[Paper Review] Distributed Control of Multi-zone HVAC Systems Considering Indoor Air Quality

Yu Yang, Seshadhri Srinivasan+2 more|arXiv (Cornell University)|Mar 17, 2020

Building Energy and Comfort Optimization32 references4 citations

TL;DR

This paper proposes a two-level distributed control method (TLDM) for multi-zone HVAC systems that jointly optimizes thermal comfort and indoor air quality (IAQ) represented by CO2 levels while minimizing energy cost. By decoupling thermal comfort control from IAQ regulation through a hierarchical, distributed computation framework, TLDM achieves near-optimal energy savings with guaranteed IAQ compliance, outperforming both centralized and existing distributed methods by 8–10% in energy reduction.

ABSTRACT

This paper studies a scalable control method for multi-zone heating, ventilation and air-conditioning (HVAC) systems to optimize the energy cost for maintaining thermal comfort and indoor air quality (IAQ) (represented by CO2) simultaneously. This problem is computationally challenging due to the complex system dynamics, various spatial and temporal couplings as well as multiple control variables to be coordinated. To address the challenges, we propose a two-level distributed method (TLDM) with a upper level and lower level control integrated. The upper level computes zone mass flow rates for maintaining zone thermal comfort with minimal energy cost, and then the lower level strategically regulates zone mass flow rates and the ventilation rate to achieve IAQ while preserving the near energy saving performance of upper level. As both the upper and lower level computation are deployed in a distributed manner, the proposed method is scalable and computationally efficient. The near-optimal performance of the method in energy cost saving is demonstrated through comparison with the centralized method. In addition, the comparisons with the existing distributed method show that our method can provide IAQ with only little increase of energy cost while the latter fails. Moreover, we demonstrate our method outperforms the demand controlled ventilation strategies (DCVs) for IAQ management with about 8-10% energy cost reduction.

Motivation & Objective

• To address the growing need for energy-efficient HVAC control that simultaneously maintains thermal comfort and indoor air quality (IAQ), particularly CO2 levels.
• To overcome the computational complexity arising from coupled dynamics and control variables in multi-zone HVAC systems.
• To develop a scalable, distributed control framework that ensures IAQ compliance without sacrificing energy efficiency.
• To demonstrate that joint optimization of thermal comfort and IAQ leads to significant energy savings compared to conventional strategies.

Proposed method

• The method employs a two-level distributed architecture: an upper-level control (ULC) that computes zone mass flow rates for thermal comfort with minimal energy cost.
• The lower-level control (LLC) adjusts zone mass flow rates and ventilation rates to satisfy IAQ constraints while preserving the energy efficiency of the ULC.
• Both ULC and LLC use distributed optimization techniques, enabling scalability and computational efficiency in large multi-zone systems.
• The ULC solves a convex optimization problem to minimize energy cost subject to thermal comfort constraints.
• The LLC enforces IAQ compliance by dynamically regulating fresh air ventilation based on real-time CO2 levels and occupancy.
• The method leverages problem structure to decouple thermal and IAQ control, enabling efficient, distributed computation.

Experimental results

Research questions

• RQ1 Can a distributed control framework achieve near-optimal energy savings in multi-zone HVAC systems while ensuring IAQ compliance?
• RQ2 How does the proposed two-level distributed method compare to centralized and existing distributed control strategies in terms of energy efficiency and IAQ performance?
• RQ3 What is the trade-off between energy cost and IAQ compliance when integrating CO2 control into HVAC systems?
• RQ4 How does the hierarchical structure of the TLDM improve scalability and computational efficiency compared to centralized methods?
• RQ5 To what extent does the TLDM outperform demand-controlled ventilation (DCV) strategies in energy savings while maintaining IAQ?

Key findings

• The TLDM achieves near-optimal energy cost savings with a sub-optimality gap of approximately 4% compared to the centralized optimal solution.
• In a 50-zone simulation, TLDM reduced total energy cost by 8–10% compared to demand-controlled ventilation (DCV) strategies, which rely solely on occupancy for ventilation.
• The TLDM successfully maintained CO2 levels within the target range of 0–800 ppm across all zones, even during high-occupancy periods.
• The method demonstrated superior scalability and computational efficiency due to its distributed implementation, with computation times significantly lower than centralized methods.
• Unlike the DTBSS method, which fails to ensure IAQ compliance, TLDM provides both IAQ and energy savings with only a marginal increase in energy cost.
• The ventilation rate in TLDM dynamically aligns with occupancy patterns—increasing during high-occupancy hours and decreasing during off-peak times—ensuring efficient IAQ management.