1、 Tianzhen Hong, Kaiyu Sun, Rongpeng Zhang and Oren Schetrit are researchers and program manager in the Building Technology and Urban Systems Division, Lawrence Berkeley National Laboratory, Berkeley, California. Ryohei Hinokuma is manager with Daikin US Corporation. Shinichi Kasahara and Yoshinori Y
2、ura are manager and researcher with Daikin Industries LTD, Japan. Development and Validation of a New VRF Model in EnergyPlus Tianzhen Hong, PhD, PE Kaiyu Sun Rongpeng Zhang, PhD Member ASHRAE Member ASHRAE Member ASHRAE Oren Schetrit Ryohei Hinokuma Shinichi Kasahara Yoshinori Yura ABSTRACT VRF (Va
3、riable Refrigerant Flow) systems vary the refrigerant flow to meet the dynamic zone cooling and heating loads, leading to more efficient operations during part-load conditions. VRF systems have minimal or no air duct, which also contributes to reduce heat losses. This paper introduces a new model to
4、 simulate the energy performance of VRF systems in heat pump operation mode (cooling or heating but not simultaneously). The main features of the new model include (1) introducing separate curves for capacities and power inputs of indoor and outdoor units instead of overall curves for the entire sys
5、tem, (2) allowing variable evaporating and condensing temperatures in the indoor and outdoor units, and (3) introducing variable fan speeds based on the temperature and zone load in the indoor unit. These features enhance the accuracy of the estimation of VRF system performance in both heating and c
6、ooling modes, especially during low part load operations. Another new feature is a physics model to calculate pressure and thermal losses in the refrigerant piping network which varies with the refrigerant flow rate, operational conditions, pipe length, and pipe and insulation materials instead of a
7、 simple correction factor. The new VRF model enables the potential simulation of demand response of VRF systems by directly slowing down the speed of compressors in the outdoor units with invertor technology. This paper describes the new VRF algorithm development, the model implementation in EnergyP
8、lus (“the simulation program” thereafter), and the model validation. For model validation, field tests were performed in a typical California house and actual performance data of VRF system was collected. The energy consumption of the installed VRF system was simulated using the new VRF model in the
9、 simulation program. The comparison of the simulated and measured energy use of the VRF system showed a reasonable match under the criteria of ASHRAE Guideline 14. This demonstrates that the new VRF model can accurately represent the actual performance of the VRF systems. Lessons learned from the mo
10、del development, calibration, and validation are discussed. The research outcomes and the new VRF model in the simulation program can improve the accuracy of simulation of VRF system performance, which can support code compliance credits toward the use of VRF systems as well as utility incentive pro
11、grams for VRF technologies. INTRODUCTION The energy consumption by residential and commercial buildings has reached levels of 20% and 40% in developed countries and has exceeded the other major sectors (e.g. industrial and transportation) (Prez-Lombard et al. 2008). More than 30% of the total energy
12、 use in buildings comes from HVAC systems. To save building energy and reduce carbon emissions, it is crucial to improve the energy efficiency of HVAC systems. VRF (Variable Refrigerant Flow) systems provide more flexible control and better thermal comfort while consuming less energy, due to the sys
13、tems multiple advantages, including: variable refrigerant flow that leads to high efficient operations during part-load conditions; minimal or no ductwork which reduces heat losses; smaller indoor fans that consume less energy as well as reduce indoor noise (Liu and Hong 2010; Aynur 2010; Amarnath a
14、nd Blatt 2008). A typical VRF system has one outdoor unit serving multiple indoor units. Each indoor unit can have an individualized thermostat to control operation (i.e. it can be turned off if the zone is not occupied or the thermal comfort requirement is met). The flexibility of zoning and contro
15、l collectively contribute to extra potential energy savings for buildings, especially those with diversified zonal loads (such as residences). In such cases, it becomes important to accurately simulate the energy performance of VRF systems for both retrofit and new construction. In the first stage o
16、f our project a new VRF model was developed to simulate the energy performance of VRF systems in heat pump operation mode (Hong et al. 2014). The main improvement of this model was the introduction of evaporative and condensing temperature capabilities in the indoor and outdoor unit capacity modifie
17、r functions. The energy performance of a VRF system in a Prototype House in California was simulated using this VRF model and compared with three alternative HVAC systems. This paper focuses on the second stage of this project, where the field testing of a real VRF system is performed in a typical h
18、ouse in California. The algorithms of the VRF-HP systems developed in the first stage are enhanced and validated using the field test data. The validated new VRF-HP model in EnergyPlus (“the simulation program” thereafter) can accurately simulate the energy performance of the VRF-HP systems, which e
19、nables fair credit of the VRF systems toward code compliance, performance ratings, and utility incentive programs. METHODOLOGY Computer based building energy modeling and simulation has been demonstrated as an effective way to evaluate the energy and cost benefits of building technologies (Hong et a
20、l. 2000). In this project the simulation program was chosen as the simulation engine to evaluate the energy performance of VRF (heat pump type) systems for residential buildings in California. Three major steps: (1) Field testing of a residential house in California, (2) Development, enhancement and
21、 implementation of VRF algorithms, and (3) Validation of the VRF model, were conducted for the study. FIELD TESTING To validate VRF algorithms and test the real performance of VRF systems, a VRF system was installed, commissioned and tested in an instrumented house, named Caleb House, located in Sto
22、ckton, California (Wilcox 2014). The case study house is a two-story single family home with a total conditioned floor area of 205 m2 (88 m2 on the first floor and 117 m2 on the second floor). It was built in 2005, with 4 bedrooms, a living room, a dining room, a kitchen, a laundry room and 3 bathro
23、oms. Figure 1 shows the facade and Figure 2 shows the plan layout of the house. Table 1 summarizes the thermal properties of the building envelope. For the VRF system, the outdoor unit is located on the ground outside the house. There are four indoor units, two on each floor. On the first floor, one
24、 indoor unit is installed in the living room while the other is installed in the kitchen. On the second floor, one indoor unit is installed in the master bedroom, while the other is installed in the hallway to condition the other three bedrooms through air ducts. All the performance data of the VRF
25、system, including supply and return air temperature, energy use of each component, fan speed etc., is monitored by the RAM Monitor, a monitoring tool developed by the VRF manufacturer. The operation of the VRF system is controlled by Manufacturers Intelligent Control System. During the field test, t
26、he case study house is unoccupied to avoid uncontrollable impacts from occupants. However, to test the real performance of the VRF system, it is necessary to create an artificial environment to represent the real indoor environment. The house was operated under controlled conditions that simulate no
27、rmal internal gains as defined in Californias Building Energy Efficiency Standards (Title 24) for residential buildings. For this purpose, additional equipment is deployed in the house, including electric heaters, humidifiers and fans. Electric heaters and humidifiers act as occupancy simulators, wh
28、ich are used to create sensible internal loads (mainly from lighting, electric equipment and occupants in a real house) and latent internal loads (mainly from occupants and cooking), respectively. Fans are used to make sure the air is well mixed. Figure 1 The case study house and its VRF system sche
29、matic Table 1. Thermal Properties of the Envelope Area (m2 / ft2) U-factor (W/(m2K) / Btu/(hft2.F) SHGC Exterior Walls 215 / 2314 0.39 / 0.0687 Roof 74 / 797 1.03 / 0.181 Exterior Windows 31 / 334 1.99 / 0.350 0.3 The house is instrumented with a variety of sensors and meters, including temperature
30、sensors, humidity sensors, and smart meters (Table 2). They are used to monitor the temperature and humidity of each room and of supply and return air, the on/off status of the electric equipment, and the energy use of all the installed electric equipment. The thermostat settings are based on Title
31、24 standards that produce load patterns similar to those of an actual residence. A weather station is installed outside the case study house, monitoring the ambient conditions, including dry-bulb air temperature, humidity, wind speed and solar radiation. Table 2. List of the Monitored Data Points Ca
32、tegory Item Energy Use (1) Total House kWh, (2) House AC Outdoor Condensing Unit kWh, (3) House AC Indoor Unit kWh Occupancy Simulator (1) Electric heaters kWh, (2) Humidifiers kWh Ambient (1) Outdoor Ambient Temperature, (2) Outdoor Ambient Humidity, (3) Wind Speed, (4) Horizontal Solar Radiation V
33、RV system (1) Thermostat Set Point, (2) Supply Air Temperature and humidity, (3) Return Air Temperature and humidity, (4) Return Air humidity, (5) Condensing Unit status (on/off), (6) Inlet refrigerant Temperature of indoor units, (7) Outlet refrigerant Temperature of indoor units 1F2FO/D Unit ： VR
34、V - S （ 3 to n ） 1I/D Un it ： Du cted 4Z one 3Z one 4Z one 2Z one 1The installation and commissioning of the VRF system in the case study house was done in May 2013. The VRF system has been running since then and detailed measured data has been collected. It should be noted that the case study house
35、 has installed three independent HVAC systems: the VRF system, the as-built Title 24-2005 baseline system, and the high efficiency system. Each system is scheduled to run for two days and then rotates to another system. The measured performance data is then used as a reference for the improvement an
36、d validation of modeling algorithms. VRF MODEL DEVELOPMENT Based on the VRF model developed in Phase I, the following significant improvements are made in Phase II: (1) The introduction of separate curves for capacities and power inputs of indoor and outdoor units instead of overall curves for the e
37、ntire system; (2) Variable evaporating and condensing temperatures in the indoor and outdoor units; (3) Variable fan speed based on the temperature and zone load in the indoor unit. These new features significantly improve the accuracy of the simulated VRF system performance in both heating and cool
38、ing modes, especially during low load operations. Another new feature is a physics based model to calculate thermal loss in the refrigerant piping network. Piping loss occurs when refrigerant travels through the pipes creating refrigerant pressure drops and heat losses. It affects the VRF system ope
39、ration in several ways. First, the heat loss creates an extra load on the system, leading to higher energy consumption. Second, the pressure drop and heat loss change the operation conditions of the compressor (i.e., compressor suction pressure and compressor suction temperature) and thus affect the
40、 operational efficiency. Compared with the heat loss model that relies on a simple correction factor, the proposed model is able to estimate the thermal loss more accurately by considering the variations in the refrigerant flow rate and operating conditions. In addition, the new VRF model enables th
41、e potential simulation of the demand response of VRF systems by directly slowing down the speed of compressors in the outdoor units with invertor technology. Figure 11 compares the existing VRF system modeling approach currently used in the simulation program with the newly proposed method. It shoul
42、d be noted that Figure 11 only lists the main equations not all of the equations actually used in the calculation. For each simulation time step, the simulation program performs a round of zone air heat balance analysis to determine the zone load and then determines the VRF system operation mode. In
43、 the existing VRF model, the simulation program uses equation (1) and (2) to calculate the actual output of each indoor unit. Then the capacity required by the outdoor unit is calculated using equation (3) taking into account the pipe length and height correction with equation (4). The total power c
44、onsumption is computed using equations (7) to (10), incorporating the modifiers correlated with average room wet bulb temperature, outdoor dry bulb temperature, and the part-load ratio. In the new VRF model, the effective evaporating temperature of indoor units is first calculated using equations (1
45、1) to (14). For outdoor unit, heat loss through the pipe can be obtained via (15) to (17) and the compressor suction temperature can be obtained via (18). Then the required/effective condensing temperature of the outdoor unit is calculated using equations (19) to (22). The compressor speed as well a
46、s the compressor power is calculated via (23) and (24), on the basis of above results. Finally, the total electric power consumption by the outdoor unit is obtained via (25). Note that the piping loss calculation and the system performance analysis are coupled together. More specifically, the piping
47、 loss changes the operating conditions of the system may lead to different control strategies and thus have a reverse affect the amount of piping loss. This makes it difficult to obtain an analytical solution for a number of operational parameters (e.g., enthalpy of refrigerant entering the indoor u
48、nit), and therefore numerical iterations are employed to address this problem. More details about the algorithms, especially the equations, are explained in the New Feature Proposal for VRF systems of the simulation program (Hong et al. 2015). Figure 11. Existing VRF model in EnergyPlus 7.2 (DOE 201
49、2) vs. the new VRF model VRF MODEL VALIDATION To validate the new VRF model, a beta version of the simulation program is implemented with the proposed VRF model and used to simulate the energy consumption of the VRF system installed in the case study house. The measured onsite weather data and cooling/heating loads are used as the inputs of the simulation. The simulated and measured energy consumption data are then compared to determine the accuracy of the VRF model. The calibration criteria from ASHRAE Guideline 14 are adopted as the cri
