• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.8 no.1
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• pp.76-87
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• 1996

Energy analysis for the hot water heating control system of apartment house complex is accomplished by computer simulation. Mathematical model of a boiler, pipe network and a unit-house is developed. The effects of heating control methods on the heating performance and energy consumption of the system are investigated. The heating control methods considered in this study are a continuous heating control, and on-off heating control and an intermittent heating control methods. For each control method, the effects of an outdoor temperature, indoor temperature sensing position and the capacities of the boilers and circulating pumps on the heating performance and energy consumption are obtained and "the best" control method is recommended.commended.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.12
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• pp.830-836
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• 2012

In this study, the effects of heating control methods on heating control performance and energy consumption in the floor radiant heating control system of residential apartments were research by computer simulation. A general regression neural network(GRNN) control method for reducing indoor temperature overshoot and saving energy in floor radiant heating system is suggested. The GRNN control method shows good responses in comparison with the conventional and outdoor reset control methods for improving indoor thermal environment and reducing energy consumption.

• Journal of Ship and Ocean Technology
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• v.6 no.4
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• pp.1-12
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• 2002

A control system for an automated line heating process is developed by use of object-oriented methodology. The main function of the control system is to provide real-time heating information to technicians or automated machines. The information includes heating location, torch speed, heating order, and others. The system development is achieved by following the five steps in the object-oriented procedure. First, requirements are specified and corresponding objects are determined. Then, the analysis, design, and implementation of the proposed system are sequentially carried out. The system consists of six subsystems, or modules. These are (1) the inference module with an artificial neural network algorithm, (2) the analysis module with the Finite Element Method and kinematics analysis, (3) the data access module to store and retrieve the forming information, (4) the communication module, (5) the display module, and (6) the measurement module. The system is useful, irrespective of the heating sources, i.e. flame/gas, laser, or high frequency induction heating. A newly developed automated line heating machine is connected to the proposed system. Experiments and discussions follow.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.7 no.1
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• pp.38-44
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• 2011

In this study, heating performance and energy consumption characteristics with control strategies for central heating system were researched by the simulation. The simulation analysis is made by TRNSYS ver. 15 with the actual data. The parametric study on proportional factor, control time interval and outdoor air temperatures changes were done to compare control characteristics and energy performance, respectively. As a result, the simulation results with various parameter changes show good heating performance and energy saving.

• International Journal of Air-Conditioning and Refrigeration
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• v.6
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• pp.136-147
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• 1998

An experimental facility consisting of two 3$\times$4.4$\times$2.8m rooms identical in construction is built. Each room has a control system and storage tank supplying hot water to the radiant floor heating system. The facility enables simultaneous comparison of two different control strategies each implemented in a separate room. The operating performance of three kinds of flow control scheme is tested and compared in this study: (ⅰ) conventional on-off control based on feedback from room air temperature (ⅱ) TPSC(two parameter switching control )(ⅲ) TPOC(two parameter on-off control). Results show that TPSC and TPOC using room air and surface temperature sequentially as feedback signal to control hot water supply is the better temperature regulation scheme than conventional control based on feedback from only room air temperature. They are good candidates for the room with radiant floor heating system under continuous and intermittent heating mode.

• Proceedings of the SAREK Conference
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• 2005.11a
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• pp.463-468
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• 2005

An experimental study on the optimal control algorithm for central heating system for minimizing energy consumption while maintaining the comfort of indoor thermal en vironment in terms of the environmental variables such as loads and weather. experimental study has been done by one using the prototype of central heating system. As a result the optimal control algorithm shows good energy performance in comparison with conventional control one.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.7 no.1
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• pp.32-37
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• 2011

In this study, control characteristics and energy performance with flow rate control methods were reviewed with the simulation. The heating system is classified such as fan coil unit and HVAC system currently used in buildings with valve control and pump inverter control. The simulation analysis program is made by TRNSYS ver. 15 with the actual data. As a result of this study, the central heating system with pump inverter control decreases electricity energy and reduces gas consumption. Inverter control method shows better performance in comparison with valve control one for energy saving.

• 한국태양에너지학회:학술대회논문집
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• 2009.04a
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• pp.109-114
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• 2009

The dominant heating system used in Korean residential apartment buildings is a hydronic radiant floor heating system, known as the Ondol system. The most common control strategy applied to this traditional hydronic radiant system is a simple on-off control that intermittently supplies "hot water of a fixed temperature" at a "constant flow rate" to each room. However, the current problems with the aforementioned control are as follows: (1) since the simple on-off control is usually based on a one point measured temperature (a signal from a thermostat installed in a living room) in each dwelling unit, heating energy use for unoccupied rooms as well as a difference in temperatures between spaces (master bedroom, living room, bedroom1, bedroom2) can occur occasionally. (2) the most widely used residential water splitter has static valves, and is thus not able to change the flow rate to each room depending on the space heating load. In other words, the ratio of flow rates to rooms is fixed after construction, resulting in over- or under-heating and an improper use of energy. The aim of this paper is therefore to investigate the differences in the system's performance between control strategies in terms of the flow rate control and sensor location. It is shown that energy savings of control strategies are strongly influenced by occupant schedule.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.1209-1214
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• 2009

Various automatic temperature control systems have been used widely in Korea for the conservation of heating energy and the enhancement of thermal comfort in residential buildings. But the heating control performance for automatic temperature control systems extensively vary with the design and operational conditions of the heating system, the climate condition and others. It was introduced in this study a numerical calculation program package to analyze heating control characteristics of the automatic temperature control system. This package is able to analyze the room air temperature, return water temperature, supplied heating flux and flow rate, and so on. One the other hand, the simulation results were verified by comparing with the field test results.

• Land and Housing Review
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• v.10 no.3
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• pp.9-16
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• 2019

This study aimed at developing control algorithms for operating a variable refrigerant flow (VRF) heating and cooling system with optimal system parameter set-points. Two artificial neural network (ANN) models, which were respectively designed to predict the heating energy cost and cooling energy amount for upcoming next control cycle, was developed and embedded into the control algorithms. Performance of the algorithms were tested using the computer simulation programs - EnergyPlus, BCVTB, MATLAB in an incorporative manner. The results revealed that the proposed control algorithms remarkably saved the heating energy cost by as much as 7.93% and cooling energy consumption by as much as 28.44%, compared to a conventional control strategy. These findings support that the ANN-based predictive control algorithms showed potential for cost- and energy-effectiveness of VRF heating and cooling systems.