Progetto SIMEA - Automatica - Università degli Studi di Padova

More documents

Recommendations

Info

SIMEA Stato dell’arte energetica degli edifici 1.2.22. ENER-WIN 44 Doc.No 20100610.SIMEA.MR.03 Versione 1 Ener-Win, originally developed at Texas A&M University, is an hourly energy simulation model for assessing annual energy consumption in buildings. The software produces annual and monthly energy consumption, peak demand charges, peak heating and cooling loads, solar heating fraction through glazing, daylighting contribution, and a life-cycle cost analysis. Design data, tabulated by zones, also show duct sizes and electric power requirements. The Ener-Win software is composed of several modules - an interface module, a weather data retrieval module, a sketching module, and an energy simulation module. Ener-Win requires only three basic inputs: • the building type, • the building's location, • the building's geometrical data. Default data derived from the initial inputs include economics parameters, number of occupied days and holidays, occupancy, hot water usage, lighting power densities, HVAC system types and schedules for hourly temperature settings, lighting use, ventilation and occupancy. Weather data generation is done hour-by-hour (Degelman 1990) based on statistical monthly means and standard deviations derived from the World Meteorological Organization and the National Solar Radiation Data Base from a 30-year period of record. The database currently contains 1280 cities. As an alternative, the user may elect to enter typical weather data from files such as TMY2 or WYEC2. The sketching interface allows the user to sketch the building's geometry and HVAC zones, floor- byfloor, and specify parameters such as number of repetitive floors, floor-to-floor heights, and building orientation. The user can specify up to 25 zones on each floor or a building total of 98 zones. Zones are simply represented in plan by different colours. After the sketching process is complete, a drawing processor will analyze the geometrical conditions, including zone floor, roof and wall areas and how the walls are shaded by adjoining and outside structures. Peak values for occupancy, hot water use, ventilation, lighting, and equipment are also specified and linked to their respective schedule numbers. Adjustments of any of the zone properties can be done by editing the zone description forms. Usually, some adjustments are desirable for occupancy numbers, lighting levels, whether daylighting is to be used and whether natural ventilation is to be specified. The default HVAC efficiencies may also be edited. Load calculations, system simulations, and energy summations are performed each hour of the year (Degelman 1990). The resulting zone air conditioning loads are based on a thermal balance model. Convective gains are translated into loads immediately, while the radiative gains are delayed by weighting factors for each source of heat. Daylighting algorithms are based on a modified Daylight Factor method and support dimmer controls. The program also has the capability of simulating the floating space temperature (passive designs) for comfort analyses in unheated or uncooled spaces. Output from Ener-Win is produced in both tabular and graphic forms. The tabular results include: breakdown of monthly energy loads and utility bills, energy savings from utilizing daylight, peak loads, electric demand charges, 24-hour energy use, temperature, energy and comfort profiles. The Life-Cycle Cost prediction is the final step in the program procedures. First costs for the building are based on the unit costs of walls, windows, and roofs from the assemblies catalogue. Additional first costs include the lighting system and the mechanical system. A "Present Worth" analysis is
SIMEA Stato dell’arte energetica degli edifici 45 Doc.No 20100610.SIMEA.MR.03 Versione 1 then performed on the future recurring costs of fuel, electric, and maintenance. These calculations are based on fuel price escalation rates and opportunity interest rates. 1.2.22.1. Validation/Testing Soebarto, Veronica I. 1997, Calibration of hourly energy simulations using hourly monitored data and monthly utility records for two case study buildings, Proc. Building Simulation 97, Vol. II, Intil. Bldg. Perf. Simulation Assin (IBPSA) Conf. held in Prague, the Czech Republic, pp 411-419, 8-10 Sept 1997 1.2.22.2. Expertise Required Experience with Windows applications. Knowledge of building thermal properties and energy concepts. 1.2.22.3. Users Estimated to be in the low hundreds at schools of architecture in Greece, Mexico, Thailand, and the U.S., as well as several dozen practitioners in the U.S., Canada, Kuwait, Mexico and Europe. 1.2.22.4. Audience Architects, engineers, energy analysts, building inspectors, and students of architecture and engineering. 1.2.22.5. Input Graphic entry of building plans through a sketch interface, building envelope thermal properties, hourly use profiles, hourly indoor temperature settings. 1.2.22.6. Output Tabular reports and graphs available for monthly loads, annual loads and energy, peak loads, electric displacement by daylighting, life-cycle costs, and weather summaries. 1.2.22.7. Computer Platform PC-compatible, MS Windows (All versions), 64 Mbytes RAM, 30 Mbytes of available hard drive. Screen resolution 1024x768 minimum. 1.2.22.8. Programming Language Visual Basic and FORTRAN. 1.2.22.9. Strengths Graphic sketch input interface, hourly weather data generator with 1500-city worldwide database. Can run in compacted weather data mode for quick testing of alternative design strategies. Generous use of defaults for materials, windows, profiles, costs, lights, etc. 1.2.22.10. Weaknesses Uses simplified system simulation algorithms. Nine HVAC systems available. Not recommended for testing differences in HVAC systems.
Page 1 and 2: Progetto SIMEA: Sistema Integrato/d
Page 3 and 4: SIMEA Stato dell’arte energetica
Page 43: SIMEA Stato dell’arte energetica
Page 95 and 96:
SIMEA Stato dell’arte energetica
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
Page 109 and 110:
Page 111 and 112:
Page 113 and 114:
Page 115 and 116:
Page 117 and 118:
Page 119 and 120:
Page 121 and 122:
Page 123 and 124:
Page 125 and 126:
Page 127 and 128:
Page 129 and 130:
Page 131 and 132:
Page 133 and 134:
Page 135 and 136:
Page 137 and 138:
Page 139 and 140:
Page 141 and 142:
Page 143 and 144:
Page 145 and 146:
Page 147 and 148:
Page 149 and 150:
Page 151 and 152:
Page 153 and 154:
Page 155 and 156:
Page 157 and 158:
Page 159 and 160:
Page 161 and 162:
Page 163 and 164:
Page 165 and 166:
Page 167 and 168:
Page 169 and 170:
Page 171 and 172:
Page 173 and 174:
Page 175 and 176:
Page 177 and 178:
Page 179 and 180:
Page 181 and 182:
Page 183 and 184:
Page 185 and 186:
Page 187 and 188:
Page 189 and 190:
Page 191 and 192:
Page 193 and 194:
Page 195 and 196:
Page 197 and 198:
Page 199 and 200:
Page 201 and 202:
Page 203 and 204:
Page 205 and 206:
Page 207 and 208:
Page 209 and 210:
Page 211 and 212:
Page 213 and 214:
Page 215 and 216:
Page 217 and 218:
Page 219 and 220:
Page 221 and 222:
Page 223 and 224:
Page 225 and 226:
Page 227 and 228:
Page 229 and 230:
show all

Progetto SIMEA - Automatica - Università degli Studi di Padova

Create successful ePaper yourself

Delete template?

Save as template?