Building automation and control system modeling and reporting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modern HVAC systems in large building complexes face inefficiencies due to the complexity of calibrating and maintaining various subsystems, leading to wasteful energy usage.
Innovation Solution
A system that mathematically models HVAC components, using actual data to generate optimized set points for subsystems, which are then fed back to controllers to improve operation and increase efficiency, by importing data into mathematical models and applying logical conclusions weighted for specific instructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If HVAC systems use multiple subsystems with various sensors and control units, then the system functionality and coverage are improved, but the device complexity and difficulty of calibration increase
Solution Approach 1:
The patent segments the complex HVAC system into multiple independent subsystems (boilers, chillers, ventilation, lighting, plumbing, energy management), each with its own controller and mathematical model. This allows each subsystem to be calibrated and maintained independently, reducing overall system complexity while preserving comprehensive functionality.
Solution Approach 2:
The patent creates a universal mathematical modeling framework that can be applied across all different HVAC subsystems. The same modeling approach, data import process, and optimization methodology work for boilers, chillers, ventilation systems, and other subsystems, providing a unified solution for diverse components.
2Reliability
If HVAC systems periodically calibrate and maintain subsystems, then system reliability is improved, but energy usage efficiency deteriorates due to complexity
Solution Approach 1:
The patent implements continuous feedback loops where actual system data is constantly imported, compared against mathematical models, and used to generate optimized set points. This real-time feedback ensures systems operate at peak efficiency without requiring periodic shutdowns for calibration, maintaining both reliability and energy efficiency.
Solution Approach 2:
The mathematical models automatically analyze system data and generate optimization instructions without requiring external intervention. The system self-diagnoses inefficiencies and self-corrects by implementing optimized set points, reducing maintenance overhead while maintaining reliability and efficiency.
3Measurement precision
If mathematical models import and analyze system data from separate subsystem controllers, then manufacturing precision and measurement accuracy are improved, but device complexity increases
Solution Approach 1:
The patent introduces mathematical models as intermediary layers between the physical HVAC subsystems and the central server. These models import data from various subsystem controllers, process the information using standardized algorithms, and generate optimized set points, thereby simplifying the overall system architecture while improving measurement and analysis precision.
4Productivity
If the system provides optimized set points fed back to subsystem controllers, then productivity and energy efficiency are improved, but loss of information increases due to data processing requirements
Solution Approach 1:
The patent transforms raw system data into optimized set points by changing key operational parameters. The mathematical models analyze extensive data but distill it into essential parameter adjustments for each subsystem, maintaining productivity improvements while minimizing information loss through focused parameter optimization rather than processing all raw data.
Data Source
AI summary
Systems and methods for modeling, reporting, controlling and optimizing HVAC systems are provided. A server receives HVAC system data, processes the data and sends the processed data to a client device. The client device receives the processed data and then makes certain choices of analog and digital rules to apply to the data to reach conclusions about certain mechanical states of the system and flow efficiencies. The rule choices are sent to the server. The server analyzes the HVAC system based on the rules and generates a report. The report can be used to optimize the mechanical components of the HVAC system or control them directly in a feedback loop.