| In the conception and technological background of building energy saving, it is one ofthe most important concerns for the researcher in the building energy saving filed in whatmanner of air conditioning to save energy. In the current researches on the refrigerationsystem simulation, small commercial type such as refrigerator, room and vehicle airconditioner, etc., are the common objects. However, simulation on the variable refrigerantvolume (VRV) is rare, and it is not found specially that VRV simulation research combinedwith building energy simulation is carried in the word. A series of theoretical andexperimental research on this subject is included in this dissertation which is described asfollows.(1) Using existing DX model flexibly, build the VRV model through a dummyoutdoor unit, and then find the energy consumption, COP, and PLR. It is convenient forgetting accurate energy results based on simple inputs. The model suitable for the buildingenergy simulation program (BESP) is flexible to be embedded into various BESP platforms.This research solves the problem that VRV annual energy is not able to be investigated forVRV model is not included in prevalent BESP. It is of significance to make VRV yearlyenergy research by BESP.(2) Build the VRV energy consumption test setup, and finish one whole year ofmeasurement to validate the accuracy of VRV energy prediction model in a real buildingapplication. Compared with normal VRV installations, the setup has some notable features:simple and typical with one-serving-two configuration in a real building; internal gains mimicked by heaters and humidifiers in special test spaces; data collection, temperaturesetting, and switching ON/OFF for all of system with affiliated devices, are controlled byPC; one whole year measurement.(3) Based on the simulation and test data for cooling and heating conditions, the VRVenergy model is verified, and it is satisfied to match the simulation and test results. What ismore important is to demonstrate the simulation error of power follows that of capacity. Itmeans the accuracy of VRV model tracks that of EnergyPlus simulation engine, whichmake users focus on the definitions of building geometry and weather conditions toimprove the results reliability.(4) Construct and improve the ANN load prediction model, and calculate the seasonalenergy usage of test rooms, based on limited test data. It is reported that the heatingaverage load is91W/m2, and the cooling average load is149W/m2for the typical officeheat-gain settings in Shanghai. Meanwhile, the improved ANN model has betterperformance and is useful for occasions in which seasonal and even annual energy usageare needed based on limited test data.(5) Investigate several influential factors in the VRV energy calculation and proposesolutions. It shows that temperature input regulation is effective to calibrate the simulationcurves and make it closer to the real curves. The set point temperatures in the simulationinput must be replaced with actual temperature. Besides, heat storage and air change perhour (ACH) have large impact on the simulation results. Proposed are two correctionmethods, i.e., equivalent heat-transfer coefficient correction method for the buildingenvelope with thermal bridge involved, and the heat-mass surface correction method ofenvelope, which improve the accuracy effectively.(6) The simulation model of energy recovery ventilator (ERV) as the fresh airintroducer of VRV system is built and validated experimentally, and the sensible heat andlatent heat recovery of ERV as well as the operating efficiency is investigated both for Beijing and Shanghai weathers with different VRV temperature set-points. Simulationresults show that the latent heat recovery is similar in winter, but significantly different insummer for both weather conditions, especially for the hot and humid July and August.The average latent heat recovery in the two months in shanghai is1.48times as much asthat in Beijing. The maximum value of sensible and latent heat recovery in winter is10times as much as the counterpart in transitional and summer season in Beijing, while5.5times in shanghai. For cold area, heat recovery in transitional and summer season is tiny,compared with that in winter. With different VRV indoor temperature set-points, the energyperformance of ERV along with the total energy supplied by air conditioning system isinvestigated both for different weathers in China in terms of an index defined asλ ERV.Simulation results show that the seasonal average of the ratio is linear with the VRV indoortemperature set-points.(7) The energy consumption for VRV and other common air conditioning systems areinvestigated, including variable air volume system(VAV) or Fan-coil system(FCU), andair-cooled or water-cooled chiller, with energy usage as the only evaluation index. Besides,the multi-objective decision-making method in the fuzzy theory is used in thecomprehensive evaluation of VRV and other system scheme. The advanced technolodgy,environmental protection, economics, management level etc can be evaluated together tooptimize the whole system performance and guide the feasibility in real applications. |
PDF Full Text Request