Home Energy Load Prioritization During Backup Power Events
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Solution Overview
Problem
Home energy management systems face challenges in making informed energy usage decisions, particularly in unreliable power grid environments, where existing systems lack effective data acquisition, visualization, and prioritization capabilities to optimize energy consumption and protect devices from power fluctuations.
Innovation Solution
A home energy management system that collects energy usage data, stores user preferences, and uses this information to determine prioritization of devices during energy issues, controlling power usage through a backup power system, ensuring efficient energy distribution and device protection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a home energy management system monitors and controls electrical generation and consumption, then energy usage optimization is improved, but device complexity increases
Solution Approach 1:
The HEMS system segments energy management by creating distinct functional modules: a communication interface for data exchange, a database for storing energy usage data and user preferences, a triggering condition determination module for detecting energy issues, a recommendation module for determining device prioritization, and a device manager for controlling power usage. This modular segmentation improves energy optimization while managing system complexity through organized functional divisions.
Solution Approach 2:
The system performs preliminary actions by continuously monitoring and storing energy usage data of multiple devices before energy issues occur. User preferences are pre-configured in the database, and the system proactively detects triggering conditions (energy issues) before they become critical problems, enabling informed decision-making about energy allocation when needed.
2Reliability
If the system determines prioritization information based on energy usage data and user preferences, then energy distribution reliability is improved, but data processing complexity increases
Solution Approach 1:
The recommendation module implements feedback by retrieving stored energy usage data and user preferences, analyzing this information to determine prioritization information for devices during energy issues, and using this feedback to control power usage through the device manager. This closed-loop feedback mechanism improves energy distribution reliability by making informed decisions based on actual usage patterns and user needs.
Solution Approach 2:
The system performs self-service by automatically monitoring energy usage, detecting energy issues, determining device prioritization based on stored data and user preferences, and controlling power allocation without requiring manual intervention. The device manager autonomously manages power distribution to prioritized devices during energy constraints, reducing operational complexity.
3Loss of energy
If the system uses backup power supply to constrain total load, then energy conservation is improved, but power supply reliability requirements increase
Solution Approach 1:
The device manager dynamically changes operational parameters by constraining the total load of powered devices based on the continuous power supply capability of the backup power system. When energy issues are detected, the system adjusts which devices receive power and at what levels, changing the power consumption parameters to match available backup capacity, thereby conserving energy while maintaining essential functions.
Data Source
AI summary
An energy management system includes: a communication interface connecting the energy management system to a plurality of devices configured to draw power from an electrical circuit of a premises including a backup power system; a database connected to the backup power system by the electrical circuit and storing energy usage data of the plurality of devices and a user preference associated with the plurality of devices; a triggering condition determination module configured to detect an energy issue at the premises; a recommendation module configured to retrieve the energy usage data and the user preference upon detecting the energy issue and determine prioritization information of the plurality devices based on the energy usage data and the user preference; and a device manager configured to control a power usage of the plurality of devices using the prioritization information.