Building energy analysis and management system
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Solution Overview
Problem
Building professionals lack an affordable and reliable method to accurately determine HVAC system inefficiencies and verify performance improvements, making it difficult to monitor and control energy consumption effectively.
Innovation Solution
The system measures and verifies HVAC unit performance using pressure independent valves, gathering data through Surge Panels and analyzing it with a central server that compares actual and predicted values, generates inferences, and suggests optimizations for improved efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional HVAC monitoring systems are used, then basic temperature control is achieved, but measurement precision of critical variables is insufficient
Solution Approach 1:
The system segments the HVAC monitoring into multiple independent measurement components: flow meters for fluid flow measurement, temperature sensors for thermal variables, pressure sensors for pressure differential, and power meters for energy consumption. Each sensor measures a specific parameter independently, collectively providing comprehensive high-precision measurement of all critical variables without requiring a single complex measurement device.
2Loss of energy
If comprehensive HVAC monitoring is implemented, then energy consumption control is improved, but system cost increases
Solution Approach 1:
The control system serves multiple functions simultaneously: it monitors flow rate, temperature, pressure, and power consumption; calculates energy efficiency metrics; compares actual performance against baseline and predicted values; generates diagnostic inferences; and provides optimization recommendations. This multi-functionality consolidates what would otherwise require separate systems into a single integrated platform, reducing overall system cost while comprehensively addressing energy consumption control.
Solution Approach 2:
The system continuously measures actual HVAC performance and feeds this data back to the control server, which compares it against baseline and predicted values. This feedback loop enables real-time detection of inefficiencies and automatic generation of optimization recommendations, allowing building professionals to control energy consumption effectively without requiring expensive manual monitoring and analysis processes.
3Reliability
If baseline comparisons are performed to verify performance improvements, then measurement reliability is enhanced, but difficulty of detecting and measuring increases
Solution Approach 1:
The system establishes baseline performance metrics before HVAC upgrades or changes are implemented. This preliminary measurement of flow rate, temperature, pressure, and power consumption creates a reference point against which future performance can be objectively compared. The baseline serves as a predetermined standard that simplifies subsequent verification of performance improvements, eliminating the need for complex retrospective analysis.
Solution Approach 2:
The control server acts as an intermediary that automatically performs the complex task of comparing actual measurements against baseline and predicted values. Rather than requiring building professionals to manually analyze multiple variables and determine whether performance improvements are real or due to external factors, the server processes this comparison automatically and generates diagnostic inferences, significantly reducing the difficulty of detecting and measuring true performance changes.
4Productivity
If granular control is implemented to address identified inefficiencies, then productivity is improved, but device complexity increases
Solution Approach 1:
The system provides dynamic, granular control of HVAC operations by adjusting flow rates, temperatures, and other parameters in real-time based on measured performance and diagnostic inferences. Rather than requiring fixed, complex control mechanisms for each possible inefficiency scenario, the system adapts its control strategy dynamically according to actual operating conditions and identified problems, improving productivity without requiring overly complex predetermined control systems.
Data Source
AI summary
This application relates to a building energy analysis and management system for measurement and verification of building performance. The system can analyze, optimize, manage, maintain, trouble shoot, and/or modify building systems, such as HVAC systems, in connection with the building energy usage. Measurements may be gathered for one or more HVAC units coupled to pressure independent valves, and sent to one or more Surge Panels that pass data to remote analysis servers, which can receive other system or external data. The analysis servers compare measurements to predicted values and can standardize the predicted values to account for external conditions. The comparison can result in difference values used to generate probable causes and optimization recommendations. The system outputs reports or other data display using a graphical user interface that can be adjusted for an anticipated user.