System for optimization of building heating and cooling systems
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Solution Overview
Problem
Commercial and residential buildings face high energy consumption costs due to inefficient heating, ventilation, and cooling (HVAC) systems, including wasteful energy use, inadequate insulation, and the inability to effectively utilize local energy sources, leading to significant environmental impact and economic burdens.
Innovation Solution
An optimized HVAC system design method that automatically imports energy model data, simulates energy use to determine an optimized system design, develops intelligent controls, and exports these controls directly to the HVAC system, allowing for efficient operation, tracking, and implementation of energy-saving strategies, including geothermal heat exchanger management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If intelligent building energy operations are custom designed for each individual building, then energy efficiency is improved, but design cost and time consumption increase significantly
Solution Approach 1:
The patent uses energy models as virtual copies of buildings to simulate and optimize energy performance before actual construction. These digital twins allow customization of energy strategies for each building without requiring physical prototypes or extensive trial-and-error on-site adjustments.
Solution Approach 2:
The system performs energy optimization simulations during the design phase rather than after construction. By conducting energy models and optimizing HVAC systems before building completion, the patent prevents energy inefficiencies from being built into the physical structure, avoiding costly retrofits later.
2Reliability
If control systems are extensively programmed and commissioned for optimized energy operations, then system performance is improved, but commissioning cost and time increase
Solution Approach 1:
The patent implements self-adjusting control systems that automatically optimize HVAC operation based on real-time building conditions and pre-loaded energy models. The system performs self-commissioning by comparing actual performance against simulated benchmarks and autonomously adjusting parameters without requiring extensive manual programming or commissioning personnel.
Solution Approach 2:
The system continuously monitors actual energy consumption and building conditions, comparing them against the energy model predictions. This feedback loop enables automatic adjustment of control parameters to maintain optimal performance, eliminating the need for lengthy manual commissioning processes.
3Temperature
If conventional HVAC systems are used to meet peak thermal loads, then temperature requirements are satisfied, but equipment size and construction cost increase
Solution Approach 1:
The patent changes the operational parameters of HVAC systems by using thermal energy storage to decouple peak load requirements from continuous operation. Instead of sizing equipment for maximum instantaneous demand, the system stores thermal energy during off-peak periods and releases it during peak periods, allowing smaller equipment to satisfy temperature requirements.
Solution Approach 2:
The system pre-charges or pre-discharges thermal energy storage systems during periods of low demand before peak thermal loads occur. This preliminary action of storing thermal energy in advance allows the HVAC equipment to be sized for average rather than peak conditions, reducing equipment size and construction costs.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces energy consumption and equipment size, lowers construction costs, and enables cost-effective, timely implementation of intelligent building energy operations, significantly reducing market barriers to widespread adoption by minimizing human interaction and errors in control system design and commissioning.
Implementation Method 1
The system can include a plurality of geothermal heat exchangers
Implementation Method 2
simulating energy use of a virtual heating and cooling system operating a thermal source or sink
Data Source
AI summary
A method of designing an optimized heating and cooling system includes: (1) automatically importing data from an energy model into an optimization model; (2) simulating energy use of a virtual heating and cooling system operating a thermal source or sink with the optimization model based upon the data from the energy model to obtain an optimized system design; (3) developing controls for an actual heating and cooling system based upon the optimized system design; and (4) automatically exporting the controls directly to a controller for the actual heating and cooling system.