{"title":"Real-time predictive control of HVAC systems for factory building using lightweight data-driven model","authors":"Young Sub Kim, C. Park","doi":"10.1080/19401493.2023.2182363","DOIUrl":null,"url":null,"abstract":"This paper presents a real-time implementation of model predictive control (MPC) for HVAC systems in an ice-cream factory building. The target building consists of two large open spaces served by two HVAC systems. We developed four artificial neural network (ANN) models that predict the thermal states of the supply air and indoor air of the two thermal zones and prove to be accurate enough (MBE = 2.65, CVRMSE = 9.43). The control variables employed in this study are the number of operating chillers, frequency of supply-air fan inverter and outdoor-air intake ratio. The objective function minimizes total energy use, and a constraint was set to maintain average indoor air temperatures close to set points. Real-time MPC was implemented at a sampling time of 20 min from 3 August to 30 August 2021 and could save approximately 31.7% of electricity when compared to the existing simple rule-based control.","PeriodicalId":49168,"journal":{"name":"Journal of Building Performance Simulation","volume":"abs/1902.05877 1","pages":"507 - 525"},"PeriodicalIF":2.2000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Building Performance Simulation","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/19401493.2023.2182363","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 2
Abstract
This paper presents a real-time implementation of model predictive control (MPC) for HVAC systems in an ice-cream factory building. The target building consists of two large open spaces served by two HVAC systems. We developed four artificial neural network (ANN) models that predict the thermal states of the supply air and indoor air of the two thermal zones and prove to be accurate enough (MBE = 2.65, CVRMSE = 9.43). The control variables employed in this study are the number of operating chillers, frequency of supply-air fan inverter and outdoor-air intake ratio. The objective function minimizes total energy use, and a constraint was set to maintain average indoor air temperatures close to set points. Real-time MPC was implemented at a sampling time of 20 min from 3 August to 30 August 2021 and could save approximately 31.7% of electricity when compared to the existing simple rule-based control.
期刊介绍：
The Journal of Building Performance Simulation (JBPS) aims to make a substantial and lasting contribution to the international building community by supporting our authors and the high-quality, original research they submit. The journal also offers a forum for original review papers and researched case studies
We welcome building performance simulation contributions that explore the following topics related to buildings and communities:
-Theoretical aspects related to modelling and simulating the physical processes (thermal, air flow, moisture, lighting, acoustics).
-Theoretical aspects related to modelling and simulating conventional and innovative energy conversion, storage, distribution, and control systems.
-Theoretical aspects related to occupants, weather data, and other boundary conditions.
-Methods and algorithms for optimizing the performance of buildings and communities and the systems which service them, including interaction with the electrical grid.
-Uncertainty, sensitivity analysis, and calibration.
-Methods and algorithms for validating models and for verifying solution methods and tools.
-Development and validation of controls-oriented models that are appropriate for model predictive control and/or automated fault detection and diagnostics.
-Techniques for educating and training tool users.
-Software development techniques and interoperability issues with direct applicability to building performance simulation.
-Case studies involving the application of building performance simulation for any stage of the design, construction, commissioning, operation, or management of buildings and the systems which service them are welcomed if they include validation or aspects that make a novel contribution to the knowledge base.
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