Backup Management System Charging Schedule Optimization
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Solution Overview
Problem
Consumers lack adequate information to efficiently manage backup devices during power disturbances, leading to either unpreparedness or excessive charging, which is costly and reduces device lifespan.
Innovation Solution
A utility communication system with a backup management system that receives consumer preferences and generates customized charging and switching schedules based on predicted power disturbances, prioritizing energy use and reducing recharging costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If consumers keep backup devices fully charged at all times, then reliability of power supply during disturbances is improved, but cost of energy consumption increases and device lifespan decreases
Solution Approach 1:
The system performs preliminary charging of backup devices based on predicted power disturbances. The backup management system receives notifications of predicted disturbances and schedules charging operations in advance, allowing consumers to charge devices only when needed rather than maintaining constant full charge, thereby reducing energy costs while ensuring reliability when disturbances occur.
Solution Approach 2:
The system dynamically adjusts charging schedules based on real-time conditions including predicted disturbance timing, current charge levels, and consumer preferences. The charging schedule is not static but adapts to changing conditions, optimizing the balance between reliability and energy cost by charging only when and how much is necessary.
2Reliability
If consumers keep backup devices fully charged at all times, then reliability of power supply during disturbances is improved, but device lifespan decreases
Solution Approach 1:
The system charges backup devices in advance based on predictions of when disturbances will occur, rather than maintaining continuous full charge. This allows the devices to be charged only sufficiently for the predicted disturbance duration, avoiding unnecessary over-charging that would reduce device lifespan while still ensuring adequate charge for reliability.
Solution Approach 2:
The system changes the charge level parameter dynamically based on predicted disturbance characteristics. Instead of maintaining a constant 100% charge level, the system adjusts the charge level to match the specific needs of each predicted disturbance scenario, optimizing both device lifespan and reliability.
3Loss of energy
If consumers do not charge backup devices, then energy cost is reduced, but readiness for power disturbances deteriorates
Solution Approach 1:
The system uses feedback from predicted disturbance notifications to determine when charging is necessary. The backup management system receives predictions of upcoming disturbances, processes this information along with current charge levels and consumer preferences, and automatically initiates charging only when a predicted disturbance is forecasted, eliminating unnecessary charging while ensuring readiness.
Solution Approach 2:
The system performs preliminary charging based on advance notification of predicted disturbances. By receiving disturbance predictions ahead of time, the system can schedule charging operations in advance, ensuring devices are charged sufficiently before disturbances occur without requiring continuous monitoring or conservative over-charging.
4Ease of operation
If consumers manually manage backup device charging, then control over charging schedule is improved, but time consumption and complexity increase
Solution Approach 1:
The backup management system performs self-service by automatically receiving predicted disturbance notifications, determining optimal charging schedules based on consumer preferences, and executing charging operations without requiring manual consumer intervention. Consumers simply provide their preferences once, and the system handles all subsequent charging management autonomously, eliminating time consumption while maintaining control through preference-based automation.
Solution Approach 2:
The system accelerates the charging management process by using automated algorithms to rapidly process disturbance predictions and generate charging schedules, replacing slow manual decision-making with fast automated computation that respects consumer preferences while minimizing time investment from users.
Data Source
AI summary
A device includes a network interface and a processor. The network interface is configured to receive one or more preferences of a customer related to the charging of at least one backup device of the consumer. The network interface is also configured to receive at least one notification of at least one predicted power disturbance. The processor is configured to utilize the one or more consumer preferences and the at least one notification to generate a charging schedule of the at least one backup device and to generate one or more charging notifications for charging the at least one backup device. The one or more charging notifications are based on the charging schedule.