Comparative Analysis of Energy Use and Human Comfort by an Intelligent Control Model at the Change of Season

Yoon, Sung Hoon; Ahn, Jonghoon

doi:10.3390/en13226023

Cited by 6 publications

(5 citation statements)

References 30 publications

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“…ANNs are employed to take into ac count the weather sensitivity, revising the preliminary forecasts from the clustering stage S.H. Yoon et al [34] proposed a learning control for an adaptive networked-based control ler for investigating the control performance of air-supply conditions to maintain the in door thermal comfort level. In the process, a thermal supply model was employed, which Figure 9, energy consumption has consistently been a topic of significance in the operation and maintenance of buildings.…”

Section: Basic Technology Developmentmentioning

confidence: 99%

Section: Basic Technology Developmentmentioning

confidence: 99%

“…S.H. Yoon et al [34] proposed a learning control for an adaptive networked-based controller for investigating the control performance of air-supply conditions to maintain the indoor thermal comfort level. In the process, a thermal supply model was employed, which combined with the geometric shape of the building, the outside temperature, and the characteristics of the occupants, to calculate the air supply conditions for either heating or cooling based on the air volume and temperature.…”

Section: Basic Technology Developmentmentioning

confidence: 99%

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A Review of Theory and Application Development of Intelligent Operation Methods for Large Public Buildings

Jiao

Liu

et al. 2023

Sustainability

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This article aims to systematically summarize the methods for intelligent operation of large public buildings, the integration and application of related technologies, as well as their development trends and challenges. (1) Background: In response to the rapid development and future needs of intelligent operation and maintenance, this study summarizes the development process of intelligent operation and maintenance in building operations, as well as relevant technical achievements and challenges; (2) Method: Quantitative and qualitative bibliometric statistical methods were used for overall analysis; (3) Result: Based on system theory, a B-IRO model was developed, and the current status of intelligent operation- and maintenance-related technologies and applications was sorted out. A framework for the entire industry was established, and future development trends were proposed as further research directions.

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Section: Basic Technology Developmentmentioning

confidence: 99%

Section: Basic Technology Developmentmentioning

confidence: 99%

Section: Basic Technology Developmentmentioning

confidence: 99%

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A Review of Theory and Application Development of Intelligent Operation Methods for Large Public Buildings

Jiao

Liu

et al. 2023

Sustainability

View full text Add to dashboard Cite

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“…The FIS and the ANN algorithms have been adopted in the PMV models to supplement inner interactions between simulation configurations and operational processes. For the improvement of the conventional control rules, numerical changes in occupant conditions by design assumptions such as types of works and clothes were utilized to analyze specific thermal situations associated with mechanical supply systems for cooling and heating air [18,19]. Additionally, data-driven genetic algorithms were used to improve specific regression models in the FIS model for making structure realistic, and, by means of instantly connecting user responses, adaptive structure in the ANN was utilized to improve their statistical significance of learning algorithms.…”

Section: Introductionmentioning

confidence: 99%

Building Space Thermal Control Model Responding to Sharp Changes in Outdoor Temperature

2023

Teh. vjesn.

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As computing and data-driven technologies have improved, the precision of the building thermal control models has been gradually improved, but the use of energy resources to operate them has been also increased. It is imperative to investigate the optimized point of energy use and human comfort for their thermal control strategies. The aim of this research is to find an energy-efficient thermal control model to maintain the constancy of thermal comfort and suppress the increase of energy use in association with precise environmental controls. Based on a cooling and heating air supply model in a simplified building model, a comprehensive energy use pattern is confirmed by adding an adaptive control model that allows indoor thermal comfort to be maintained at a setting level. The adaptive control model utilizing the artificial neural network and the adjustment process of initial settings is proposed to examine its performance in controlling the amount of thermal supply air and its temperature. For the clear comparison between a baseline model and a proposed model, the statistical indices of each thermal dissatisfaction value and the weekly heating energy use are utilized. The results of this research show that the thermal dissatisfaction fluctuation is alleviated by about 22.0~41.0% and the energy efficiency is improved by about 5.1%, respectively. The results provide the effectiveness of the proposed model which can improve both the energy use and thermal comfort in a building space. This advantage can help old thermal systems to improve their usability without replacing any major components.

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“…On the other hand, several types of theory-based, experiment-based, survey-based, and simulation-based studies have been examined by means of various types of data derived from categorized characteristics of the occupants in the area of indoor thermal comfort [16][17][18]. In addition to the subjective indices that reflect occupant responses, there has been a need to more objectively analyze subjective indicators that may be difficult to quantify.…”

Section: Introductionmentioning

confidence: 99%

Abatement of the Increases in Cooling Energy Use during a Period of Intense Heat by a Network-Based Adaptive Controller

Ahn

2021

Sustainability

Self Cite

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Various methods to control thermal conditions of building spaces have been developed to investigate their performances of energy use and thermal comfort in the system levels. However, the high control precision used in several studies dealing with data-driven methods may cause energy increases and the high energy efficiency may be disadvantageous for maintaining indoor environmental quality. This study proposes a model that optimizes the supply air condition to effectively reach the setting values by two-way controls of the supply air conditions. In such a process, if the results of the thermal comfort level are outside the range of the initial setting values, an adaptive model starts to work to send additional signals to adjust the set-point temperature. In order to assess its efficiency, the conventional thermostat model and fuzzy deterministic model are adopted as comparators. Comparing the results of the proposed network-based model with conventional control models, an improved control performance from 15.5% to 29.3% in thermal comfort indices was identified, as well as an over 30% improvement in energy efficiency. As a consequence, the network-based adaptive control rule supervising thermal comfort indices properly operates to abate increases in its energy use without compromising its thermal comfort. This performance can be significant in places where many spaces are woven at high density, and in situations where better thermal comfort can increase users’ workability and productivity.

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Comparative Analysis of Energy Use and Human Comfort by an Intelligent Control Model at the Change of Season

Cited by 6 publications

References 30 publications

A Review of Theory and Application Development of Intelligent Operation Methods for Large Public Buildings

A Review of Theory and Application Development of Intelligent Operation Methods for Large Public Buildings

Building Space Thermal Control Model Responding to Sharp Changes in Outdoor Temperature

Abatement of the Increases in Cooling Energy Use during a Period of Intense Heat by a Network-Based Adaptive Controller

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