• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.11
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• pp.982-993
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• 2000

This paper describes an optimal control scheduling of an encapsulated ice storage system with a chiller of nominal chiller 34RT(103,200kcal/hr) and an ice storage tank of 170RT-hrs(514,080 kcal). The optimization technique used in the study is dynamic programing. The objective function is summed cost during a day including charge and discharge periods. Control strategies being used commercially are chiller priority and storage priority control. In chiller priority control, the chiller is allowed to run at full capacity during the day, subject to limitations of the building load, and the ice is only melted when and if the load exceeds the chillers full capacity. In contrast to chiller priority control, the aim in storage priority control is to melt as much as ice as possible during the day time period. The system simulation calculates the operation costs for the three control strategies in the condition of the same cooling load and the same ice storage system. The simulation period is a day, assuming that initially the tank is stored fully and the cooling load is perfectly predicted for the scheduling. Also Final state of the tank is to be charged fully.

• KIEAE Journal
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• v.17 no.5
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• pp.69-76
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• 2017

Purpose: This study aimed at developing an Artificial Neural Network (ANN) model for predicting the amount of cooling energy consumption of the variable refrigerant flow (VRF) cooling system by the different set-points of the control variables, such as supply air temperature of air handling unit (AHU), condenser fluid temperature, condenser fluid pressure, and refrigerant evaporation temperature. Applying the predicted results for the different set-points, the control algorithm, which embedded the ANN model, will determine the most energy efficient control strategy. Method: The ANN model was developed and tested its prediction accuracy by using matrix laboratory (MATLAB) and its neural network toolbox. The field data sets were collected for the model training and performance evaluation. For completing the prediction model, three major steps were conducted - i) initial model development including input variable selection, ii) model optimization, and iii) performance evaluation. Result: Eight meaningful input variables were selected in the initial model development such as outdoor temperature, outdoor humidity, indoor temperature, cooling load of the previous cycle, supply air temperature of AHU, condenser fluid temperature, condenser fluid pressure, and refrigerant evaporation temperature. The initial model was optimized to have 2 hidden layers with 15 hidden neurons each, 0.3 learning rate, and 0.3 momentum. The optimized model proved its prediction accuracy with stable prediction results.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.1
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• pp.15-20
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• 2017

The summer climate is very hot and humid in Korea. The humidity is an important factor in determining thermal comfort. Recently, the research for dehumidification device development has been attempted to save energy that is required for the operation of the current dehumidifiers on the market. Existing dehumidification systems have disadvantages such as wasting energy to drive a compressor. Meanwhile, dehumidification systems with membranes can dehumidify humid air without increasing the dry bulb temperature so it doesn't have to consume cooling energy. In this paper, the cooling energy savings was studied when a dehumidification system was applied in a model building instead of a chiller. The sensible heat load was almost the same result, but the latent heat load was decreased by 38.9% and the total heat load was decreased by 8.5%. As a result, electric energy used to drive the compressor in a chiller was saved by applying a membrane air-conditioning system instead.

• Environmental and Resource Economics Review
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• v.16 no.4
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• pp.803-832
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• 2007

Electricity and heat load profiles by use types on an hourly basis at the least are essential for assessing economic viability of new cogeneration and CES projects and for optimally operating existing cogeneration and CES facilities. We adopt a multilevel model to specify heat load profiles so as to utilize in a flexible manner the panel nature of our data on weather and heating/cooling use. Converting the multilevel model to the linear mixed-effects model, we estimate the model by panel FGLS. The estimated load profile model for each distinct use type accounts for the effects of temperature, humidity, each hour over the year, each day of the week, each type of legal holidays, and heating/cooling area on energy use. To save space, we feature in detail the heating profile of the household.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.12
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• pp.1730-1738
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• 2001

This paper presents an overview of testing and analyzing field performance of a centrifugal chiller which has a rated capacity of 200 RT(703 kW). Field data of a chiller installed in the cleanroom research building of KIST has been collected far performance analysis. The operating data included start-up, shut-down, and quasi-static state where cooling capacity and compressor power consumption varied cyclically. It was found that the steady-state thermodynamic model could be applied to relate the cooling capacity and COP under quasi-static conditions. The results led to finding the required cooling load pattern and a possible energy saving method. This study provides a method of evaluating performance of a large capacity centrifugal chiller in which field test is necessary.

• Journal of Bio-Environment Control
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• v.32 no.3
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• pp.181-189
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• 2023

Hydrogen has gained attention as an environmentally friendly energy source among various renewable options, however, its application in agriculture remains limited. This study aims to apply the hydrogen fuel cell triple heat-combining system, originally not designed for greenhouses, to greenhouses in order to save energy and reduce greenhouse gas emissions. This system can produce heating, cooling, and electricity from hydrogen while recovering waste heat. To implement a hydrogen fuel cell triple heat-combining system in a greenhouse, it is crucial to evaluate the greenhouse's heating and cooling load. Accurate analysis of these loads requires considering factors such as greenhouse configuration, existing heating and cooling systems, and specific crop types being cultivated. Consequently, this study aimed to estimate the cooling and heating load using building energy simulation (BES). This study collected and analyzed meteorological data from 2012 to 2021 for semi-enclosed greenhouses cultivating tomatoes in Jeonju City. The covering material and framework were modeled based on the greenhouse design, and crop energy and soil energy were taken into account. To verify the effectiveness of the building energy simulation, we conducted analyses with and without crops, as well as static and dynamic energy analyses. Furthermore, we calculated the average maximum heating capacity of 449,578 kJ·h^-1 and the average cooling capacity of 431,187 kJ·h^-1 from the monthly maximum cooling and heating load analyses.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.1920-1925
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• 2007

A transformer is a device that changes the current and voltage by electricity induced between coil and core steel, and it is composed of metals and insulating materials. In the core of the transformer, the thermal load is generated by electric loss and the high temperature can make the break of insulating. So we must cool down the temperature of transformer by external radiators. According to cooling fan's usage, there are two cooling types, OA(Oil Natural Air Natural) and FA(Oil Natural Air Forced). For this study, we used Fluent 6.2 and analyzed the cooling characteristic of radiator. we calculated 1-fin of detail modeling that is similar to honeycomb structure and multi-fin(18-fin) calculation for OA and FA types. For the sensitivity study, we have different positions(side, under) of cooling fans for forced convection of FA type. The calculation results were compared with the measurement data which obtained from 135.45/69kV ultra transformer flowrate and temperature test. The aim of the study is to assess the Fluent code prediction on the radiator calculation and to use the data for optimizing transformer radiator design.

• Structural Engineering and Mechanics
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• v.66 no.2
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• pp.273-283
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• 2018

Currently, the dynamic amplification effect of suction is described using the wind vibration coefficient (WVC) of external loads. In other words, it is proposed that the fluctuating characteristics of suction are equivalent to external loads. This is, however, not generally valid. Meanwhile, the effects of the ventilation rate of louver on suction and its WV are considered. To systematically analyze the effects of the ventilation rate of louver on the multi-dimensional WVC of ultra-large cooling towers under suctions, the 210 m ultra-large cooling tower under construction was studied. First, simultaneous rigid pressure measurement wind tunnel tests were executed to obtain the time history of fluctuating wind loads on the external surface and the internal surface of the cooling tower at different ventilation rates (0%, 15%, 30%, and 100%). Based on that, the average values and distributions of fluctuating wind pressures on external and internal surfaces were obtained and compared with each other; a tower/pillar/circular foundation integrated simulation model was developed using the finite element method and complete transient time domain dynamics of external loads and four different suctions of this cooling tower were calculated. Moreover, 1D, 2D, and 3D distributions of WVCs under external loads and suctions at different ventilation rates were obtained and compared with each other. The WVCs of the cooling tower corresponding to four typical response targets (i.e., radial displacement, meridional force, Von Mises stress, and circumferential bending moment) were discussed. Value determination and 2D evaluation of the WVCs of external loads and suctions of this large cooling tower at different ventilation rates were proposed. This study provides references to precise prediction and value determination of WVC of ultra-large cooling towers.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.3
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• pp.123-130
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• 2024

This paper proposes an EMPC (Explicit Model Predictive Controller) for temperature tracking control based on heat load prediction by an ESO (Extended State Observer) for a variable cooling circulation system with multiple indoor units connected to one outdoor unit. In this system, heat transfer and heat loss relative to the input temperature are modeled using system dynamics. Using this model, we design an EMPC based on an ESO that is robust to temperature changes and depends on airflow. To determine the stability of both the controller and the observer, asymptotic stability is verified through Lyapunov stability analysis. Finally, to validate the performance of the proposed controller, simulations are conducted under three scenarios with varying airflow, set temperature, and heat load.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.11 no.1
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• pp.133-146
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• 1999

The charge operation of an ice storage system has been analyzed in this paper. The thermal characteristics of major components of the ice storage system. i.e., the refrigerator and the ice storage tank are evaluated from performance tests on an existing ice storage system. Based on the measured data for thermal characteristics, a simulation is carried out for the charge operation and the effect of the refrigerator size on the system performance is investigated. The results indicate that the larger the refrigerator size for a given storage capacity, the lower the inlet temperature of the ice storage tank so that the lower the efficiency of charge operation. It is also found that there exists an optimal size of the refrigerator with which the ice storage at the end of the charge operation is maximized, but the complete charge is not possible even with the optimally sized refrigerator. This leads to the result that the design capacity of the storage tank should be larger than the required amount of cold energy for the daytime cooling considering the practically chargeable amount of cold energy during the nighttime. Where the cooling load sharing of the storage is 40%, the nominal capacity of an ice storage tank needs to be larger than the required storage amount by 30%.