• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.1
• /
• pp.28-34
• /
• 2007

Recently, with the rapid growth of industry, environmental condition became worse. In addition to outdoor insulators in seashore are polluted due to salty wind. Also this pollution causes the flashover and failure of electric equipments. Especially the salt contaminant is one of the most representative pollutants, and known as the main source of the accident by contamination. As well known, the pollution has a close relation with meteorological factors such as wind velocity, wind direction, temperature, relative humidity, precipitation and so on. In this paper we have statistically analyzed the correlation between the pollution and the meteorological factors. The multiple regression analysis was used for the statistical analysis; daily measured equivalent salt deposit density(dependent variable) and the weather condition data(independent variable) were used. Also we have developed an expert program to predict the pollution deposit. A new prediction system using this program called SPPP(salt pollution prediction program) has been used to model accurately the relationship between ESDD with the meteorological factors.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
• /
• v.8 no.3
• /
• pp.19-28
• /
• 2012

In a heat only boiler system of a steam power plant, outdoor air required for combustion is made to pass through indoor space for increasing the boiler efficiency. Due to heat generated by various equipments, temperature of the air that enters the boiler will increase resulting in combustion efficiency. If the outdoor air temperature is low, however, this will cause freezing and bursting of pipes which are filled with water. It is especially fatal to small diameter pipes and pipes connected to measuring instruments. The purpose of this study is find operation and outdoor conditions where this phenomena can happen and also establish preventive measures to avoid this problem.

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

• Proceedings of the SAREK Conference
• /
• 2009.06a
• /
• pp.1300-1305
• /
• 2009

The energy conservation in buildings affects environmental preservation as well as economic benefits, and creates the comfortable indoor environment set for the inhabitants. Especially, apartment buildings show ever-increasing energy consumption with large-sized and high-class tendency, thus energy saving counterplans are needed. The present study is to develop an optical control algorithm by using heating load curve according to the outdoor temperature change. Heating load analysis should be performed before the present method can be applied. Dynamic heating load simulations are performed by resistance-capacitance method. Results show that heating load decrease linearly according to the increase of outdoor temperature.

• Proceedings of the KIEE Conference
• /
• 2004.05b
• /
• pp.173-175
• /
• 2004

The degree of contamination on outdoor insulators is one of the most importance factor to determine the pollution level of outdoor insulation. Outdoor insulators in coastal are affected due to salty wind blowing from the seaside. The sea salt is known as the most dangerous pollutant. As known through the preceding study, the generation of salt pollutant and the pollution degree of outdoor insulators have a close relation in accordance with meteorological conditions, such as temperature, humidity, dewpoint, wind velocity and wind direction. Therefore, at first, we have analyzed relation between meteorological conditions and contaminants for development of prediction method. In this paper, we have investigated a statistical estimation technique based on actual data for equivalent salt deposit density(ESDD) of outdoor insulators which were installed in Kochang field test substation with multiple linear regression analysis.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.11 no.2
• /
• pp.193-204
• /
• 1999

Performance of a variable-speed, roller-type vane compressor was evaluated at low evaporating temperature. First, an experimental investigation was conducted to examine the performance variation as functions of both outdoor temperature and rotating speed. For this purpose, a typical heat pump was implemented as a test apparatus to measure mass flow rate and power input. Secondly, computational investigations corresponding to the heat pump test conditions were performed to predict compressor performance using ORNL Map-Based compressor model. Results obtained from the heat-pump experiments showed that both mass flow rate and power consumption were sensitively dependent on both evaporating temperature and compressor speed as was predicted from the computational results. From the comparisons of both experimental and computational results, it was well recognized that the ORNL model was subjected to larger error in the accuracy of prediction as outdoor temperature decreased. When the outdoor temperature was above $-5^{\cire}C$, errors of predicted values corresponding to both mass flow rate and power consumption were estimated as $\pm$10% and $\pm$ 15%, respectively. Finally, it is suggested that the ORNL model needs to be re-evaluated if compressor map data tested below $-5^{\cire}C$(in evaporating temperature) are available.

• KIEAE Journal
• /
• v.12 no.3
• /
• pp.27-32
• /
• 2012

In recent years, the quality of the outdoor thermal environment has come to be regarded as important as that of the indoor thermal environment. Since the outdoor thermal environment is composed of many elements and is affected by many factors, it is not easy to evaluate the impact of each factor separately. Hence, a comprehensive assessment method is required. In order to evaluate the pedestrian level comfort of an outdoor climate, it is necessary to investigate not only wind velocity but also various physical elements, such as temperature, moisture, radiation, etc. Prediction of wind and thermal environment for a large scale buildings is one of the most important targets for research. Wind and thermal change in a city area is a very complicated phenomenon affected by many physical processes. The purpose of this study is to develop a design plan for wind environment at a large Buildings. In this study, we analyze outdoor wind environment and thermal environment on buildings using the CFD (Computational Fluid Dynamics) method. The arrangement of building models is an apartment in Jeonju. These prediction of wind and thermal environment for a large scale buildings is necessary in a plan before a building is built.

• Journal of the Korean Solar Energy Society
• /
• v.36 no.2
• /
• pp.65-72
• /
• 2016

PV module is installed in various outdoor conditions such as solar irradiation, ambient temperature, wind speed and etc. Increase in solar cell temperature within PV module aggravates the behaviour and durability of PV module. It is difficult to measure temperature among respective PV module components during PV module operating, because the temperature within PV module depends on thermal characteristics of PV module components materials as well as operating conditions such as irradiation, outdoor temperature, wind etc. In this paper, simulation by using finite element method is conducted to predict the temperature of each components within PV module installed to outdoor circumstance. PV module structure based on conventional crystalline Si module is designed and the measured values of thickness and thermal parameters of component materials are used. The validation of simulation model is confirmed by comparing the calculated results with the measured temperatures data of PV module. The simulation model is also applied to estimate the thermal radiation of PV module by front glass and back sheet.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.15 no.4
• /
• pp.287-293
• /
• 2003

This study examined the temperature-dependent regression model of energy consumption based on various measuring period. The methodology employed was to construct temperature-dependent linear regression model of daily energy consumption from one day to three months data-sets and to compare the annual heating energy consumption predicted by these models with actual annual heating energy consumption. Heating energy consumption from a building in Daejon was examined experimentally. From the results, predicted value based on one day experimental data can have error over 100%. But predicted value based on one week experimental data showed error over 30%. And predicted value based on over three months experimental data provides accurate prediction within 6% but it will be required very expensive.

• Current Photovoltaic Research
• /
• v.5 no.1
• /
• pp.33-37
• /
• 2017

Today, photovoltaic power generation mostly uses Si crystalline solar cell modules. The most vulnerable part of the Si solar cell module is that the power generation decreases due to the temperature rise. But, it is widely used because of low installation cost. In the solar market, where Si crystalline solar cell modules are widely used. The CPV (Concentrated Photovoltaic) module appeared in the solar market. The CPV module reduces the manufacturing cost of the solar cell by using non-Si in the solar cell. Also, there is an advantage that a rise in temperature does not cause a drop in power generation. But this requires high technology to install and has a disadvantage that the initial installation cost is expensive compared to normal Si solar cell module. So that we built a testbed to see these characteristics. The testbed was used to measure the amount of power generation in a long-term outdoor environment and compared with the general Si solar cell module.