1、Michael West is Principal-CEO with Advantek Consulting, Inc. headquartered in Melbourne, FL. He earned a doctorate in Mechanical Engineering - Thermal Science from the University of Florida, is a practicing Professional Engineer, and holds an EPA 608 Types I, II, and III refrigerant technician certi
2、fications. Richard Combes is Engineering Consultant with Advantek Consulting, Inc. in Beaufort, SC. He has over 30 years of experience with cutting-edge technologies. Unitary HVAC Equipment: Performance Optimization Strategy and Field Tests Michael K. West, PhD, PE Richard Combes, PE, PhD Member ASH
3、RAE Member ASHRAE ABSTRACT Although often garnering scant attention, commercial unitary HVAC systems, such as rooftop air conditioners, are estimated to consume 0.88 quads of energy annually, or about 46% of commercial building cooling site energy consumption, and are used to cool over 60% of all co
4、mmercial space in the U.S. The as-installed energy efficiency of unitary systems can be half that of central systems, and the efficiency gap widens as systems age due to maintainability issues. When tuning systems, energy engineers and service technicians use indirect indicators of equipment perform
5、ance and make adjustments according to manufacturer guidelines and standard field practice, which varies with their level of experience. Growing numbers of unitary systems combined with shrinking budgets result in deferred maintenance, and long-term operation of equipment at degraded levels. Energy
6、efficiency is a metric that must be measured to be optimized. This paper reports on field testing of continuous sensing of operating energy efficiency to control unitary equipment operating parameters, provide remote fault detection diagnostics, and support maintainability. Optimization systems were
7、 installed on package units at three sites in diverse climate locations: Cape Canaveral, FL; Mojave Desert, CA; and Beaufort, SC. The systems utilize a relational control strategy to continuously maximize the ratio of cooling delivered versus power consumed as operating conditions vary over a day an
8、d across seasons, and as components degrade over time. Condenser fan speed, supply airflow, evaporator temperature, outside airflow, and refrigerant charge were continuously adjusted by the system to maintain a state of optimized operation. The systems successfully detected and attempted to compensa
9、te for faults such as low refrigerant charge or condenser coil fouling, and reported operating EER, pressures, temperatures, and efficiency degradation to service technicians in an actionable way. Analysis of resulting data from the field tests shows considerable unitary energy efficiency gains and
10、maintenance improvements can be obtained cost effectively. INTRODUCTION Commercial unitary HVAC systems, or rooftop air conditioners, are used to cool over 60% of U.S commercial floor area (DOE, 2013). Rooftop units are also available in heat pump models as an alternative to fuel gas or electric res
11、istance heating. In total, they consumed 0.88 quads of energy annually, or about 46% of commercial building cooling primary energy consumption in 2010 (DOE, 2011). About 170,000 new unitary systems sized 8-tons (28 kW) and larger are installed annually in the U.S. and there are over 1.6 million unit
12、s in service that were installed since 2005 (AHRI, 2015). Rooftop air conditioners (RTUs) have been identified as a high priority target for energy savings in buildings by ACEEE (Sachs, 2009). The as-installed energy efficiency of unitary systems can be half that of central plants and the efficiency
13、 gap widens as systems age due to maintainability issues (Little, 2001 and EPRI, 1997). The U. S. Department of Energy (DOE) teamed with American Society for Heating, Refrigeration and Air Conditioning Engineers (ASHRAE) and the Retail Industry Leaders Association (RILA) to launch the Advanced RTU C
14、ampaign, started in May 2013. The Campaign “is a recognition and guidance program designed to encourage building owners and operators to take advantage of savings opportunities from high efficiency RTUs“ (Advanced RTU, 2015). The Campaign is based on the premise that both installed and new RTUs are
15、excellent targets for improved energy efficiency and significant energy savings. Technology is needed that can increase the energy efficiency and maintainability of unitary equipment to be comparable with central plants. Package units are typically selected in applications where low cost and ease of
16、 maintenance are paramount, so technology advances must be cost effective and enhance maintainability. Most unitary models have fixed operating parameters, such as constant speed fans, which differs markedly from variable speed central plants that can be twice as energy efficient. The actual energy
17、efficiency of a unit thats been in operation for several years could be degraded 10 to 40% from its like-new condition, although it might appear to be performing adequately to occupants and service technicians, usually because units are oversized. Efficiency degradation is largely invisible using cu
18、rrently available diagnostic tools, so a system that measures energy efficiency is a step forward. A versatile diagnostic and once the humidity setpoint range is satisfied the temperature is adjusted relationally along with other parameters to maximize the amount of cooling delivered versus power co
19、nsumed. Supply airflow is adjusted correspondingly, for example, more restrictive duct work with higher pressure losses will tend towards lower airflow settings, or in other installations the system will take advantage of free flowing ductwork to provide more airflow and increased energy efficiency.
20、 Figure 1 Results from ORNL Mark VII modeling of a prototype 4-ton package unit showing how optimum refrigerant charge level (z-axis and colored contours) varies with condenser outdoor air inlet temperature (x-axis) and indoor supply airflow (y-axis). The technology addresses EER degradation due to
21、refrigerant leaks in a straightforward manner. Service technicians sometimes address minor refrigerant leaks by adding refrigerant during seasonal service visits. It is difficult and time-consuming to locate a small leak, which is usually not repairable without the labor-intensive procedure of recov
22、ering, evacuating, and recharging a system. Systems are on occasion intentionally overcharged to compensate for pinhole leaks. Unfortunately, repeated topping off over time can result in drift of the mixture proportion in blended refrigerants, for example, more R-125 than R-32 could escape from a le
23、aking R410A condenser coil, since R-125 condenses first. The controller detects a refrigerant charge imbalance, and adjusts the charge accordingly by flowing refrigerant into or out of a receiver. The controller also responds to an overcharge condition, as ambient air temperature and airflow affects
24、 optimal refrigerant charge level. Simulation results show that energy efficiency is increased by reducing charge as ambient temperature rises, and as evaporator coil airflow is reduced. DATA ANALYSIS Data logging of the cooling delivered versus power consumed enables calculation of a field-measured
25、 operational IEER (Integrated Energy Efficiency Ratio) calculated using the formulas published in ANSI/AHRI Standard 340/360 (AHRI, 2007), which is displayed on the controller screen. Trending of operational IEER can quantify long-term degradation of energy efficiency when compared against as-instal
26、led values. Regression calculations are performed to obtain linear relations for power used and cooling delivered versus ambient temperature, which characterizes most of the variation in operating conditions entering air conditions typically have much less variation than ambient temperature. The reg
27、ression yields equations of two lines in the form y=mx+b that are Power = mp * OAT + bp and Cooling = mc * OAT + bc (1a and 1b) From equations 1a and 1b, Power and Cooling are calculated at the four standard rating temperatures: OAT = 90, 81.5, 68, 65 F, giving four values of Power and Cooling. Then
28、 EER is calculated at the four temperatures for substitution into the formula for IEER defined by Section 6.2.2 of ANSI/AHRI Standard 340/360-2007, IEER = 0.02 * EER(95) + 0.617 * EER(81.5) + 0.238 * EER(68) + 0.125 * EER(65) (2) While operational IEER is not directly equivalent to published IEER ra
29、tings measured under tightly controlled laboratory conditions, it can be valuable for comparisons over time and between systems. FIELD TESTING Test systems were installed at three sites in diverse climate locations: Cape Canaveral, FL; Mojave Desert, CA; and Beaufort, SC. The Florida and South Carol
30、ina sites are located at humid and temperate ends of the ASHRAE hot this is a legacy R22 system that serves a retail store. The California equipment is a dual-compressor, 12-ton (44 kW) R410A heat pump installed 2010, which serves a classroom building. The diagnostic controller system has capability
31、 to simultaneously optimize many operating parameters using a relational control algorithm, including supply air temperature setpoint, supply fan airflow, cooling coil temperature setpoint, bypass damper position, condenser fan speed, fresh air damper position, and refrigerant charge level. Many of
32、these parameters are not controllable on most single zone unitary models. Accordingly, the test units were also retrofitted with variable speed supply and condenser fan drives, and a bypass damper with actuator in order to test simultaneous optimization of several parameters. Supply airflow is optim
33、ized to maximize sensed EER, rather than typical duct static pressure based VAV control test units were single zone, not VAV systems. Note that relational control of these variable components was used to maximize operating EER, rather than conventional VAV control to meet a static pressure setpoint.
34、 Baseline performance measurements were taken over the first cooling season of the project to benchmark energy efficiency before installation of the diagnostic controller technology, which was installed between the two cooling seasons of the project. Performance during the second cooling season was
35、compared against the benchmark. Metrics used to measure performance are field-measured EER (Energy Efficiency Ratio = Btu/hr cooling / total unit Watts and IEER (Integrated Energy Efficiency Ratio) ; cooling season electric kWh consumed both actual and normalized to cooling degree-day and heating de
36、gree-day (CDD and HDD) weather data for adaptation to other climate locations; IAQ via space relative humidity, temperature, and carbon dioxide levels and the fraction of occupied hours which these levels are deemed acceptable; and maintenance costs and the number and severity of unplanned or emerge
37、ncy maintenance interventions, if any. Web-based 45-channel data loggers at each site were used to collect averaged data at 1-minute intervals continuously throughout the project period. Dependent system-level variables measured are: System power demand (kW) and energy consumption (kWh); system cool
38、ing delivered in terms of both sensible and latent (Btuh); and occupied space air temperature (F), relative humidity (%RH), and carbon dioxide level (ppm) differential with respect to ambient carbon dioxide level. Dependent component-level variables measured are: compressor and fan electric power (W
39、atts), refrigerant pressures and temperatures at the inlet and outlet of the compressor (psig and F); refrigerant flow rate (gpm); refrigerant charge (lbm); coil air face velocity (fpm). A propagation of error analysis was performed on typical data sets using a sensitivity analysis technique, to qua
40、ntify the error in the IEER measurement from nth-order uncertainty in the temperature, humidity, pressure, flow, and power inputs. The accuracy of the measured operational IEER is generally 5% or 0.6 Btuh/Watt via this sensitivity/propagation of error uncertainty analysis. Because comparisons were p
41、erformed using data from the same sensors installed in the same positions, and the same equations, calibrations and correlations were used in the analysis, the same uncertainty in the baseline field operational IEER equally applies to the test systems operational IEER. Thus, the field measured IEER
42、values are directly comparable to each other with better certainty than comparisons with values obtained from other sources, such as factory ratings obtained under laboratory conditions. Figure 3 (a) Diagnostic controller technology assembled for bench testing and calibration, (b) controller touch s
43、creen panel as installed as the Cape Canveral, FL test site. The touch screen is accessible remotely via web. RESULTS Data collected over two cooling seasons was analyzed to evaluate the performance of each of the three package units. Data sets for benchmark performance span from summer 2014, and fo
44、r the units after installation of the diagnostic controller from summer 2015. The authors found a significant increase in the field-measured operating IEER of the three test units along with decreased energy consumption, while maintaining or improving comfort and ventilation levels. On a few occasio
45、ns, the controller identified and alerted faults, including a failed condenser fan motor and low refrigerant charge. The controllers adjusted operating parameters to maximize performance, as shown in Figure 4. Sensor inputs are filtered to remove transients caused by compressor starts /stops and con
46、troller set point initializations. The retail store at the South Carolina site does not require a tight humidity setpoint, so a band setting between too dry and too humid was entered into the controller. Steady-state damper position signal plotted in Figure 4a shows how the controller modulates the
47、bypass damper open as space humidity rises, and modulates closed in the setpoint range of 50% to 60%rh. The California site required no dehumidification whatsoever. Steady state condenser fan speed signal plotted in Figure 4b shows the controller response versus outdoor ambient temperature. The Sout
48、h Carolina system benefited from the units intertwined condenser coil circuiting, which allowed the condenser fan to run at approximately 40-60%-speed when one compressor was energized. With two compressors energized, there was fan energy savings at ambient temperatures below 80F (27C) down to appro
49、ximately 80%-speed at the coldest ambient temperature during the test period of 57.2F (14C). The other two package units have face-split condenser coils, so fan energy savings was less. Damper Position Control Signal vs RHTest Site: Beaufort, SC02040608010040 45 50 55 60 65 70Space Relative Humidity %rh% Damper OpenOpeningClosingCondenser Fan Speed Signal vs OATTest Site: Beaufort, SC02040608010050 60 70 80 90 100Outside Air Temperature F% Speed10.0 15.6 21.1 26.7 32.2 37.8CStage 2Stage 1Figure 4 (a) Damper position opened according to rise in space relative hu
