Optimization-informed Rule Extraction for HVAC system: A Case Study of Dedicated Outdoor Air System Control in a
Youngsik Choi1, Xing Lu1,2, Zheng O'Neill1
1J. Mike Walker '66 Department of Mechanical Engineering, Texas A&M University, College Station, TX, United States.
Energy and Buildings
|April 15, 2024
Summary
Optimizing dedicated outdoor air systems (DOAS) with rule extraction saves energy and improves indoor air quality. This simulation-based approach offers practical, implementable control sequences for building operators.
Area of Science:
- HVAC systems engineering
- Building energy efficiency
- Indoor environmental quality
Background:
- Dedicated Outdoor Air Systems (DOAS) are crucial for maintaining indoor air quality post-COVID-19 by supplying 100% fresh air.
- Current DOAS control strategies often lack practical guidance, leading to issues like insufficient ventilation, dehumidification, and energy waste.
- Existing advanced controls can be overly complex for building designers and operators.
Purpose of the Study:
- To develop a simulation-based framework for generating an implementable supply air temperature control sequence for DOAS.
- To optimize DOAS control for both energy savings and practical application in buildings.
- To ensure improved energy-saving potential while guaranteeing the implement-ability of the control logic.
Main Methods:
- Modeled a U.S. Department of Energy prototype primary school in EnergyPlus, including a DOAS with energy recovery and fan-coil units.
- Employed a Genetic Algorithm to determine the optimal supply air temperature control sequence for minimizing HVAC energy costs.
- Utilized Decision Tree analysis to extract practical operational rules from the optimal control sequence.
Main Results:
- Optimization-informed rule extraction control saved approximately 13% in energy costs and 25% in energy consumption compared to conventional controls.
- Energy savings were primarily driven by reduced heating energy consumption.
- The developed control strategy closely approximated optimal control performance, achieving significant energy reductions with reduced complexity.
Conclusions:
- A simulation-based framework using optimization and rule extraction can yield highly effective and implementable DOAS control sequences.
- This approach offers a practical solution for enhancing energy efficiency and indoor air quality in buildings.
- Optimization-informed rule extraction provides a balance between control performance and operational simplicity for building designers and operators.
Keywords:
Building energy simulationDedicated Outdoor Air SystemGenetic AlgorithmOptimal controlRule extractionMore Related Videos
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