How Multi-Criterion Optimized Control Methods Improve Effectiveness of Multi-Zone Building Heating System Upgrading

Ahmad Esmaeilzadeh, Brian Deal, Aghil Yousefi-Koma () and Mohammad Reza Zakerzadeh
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Ahmad Esmaeilzadeh: Smart Energy Design Assistance Center (SEDAC), Department of Landscape Architecture, University of Illinois Urbana-Champaign, Champaign, IL 61820, USA
Brian Deal: Department of Landscape Architecture, University of Illinois Urbana-Champaign, Champaign, IL 61820, USA
Aghil Yousefi-Koma: Center of Advanced Systems and Technologies (CAST), School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran 15614, Iran
Mohammad Reza Zakerzadeh: School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran 15614, Iran

Energies, 2022, vol. 15, issue 22, 1-27

Abstract: This paper aims to develop multi-objective optimized control methods to improve the performance of retrofitting building heating systems in reducing consumed energy as well as providing comfortable temperature in a multi-zone building. While researchers evaluate various controllers in specific systems, providing a comprehensive controller for retrofitting the existing heating systems of multi-zone buildings is less investigated. A case study approach with a four-story residential building is simulated. The building energy consumption is modeled by EnergyPlus. The model is validated with energy data. Then, the building steam system model is upgraded, and in the other case, renewed by a hydronic system instead of a steam one. Three optimized controller groups are developed, including Model Predictive Controller (MPC), fuzzy controllers (Fuzzy Logic Controller (FLC) and an Optimized Fuzzy Sliding Mode Controller (OFSMC)), and optimized traditional ones. These controllers were applied to the upgraded steam and hydronic heating systems. The control methods affected the tuning of the boiler feed flow by regulating the condensing cycle and circulating the pump flow of the hydronic system. Accordingly, renewing the heating system improves energy efficiency by up to 29% by implementing a hydronic system instead of the steam one. The fuzzy controllers increased renewing effectiveness by providing comfortable temperatures and reducing building environmental footprints by up to 95% and 12%, respectively, compared with an on/off controller baseline.

Keywords: optimization; model predictive control (MPC); fuzzy logic system; Optimized Fuzzy Sliding Mode Controller (OFSMC); heating system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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