Adaptive Energy Control Device for HVAC and Lighting
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Solution Overview
Problem
Existing energy consumer control methods, particularly for space heating and air conditioning, are inflexible and require manual reprogramming to adapt to changes in user behavior, leading to inefficient energy usage and comfort issues.
Innovation Solution
A control method that predicts future energy consumption by analyzing historical data, using templates to correlate past consumption patterns with current situations, allowing for self-learning and adaptive control of energy consumers without the need for predefined user states or setup phases, enabling optimal comfort and energy efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If time-controlled processes are used for energy consumers, then energy consumption can be managed according to fixed schedules, but the system becomes inflexible and requires manual reprogramming when user behavior changes
Solution Approach 1:
The control device automatically learns user behavior patterns by analyzing historical energy consumption data and sensor information, eliminating the need for manual programming. The system self-adjusts control parameters based on detected patterns, providing adaptability without increasing operational complexity for users.
Solution Approach 2:
The system continuously monitors energy consumption data and sensor inputs, compares actual behavior with predicted patterns, and automatically adjusts control parameters. This closed-loop feedback mechanism enables the system to adapt to changing user behavior dynamically without manual intervention.
2Speed
If sluggish energy consumers like space heating are controlled manually, then user comfort can be adjusted, but the system cannot provide desired climate at the push of a button and requires several hours of lead time
Solution Approach 1:
The system predicts user presence and desired climate conditions in advance based on learned behavior patterns, and automatically initiates heating or cooling operations beforehand. This preliminary action ensures that the desired climate is ready when the user arrives, eliminating wait time while maintaining comfort.
Solution Approach 2:
The control system dynamically adjusts operation timing and intensity based on real-time predictions of user behavior and environmental conditions. Rather than fixed schedules, the system continuously adapts its control strategy to minimize lead time while ensuring comfort requirements are met.
3Adaptability or versatility
If roller shutter and awning controls are used to prevent overheating, then room temperature can be controlled, but the system cannot actively heat rooms and buildings effectively
Solution Approach 1:
The control device manages multiple energy consumers including roller shutters, awnings, space heating, and air conditioning through a unified learning-based system. The same behavioral prediction and optimization algorithms are applied across different device types, enabling versatile control while improving overall energy efficiency through coordinated operation.
Data Source
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AI summary
The consumer load controlling method involves predicting futuristic energy consumption (Emp) of an energy consumer by analyzing type and technology of the energy consumption values (Ee). The energy consumers are controlled particularly activated or deactivated based on the predicted energy consumption. The energy consumer is a heating regulating unit, an airconditioning unit, a blackout control system for the selective blackout of the room of the building, or a light regulation unit for the selective illumination of the room of the building. An independent claim is included for a control device for controlling one or more energy consumers within a building.