Energy-saving building system integration with a smart and low-cost sensing/control network for sustainable and healthy living environments: Demonstration case study

Han, Kwanghoon; Zhang, Jensen

doi:10.1016/j.enbuild.2020.109861

Cited by 33 publications

(18 citation statements)

References 17 publications

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“…Healthy buildings need energy-efficient designs that can also reduce the cost of living [ 32 ]. It is crucial to work on the development of IAQ monitoring systems with low power consumption requirements [ 110 ].…”

Section: Discussionmentioning

confidence: 99%

“…Two [ 26 , 27 ] were excluded following EC4 as they were review papers or theoretical analysis (EC3, EC4). Furthermore, 20 studies [ 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 ] were removed due to missing information about the design methodology and the type of sensors used for measuring IAQ parameters (IC4, EC3). In addition, five more studies [ 48 , 49 , 50 , 51 , 52 ] were excluded as they were focused on thermal comfort parameters only or had no relevant details about IAQ sensors (IC2, IC3, EC3).…”

Section: Methodsmentioning

confidence: 99%

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Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review

Saini

Dutta

Marques

2020

IJERPH

129

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Indoor air quality has been a matter of concern for the international scientific community. Public health experts, environmental governances, and industry experts are working to improve the overall health, comfort, and well-being of building occupants. Repeated exposure to pollutants in indoor environments is reported as one of the potential causes of several chronic health problems such as lung cancer, cardiovascular disease, and respiratory infections. Moreover, smart cities projects are promoting the use of real-time monitoring systems to detect unfavorable scenarios for enhanced living environments. The main objective of this work is to present a systematic review of the current state of the art on indoor air quality monitoring systems based on the Internet of Things. The document highlights design aspects for monitoring systems, including sensor types, microcontrollers, architecture, and connectivity along with implementation issues of the studies published in the previous five years (2015–2020). The main contribution of this paper is to present the synthesis of existing research, knowledge gaps, associated challenges, and future recommendations. The results show that 70%, 65%, and 27.5% of studies focused on monitoring thermal comfort parameters, CO2, and PM levels, respectively. Additionally, there are 37.5% and 35% of systems based on Arduino and Raspberry Pi controllers. Only 22.5% of studies followed the calibration approach before system implementation, and 72.5% of systems claim energy efficiency.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review

Saini

Dutta

Marques

2020

IJERPH

129

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“…A randomization coefficient based on a normal distribution ranging from 50% to 100% has been introduced to simulate the random presence or absence of students during classes, to obtain a realistic occupancy profile. The same analysis can be based on real time dynamic monitoring of the building occupancy, as considered in some recent studies, using Internet of Things (IoT) prototypes, as [15,42] or with smart and low-cost sensing control, [43,44]. After the pandemic crisis of COVID-19, several papers, as [41], provided useful sug gestions and guidelines for educational buildings, to make classrooms safe and sustaina ble indoor places.…”

Section: Case Studies For Testing the Methodsmentioning

confidence: 99%

HVAC Energy Saving Strategies for Public Buildings Based on Heat Pumps and Demand Controlled Ventilation

2021

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The paper analyzes and compares the perspectives for reducing the energy consumption associated to the operation of Heating Ventilation and Air Conditioning system for climatic control of large-size non-residential buildings. Three different control strategies are considered comparing the use of boiler and heat pumps as heating systems and analyzing the use of demand-controlled ventilation, operating on the effective occupancy of the building. The control strategies are applied to two different educational buildings with shapes representative of typical educational structures. The results of the analysis show how the energy consumption can be reduced up to 70%, shifting from the actual values of the energy intensity of over 300 kWh/m2 for year to values of less than 100 kWh/m2 per year. The significance of the energy savings achieved in such different buildings has led to the identification of a possible benchmark for HVAC systems in the next future years which could help reach the environmental targets in this sector.

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“…Transfer to the advanced control of HVAC systems can be a relatively cheap and easy way to increase the overall energy efficiency in buildings (especially considering that HVAC systems make up over 30% of the total energy use in buildings [2]). There are strategies for increasing the energy efficiency in buildings that use alternative concepts: Papers [3][4][5] relied on occupancy-based demand controls, while paper [6] used occupant feedback (voting) to find optimal setpoints for HVAC control systems.…”

Section: Introductionmentioning

confidence: 99%

Detailed Thermodynamic Modeling of Multi-Zone Buildings with Resistive-Capacitive Method

Belić¹,

Slišković

Hocenski

2021

Energies

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Increased use of energy in buildings and HVAC systems requires advanced control schemes like model-based control to improve energy efficiency, which in turn requires accurate thermodynamic models of buildings. The Resistive-Capacitive (RC) method is a popular and versatile approach for thermal modeling of buildings. Despite this, it is not easy to find practical solutions of implementation of the RC method. It is the goal of this paper to clarify the RC method and demonstrate simple implementation of this method, especially for multi-zone buildings, which have more potential for energy savings from use of model-based control. This paper provides two contributions. First is a detailed explanation of the RC method, focusing on its use for developing a structure of a model and first-principles approach for estimation of parameters of a model. Second is a demonstration of an algorithm that enables automatic development of the structure of a model from basic information about a building (layout, construction elements) and its combination with data-based parameter estimation. Use of the algorithm is presented with a case-study on industrial multi-zone building, for which such a grey-box model is developed and analyzed. The resulting model is rapidly developed and used in a simulation with the measured data. The outputs of the model are compared with the measured temperatures and they show good fit.

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Energy-saving building system integration with a smart and low-cost sensing/control network for sustainable and healthy living environments: Demonstration case study

Cited by 33 publications

References 17 publications

Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review

Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review

HVAC Energy Saving Strategies for Public Buildings Based on Heat Pumps and Demand Controlled Ventilation

Detailed Thermodynamic Modeling of Multi-Zone Buildings with Resistive-Capacitive Method

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