Demand Response System Peak Load Shifting
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Solution Overview
Problem
Conventional demand response systems cause user inconvenience by relying on simple cost or price-based control schemes to manage household appliances during high power rates, leading to inefficient power consumption.
Innovation Solution
A demand response method that adjusts the operation start time of high-power-consumption loads, such as refrigerators and air-conditioners, to low-power-rate intervals, using a processor to estimate and shift the operation time points based on electricity demand patterns, thereby reducing peak power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional demand response systems use simple cost or price-based control schemes to limit household appliance operation during high power rates, then power consumption during peak periods is reduced, but user convenience deteriorates
Solution Approach 1:
The system performs pre-cooling or pre-heating operations before high power-rate intervals begin. The controller predicts upcoming high power-rate periods and advances appliance operations (such as cooling appliances before peak hours) to complete necessary tasks before expensive periods, thereby reducing peak power consumption while maintaining service quality and user convenience.
2Loss of energy
If load operation time points are shifted to low-power-rate intervals, then electricity bills are reduced, but system complexity increases
Solution Approach 1:
The system incorporates a controller that receives real-time power rate information and appliance operation status, compares current conditions with predicted future conditions, and automatically adjusts operation timing. This feedback mechanism enables intelligent load shifting without requiring complex user intervention, as the system continuously monitors and responds to changing power rate conditions.
Solution Approach 2:
The demand response system automatically manages load scheduling without requiring direct user involvement. The controller independently analyzes power rate patterns, predicts optimal operation times, and executes timing adjustments based on appliance characteristics and user preferences, enabling the system to serve itself and reduce complexity for the end user.
3Ease of manufacture
If simple price-based control is used to manage appliances during high power rates, then implementation ease is improved, but power consumption efficiency deteriorates
Solution Approach 1:
The system performs pre-cooling or pre-heating operations before high power-rate intervals begin. The controller predicts upcoming high power-rate periods and advances appliance operations (such as cooling appliances before peak hours) to complete necessary tasks before expensive periods, thereby reducing peak power consumption while maintaining service quality and user convenience.
Solution Approach 2:
The system incorporates a controller that receives real-time power rate information and appliance operation status, compares current conditions with predicted future conditions, and automatically adjusts operation timing. This feedback mechanism enables intelligent load shifting without requiring complex user intervention, as the system continuously monitors and responds to changing power rate conditions.
Data Source
AI summary
A demand response (DR) system, computer-readable medium and method are disclosed. The DR system controls a high-power-consumption load to be pre-operated or post-operated in a low-power-rate interval instead of a high-power-rate interval, and reduces an amount of power consumption required for a high-power-rate interval, resulting in reduction of power rates. In addition, limitation to household appliance operation is minimized, to greatly reduce inconvenience of a user.