Power Demand Stabilization via Predictive Load Shedding
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Solution Overview
Problem
Industrial power consumption poses significant environmental and financial risks, with existing technologies failing to effectively manage power demand in industrial facilities, leading to high energy costs and environmental impact.
Innovation Solution
Implementing a system that stabilizes power demand by identifying low-priority controllable devices and adjusting their power usage to match the maximum power draw of high-priority devices during peak events, using a facility coordinator and predictive algorithms to optimize energy use based on sensor data and priority databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high power draw devices are operated without coordination, then productivity is maintained, but power demand spikes increase energy costs and environmental impact
Solution Approach 1:
The system performs preliminary actions by predicting future power draw events using scheduled data and power profiles before the actual events occur. When a high power draw event is predicted, the system proactively adjusts lower priority devices beforehand to compensate, preventing power demand spikes while maintaining productivity of critical devices.
2Loss of energy
If power to low priority devices is reduced during peak events, then energy costs are lowered, but device complexity increases due to coordination requirements
Solution Approach 1:
The system implements self-service through automated prediction and coordination algorithms that independently manage power distribution without requiring complex manual intervention. The facility coordinator automatically predicts power draw events, identifies appropriate lower priority devices to adjust, and executes power reallocation based on predefined priorities and power profiles, simplifying the overall system operation.
3Object-generated harmful factors
If power draw is stabilized by coordinating multiple devices, then environmental impact is reduced, but ease of operation decreases due to centralized control requirements
Solution Approach 1:
The system employs feedback mechanisms by continuously monitoring actual power draw events and comparing them against predicted values. This feedback loop enables the facility coordinator to refine predictions and adjust coordination strategies, achieving environmental benefits through automated stabilization while maintaining operational simplicity through adaptive, data-driven control.
Data Source
AI summary
Some embodiments include electric power demand stabilization methods and systems that may include receiving an indication that a specific controllable device will have a high power draw event; retrieving a power draw profile for the specific controllable device that includes at least a maximum power draw and an event duration; identifying a plurality of low priority controllable devices with a combined power draw that is substantially equal to the maximum power draw of the specific controllable device; and turning off the plurality of low priority controllable devices for a time period substantially equal to the event duration.