Energy Management System with Device-Level Feedback
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Solution Overview
Problem
Conventional energy management techniques lack the ability to provide detailed feedback on energy savings across multiple devices, making it difficult for users to differentiate and optimize energy consumption reductions.
Innovation Solution
An energy management system with a central controller that receives feedback from multiple devices, determines statistical patterns, and generates control policies to optimize energy usage across these devices, using a PLC network for communication and AI-driven decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional electricity meters are used to monitor energy usage, then energy consumption can be displayed at the building level, but detailed feedback on energy savings from specific devices or actions cannot be provided
Solution Approach 1:
The patent segments the energy monitoring system into device-level components, where individual devices or appliances are monitored separately. This segmentation enables detailed feedback on energy consumption and savings from specific devices, transforming the aggregate building-level monitoring into granular device-level monitoring without creating a single complex centralized system.
2Measurement precision
If device-level monitoring is implemented across multiple devices, then detailed energy consumption feedback can be obtained, but system complexity and infrastructure requirements increase
Solution Approach 1:
The patent implements feedback mechanisms that provide users with real-time or near-real-time information about energy consumption at the device level. This feedback enables users to see the direct impact of their actions on energy usage, allowing for precise measurement and actionable insights while managing system complexity through standardized feedback channels and user interfaces.
Solution Approach 2:
The system employs universal communication protocols and standardized interfaces that allow multiple devices to be monitored through a common framework. This multi-functionality approach enables the system to handle various device types and communication methods without requiring separate complex infrastructure for each device, thus achieving high measurement precision while controlling overall system complexity.
Data Source
AI summary
Feedback is received from a plurality of devices. External data is also received. Statistical patterns of the plurality of devices are determined based on the feedback. A policy is determined based on the statistical patterns, the feedback, and the external data. The policy may include a set of rules dictating the operation of each of the plurality of devices and reducing energy consumption at the plurality of devices. Control data based on the policy is transmitted to the plurality of devices. The control data may be operative to transform the operation of the plurality of devices according to the set of rules.