Appliance Cycle Scheduling via Energy Rate Thresholds
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Solution Overview
Problem
Existing energy management solutions for home appliances are inefficient in minimizing energy costs, as they often require suspending appliance cycles mid-operation, which can lead to increased energy consumption and costs, especially when resuming after suspension.
Innovation Solution
A method that calculates projected energy usage rates for future time periods, using a user-defined tradeoff factor to determine a rate threshold, allowing for delayed appliance cycles when energy costs exceed this threshold, thereby optimizing energy consumption and reducing overall energy bills.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If existing energy management solutions delay appliance cycles, then energy costs are reduced, but appliance cycles are suspended mid-operation leading to increased energy consumption
Solution Approach 1:
The system performs preliminary actions by completing the entire appliance cycle before the delayed time period begins, rather than suspending mid-cycle. The controller determines a completion time that allows the cycle to finish before the new start time, ensuring reliable completion while still achieving energy cost reduction by delaying the overall operation.
Solution Approach 2:
The system dynamically adjusts the cycle timing based on projected energy costs. The controller modifies the start time and completion time of appliance cycles according to predicted energy pricing, creating a dynamic scheduling system that optimizes energy costs while maintaining operational reliability.
2Loss of energy
If appliance cycles are completed before delayed time periods, then energy costs are minimized, but the scheduling complexity increases
Solution Approach 1:
The system uses feedback from projected energy cost data to automatically adjust scheduling decisions. The controller receives or predicts energy cost information, processes this feedback, and automatically modifies appliance cycle timing accordingly, reducing scheduling complexity through automated decision-making based on cost feedback.
Solution Approach 2:
The scheduling system performs self-service by automatically determining optimal start and completion times based on projected energy costs without requiring complex user intervention. The controller independently analyzes energy cost projections and adjusts appliance schedules autonomously, simplifying the overall system complexity.
Data Source
AI summary
A method of determining an optimal schedule for performing a cycle of operation in the appliance wherein the schedule is a function of the tradeoff factor wherein the tradeoff factor is used to determine a rate threshold above which a delay request is included in the optimal schedule, and the rate threshold is a summation of I) an average of a series of projected rates for the use of the resource by the appliance for a future series of time periods and II) a product of the tradeoff factor and a standard deviation of the series of projected rates.