Occupancy-Based Demand Response Dispatch for Building Energy Management
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Solution Overview
Problem
Current methods for determining occupancy in buildings are inadequate for real-time analysis and energy management, as they rely on subjective scaling and 'eyeballing' techniques, which are inefficient and inaccurate, especially for comparing energy consumption across different periods and facilities.
Innovation Solution
A system that uses energy consumption and outside temperature data to automatically determine occupancy levels, employing a network operations center with computer code to process streams and generate occupancy levels, which are then used to prioritize demand response programs and optimize energy use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated occupancy determination using energy consumption and temperature data is implemented, then occupancy determination accuracy is improved, but system complexity increases
Solution Approach 1:
The patent introduces an occupancy determination system as an intermediary that processes energy consumption data and temperature data to calculate occupancy levels. This intermediary system acts as a mediator between the available data streams and the required occupancy information, using a standardized formula that combines these data sources with normalization factors to produce accurate occupancy determinations without requiring direct complex sensor networks in each building.
Solution Approach 2:
The patent uses energy consumption data as a proxy or copy of actual occupancy levels. Instead of directly measuring occupancy through sensors, the system copies the information contained in energy consumption patterns and temperature data to infer occupancy. This approach allows occupancy determination without deploying complex physical sensing infrastructure, thereby improving accuracy while managing system complexity.
2Productivity
If real-time occupancy analysis is implemented for demand response prioritization, then energy management effectiveness is improved, but data processing requirements increase
Solution Approach 1:
The patent implements preliminary action by pre-calculating and storing normalization factors, building characteristics, and baseline energy consumption patterns. These pre-computed elements are stored in databases and readily available when real-time occupancy determination is needed. This preliminary preparation significantly reduces the computational burden during real-time operations, enabling fast energy management decisions without excessive data processing delays.
Solution Approach 2:
The patent replaces complex mechanical data processing systems with streamlined computational formulas and algorithms. Instead of using elaborate data analysis mechanisms, the system employs a standardized occupancy determination formula that efficiently processes energy consumption and temperature data. This substitution reduces computational complexity and processing time while maintaining real-time capability for demand response prioritization.
Data Source
AI summary
A method for prioritizing a demand response program event based on occupancy for one or more buildings of one or more building types participating in a demand response program, the method comprising: receiving energy consumption and outside temperature streams Ei(h,T) corresponding to a portion of the one or more buildings, the energy consumption provided by streaming consumption sources, and receiving and employing occupancy components for each of the one or more buildings within the portion to process the streams, and generating occupancy levels corresponding to the one or more buildings within the portion, and assigning the occupancy levels to remaining ones of the one or more buildings not in the portion; and optimizing execution of the demand response program event by employing the occupancy components to prioritize dispatch messages to the one or more buildings to achieve objectives of the demand response program event.


