Energy Budget Control Using Predictive Equipment Adjustment
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Solution Overview
Problem
Existing systems struggle to accurately quantify energy savings and adhere to energy budgets due to factors like weather variability, equipment degradation, and inconsistent billing periods, making it difficult to measure and manage energy consumption effectively.
Innovation Solution
A system that uses sensors and machine learning to monitor energy use, predict future consumption based on environmental and facility data, and automatically adjust equipment settings to adhere to a predetermined budget by implementing real-time adjustments within tolerance levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional energy metering methods are used, then installation cost is reduced, but measurement precision deteriorates due to inability to accurately allocate energy use to specific devices
Solution Approach 1:
The patent segments the energy measurement system into multiple levels: main service metering, submetering for different areas/devices, and circuit-level monitoring. This segmentation enables precise energy allocation to specific devices and areas while maintaining manageable system complexity through modular deployment.
Solution Approach 2:
The patent introduces an energy management system as an intermediary that collects, processes, and analyzes data from various meters and sensors. This intermediary layer provides centralized control and reporting capabilities, enabling precise measurement without requiring complex individual device modifications.
2Measurement precision
If simple month-to-month energy comparisons are made, then ease of operation is improved, but measurement precision deteriorates due to weather variability and billing period inconsistencies
Solution Approach 1:
The system performs preliminary actions by collecting and storing detailed energy consumption data, weather data, and operational parameters continuously before comparisons are needed. This pre-collection of data enables accurate retroactive analysis and comparison while maintaining simple user interfaces for viewing results.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors energy consumption, compares it against baseline data adjusted for weather and operational conditions, and provides feedback on actual energy savings achieved. This feedback loop enables precise measurement while automating the complexity of adjustments and comparisons.
3Productivity
If no real-time monitoring is implemented, then device complexity is reduced, but productivity deteriorates due to inability to make timely energy management decisions
Solution Approach 1:
The energy management system performs self-service by automatically collecting data from meters and sensors, processing the information, generating reports, and providing recommendations without requiring constant human intervention. This automation improves energy management efficiency while keeping the user interface simple and manageable.
Solution Approach 2:
The patent creates a universal energy management platform that handles multiple functions: data collection from various sources, weather adjustment calculations, baseline comparisons, reporting, and control operations. This multi-functional system improves productivity by consolidating what would otherwise require multiple separate systems into a single manageable platform.
Data Source
AI summary
A system and method for the quantification and automatic control of energy usage for equipment through active measurement, intelligent monitoring, and predictive analysis enabling the adherence to energy budgets through automatic adjustment of the operation of the equipment.