecture that handles both modes.
Solution Approach 2:
The system changes operational parameters of the cloud platform based on demand: switching between automated scheduled retrieval and manual on-demand retrieval modes. This parameter change capability provides flexibility in data retrieval strategies while the underlying cloud architecture manages the complexity of supporting multiple operational modes.
Data Source
AI summary
A smart grid network is provided including one or more transformer monitoring devices configured to collect metering data from one or more metering devices in the smart grid network. The smart grid network further includes a cloud-based data processing and storage system with one or more cloud data processors configured to receive data from the one or more transformer monitoring devices and process the received data into categories including at least a first category of data comprising the collected metering data. The cloud-based data processing and storage system further includes at least one data store to store data of at least the first category of data, an analytics platform configured to analyze the received and categorized data and a graphics server configured to format the analyzed data for display on a user device of the smart grid network.