학위논문 (석사)-- 서울대학교 대학원 : 생태조경.지역시스템공학부(지역시스템공학전공), 2012. 8. 이인복.At this situation that ever-soaring oil price and increasing the size and area of controlled horticulture, calculation of appropriate size of facilities for heating and cooling system is a task which should be preceded necessarily from an aspect of reasonable farm design, management and energy saving. This study is a basic study which applies BES technique to greenhouses in agricultural field, the contents of analyzing the heating and cooling characteristics of greenhouse were dealt. First, the design method of greenhouse model was sought using TRNSYS that is one of BES programs and the verification of that was conducted. And, based on verified greenhouses, it modeled widespan-type and venlo-type greenhouse which are typically used in the domestic and aimed to compare and analyze characteristics of energy loads by applying weather data for 1 year in 2010 in 6 regions. With this, it aimed to realize geothermal energy system which is being recognized as an alternative energy source in controlled horticulture industry using BES and performed its analysis. As a result of comparison with greenhouse design model using TRNSYS and field experiment data, the vertical model that divides the zone to vertical direction along multi-span of greenhouse showed good agreement both qualitatively and quantitatively. All of the verification was 5.2 and 5.5 %, respectively. As the results of performing the load calculation of widespan-type and venlo-type greenhouse that is the representative domestic greenhouse and 6 domestic regions using BES simulation, seasonal heating load was higher from Chuncheon, high latitude to Jeju a low latitude about 11∼49 %. On the contrary, the seasonal cooling load showed lower as it goes from low latitudes to high latitudes. Among them, the case of Daegu where has the topographical characteristic of basin-shape calculated the highest load, and the low loads of about 6, 12, 19 and 22 % each showed in sequential order of Jeonju, Cheongju, Suwon and Chuncheon based on Daegu. And, regarding the load difference between two greenhouses for each region, venlo-type greenhouse whose volume is relatively large was computed as higher by about 3∼8 % in case heating and about 5∼6 % in case cooling than widespan-type. Maximum heating and cooling load appeared similar to the tendency of seasonal load and maximum cooling load appeared at the different time in the simulation in case of maximum cooling load not like actual highest temperature. As the results of comparing between dynamic analysis method and static analysis method, both widespan-type and venlo-type were computed as low by about 30∼36 % and 27∼33 % in dynamic analysis method and they were computed as low by about 44∼49 % and 43∼47 % in dynamic analysis method as well, and it could be guessed that the facilities were overestimated through load estimation of greenhouse so far. Geothermal energy system of greenhouse was simulated using BES. The simulation result was validated through the comparison with the installation capacity of geothermal energy system of Top-green greenhouse. Based on the criteria to install the geothermal system (70 % of the maximum heating loads), it generates about 5 % of errors. Also, when the quantity of heat generated for 1 hour by the geothermal energy system through simulation with the installation capacity of the geothermal energy system in the target greenhouse, it generates about 6 % of errors.
In this study, it was recognized that it can be applied to greenhouse that is the agricultural facility by using BES simulation and the more accurate energy consumption of interior greenhouse could be grasped efficiently through the comparison with existing energy analysis method. And, as the example of applying and simulating geothermal energy system to greenhouse by using BES, it is expected that more accurate and predictable simulation method can be applied to greenhouse by simulating various new renewable energies and facility system as well as geothermal energy. It is considered that the reliability of BES method can be risen through the further studies that seek the energy load characteristic of actual greenhouse such as ventilation, warm curtain and crops and can used as the important technology for the calculation of energy load for building up the optimal environment of heating and cooling facilities of greenhouse.ABSTRACT ⅰ
CONTENTS ⅳ
LIST OF TABLES ⅶ
LIST OF TABLES ⅸ
Ⅰ. INTRODUCTION 1
Ⅱ. LITERATURE REVIEW 5
2.1. METHOD FOR CALCULATING THE ENERGY CONSUMPTION IN A BUILDING 5
2.2. METHOD FOR CALCULATING THE ENERGY CONSUMPTION IN A GREENHOUSE 7
Ⅲ. MATERIALS AND METHODS 10
3.1. BUILDING ENERGY SIMULATION 10
3.1.1. SIMULATION ANALYSIS METHOD 15
3.2. TARGET FACILITY AND REGION 17
3.2.1. GREENHOUSE 1: GREENHOUSE FOR VERIFICATION 17
3.2.2. GREENHOUSE 2: TYPICAL DOMESTIC GREENHOUSE 18
3.2.3. GREENHOUSE 3: GREENHOUSE USING GEOTHERMAL ENERGY 20
3.3. RESEARCH METHODS 22
3.3.1. MODELING AND VERIFYING THE GREENHOUSE USING BES 23
3.3.1.1. FIELD EXPERIMENT 23
3.3.1.2. GREENHOUSE MODELING 26
3.3.2. CALCULATION AND PREDICTION OF LOAD BY EACH REGION AND EACH TYPE OF GREENHOUSE IN THE DOMESTIC 28
3.3.2.1. COMPARISON OF BES AND STATIC ANALYSIS SIMULATION 28
3.3.2.1.1. GES PROGRAM FOR STATIC LOAD ANALYSIS 29
3.3.3. MODELING OF GEOTHERMAL ENERGY SYSTEM IN GREENHOUSE 30
3.3.3.1. DATA COLLECTION FROM GEOTHERMAL GREENHOUSE 31
3.3.3.2. GEOTHERMAL SYSTEM MODELING 32
Ⅳ. RESULTS AND DISCUSSION 33
4.1. MODELING AND VERIFYING THE GREENHOUSE USING BES 33
4.1.1. FIELD EXPERIMENT 33
4.1.2. GREENHOUSE MODELING 35
4.1.3. DYNAMIC SYSTEM MODELING USING BES 37
4.1.4. VERIFICATION OF BES MODEL 39
4.2. CALCULATION AND PREDICTION OF LOAD BY EACH REGION AND THE DOMESTIC GREENHOUSES 44
4.2.1. METEOROLOGICAL ANALYSIS 45
4.2.2. BES MODELING 47
4.2.3. LOAD CALCULATION BY EACH REGION AND EACH TYPE OF GREENHOUSE 48
4.2.3.1. SEASONAL HEATING LOAD 48
4.2.3.2. SEASONAL COOLING LOAD 50
4.2.3.3. MAXIMUM HEATING AND COOLING LOAD 52
4.2.4. COMPARISON OF DYNAMIC ANALYSIS METHOD AND STATIC ANALYSIS METHOD 56
4.2.4.1. MAXIMUM HEATING LOAD 56
4.2.4.2. SEASONAL HEATING LOAD 59
4.3. MODELING OF GEOTHERMAL ENERGY SYSTEM IN GREENHOUSE 62
4.3.1. DATA COLLECTION FROM GEOTHERMAL GREENHOUSE 63
4.3.2. GEOTHERMAL SYSTEM MODELING 66
4.3.3. APPLYING AND ANALYZING FOR GEOTHERMAL SYSTEM MODEL 72
Ⅴ. CONCLUSION 78
REFERENCE 82
국문초록 90Maste