Distributed Smartgrid Energy Data Visualization System
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Solution Overview
Problem
Current electrical grid systems are unable to provide granular, real-time energy usage data to customers, limiting their ability to manage energy consumption effectively and identify inefficiencies, and they struggle to scale to handle large numbers of energy monitoring devices.
Innovation Solution
A distributed architecture system that includes redundant sensor, logger, and storage devices, capable of collecting, storing, and presenting energy usage data in real-time, using a spreading algorithm to distribute data across multiple storage units and employing a service announcement protocol for efficient data management and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a distributed architecture with redundant devices is implemented, then the system can provide granular real-time energy usage data and scale to handle large numbers of devices, but the device complexity and infrastructure requirements increase
Solution Approach 1:
The system divides the energy monitoring infrastructure into multiple independent components: sensor devices at customer premises, agent devices for data collection, logger devices for data storage, and visualization devices for data presentation. Each component operates independently and can be scaled separately, allowing the system to handle large numbers of devices while maintaining manageable complexity at each level.
Solution Approach 2:
The system changes the parameter of data granularity from monthly totals to real-time detailed measurements. By implementing continuous monitoring at the sensor level and storing detailed time-stamped data in loggers, the system transforms coarse-grained estimation into fine-grained measurement, enabling customers to see energy consumption at 15-minute intervals or finer resolutions.
2Loss of information
If monthly billing is used for energy consumption feedback, then the system is simple to operate, but the information timeliness and granularity are insufficient for effective energy management
Solution Approach 1:
The system implements continuous feedback loops where sensor devices measure energy consumption, agent devices collect the data, logger devices store it with timestamps, and visualization devices present it to customers in real-time. This creates an ongoing feedback mechanism that allows customers to monitor their energy usage continuously and make immediate adjustments, rather than receiving delayed monthly summaries.
Solution Approach 2:
The system adds the dimension of time granularity by transitioning from monthly aggregated data to real-time time-stamped measurements. By recording energy consumption at frequent intervals (e.g., every 15 minutes or less) and preserving these temporal details in the database, the system enables customers to analyze usage patterns by hour, day, or specific time periods within the billing cycle.
3Adaptability or versatility
If traditional electrical grid systems are used, then the system is stable and proven, but the system cannot provide real-time data access or scale to millions of monitoring devices
Solution Approach 1:
The system creates universal interfaces and protocols that allow diverse energy monitoring devices to communicate through standardized methods. The agent devices can collect data from various sensor types using common communication protocols, and the logger devices store data in standardized formats, enabling the system to scale to millions of devices from different manufacturers while maintaining stable, predictable operation.
Data Source
AI summary
An energy usage data visualization process includes receiving an energy data presentation request from a user, processing the energy data presentation request by the customer portal service module, and retrieving energy usage data associated with the energy data presentation request. The energy usage data is retrieved from a storage device, which is communicatively coupled to the customer portal service module. The service module produces a visual output based upon the presentation request and the retrieved energy usage data. The service module produces the visual output for presentation onto the display of the end user interface, by using an energy data visualization template of a template module application. The template module application is determined by the energy data presentation request, and is stored on the customer portal service module. The customer portal service module has a housing that is separate from the housing of the end user device.