Building Load Reduction via Sensitivity-Based Logical Grouping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current demand response techniques for building load reduction are static and do not account for varying occupancy and illumination needs, leading to inefficient electricity savings, as they uniformly reduce lighting and HVAC loads without considering the criticality of different areas within a building.
Innovation Solution
A method and system that assign loads to logical groups based on sensitivity coefficients proportional to their impact on occupants, allowing for dynamic load reduction by determining baseline loads and adjusting power usage in response to demand response signals, thereby minimizing disruption and maximizing productivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If uniform load reduction is applied across all lighting loads during demand response events, then overall electricity consumption is reduced, but productivity and usability in critical areas are negatively impacted
Solution Approach 1:
The patent applies local quality by differentiating load reduction strategies across different building zones based on their criticality. Critical areas (laboratories, executive rooms) maintain higher lighting levels while non-critical areas (break rooms, corridors) experience greater reduction. This is achieved through zone-specific control algorithms that adjust lighting loads proportionally to each zone's importance, thereby reducing overall energy consumption while preserving productivity in critical work areas.
2Ease of manufacture
If static pre-configured load reduction methods are used during demand response events, then implementation is simple and fast, but the solution does not adapt to varying occupancy and environmental conditions
Solution Approach 1:
The patent implements dynamics by transitioning from static pre-configured load reduction to dynamic adaptive control. The system continuously monitors occupancy sensors, environmental conditions, and building zone criticality levels to adjust lighting and HVAC loads in real-time during demand response events. This dynamic approach allows the system to adapt to varying conditions while maintaining relatively simple implementation through centralized control algorithms that process sensor data and automatically adjust loads accordingly.
3Productivity
If critical areas maintain higher lighting levels during demand response, then productivity is preserved, but overall load reduction effectiveness is diminished
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting lighting level parameters based on zone criticality and occupancy. Instead of using fixed lighting levels, the system modifies illumination parameters (intensity, duration) according to each zone's characteristics. Critical areas receive maintained or minimally reduced lighting, while non-critical areas experience proportionally greater reduction. This parameter-based differentiation optimizes the balance between preserving productivity in essential work areas and maximizing overall energy savings across the entire building.
Data Source
AI summary
Apparatuses, methods and systems for managing a building load reduction of a plurality of loads within a building are disclosed. One method includes assigning one or more loads of the plurality of loads to logical groups, assigning a sensitivity coefficient to each of the logical groups, wherein the sensitivity coefficient is directly proportional to an impact on occupants in the building to load changes, determining the baseline load for each of the logical groups, receiving a power reduction demand response, and reducing a load of each logical group based upon the sensitivity coefficient.