What simulation can tell us about building tuning

Transcription

1 What simulation can tell us about building tuning Dr Paul Bannister, M.AIRAH, Hongsen Zhang Projects and Advisory Services Division Energy Action Pty Ltd (incorporating Exergy Australia Pty Ltd) ABSTRACT Building tuning has long been recognised as a critical method for the improvement of the performance of existing buildings. However, the estimation of the potential benefits of HVAC control adjustments is difficult using normal industry calculation methods. Fortunately, with recent advances in building simulation models, it is possible to test a number of common tuning strategies to determine their effectiveness in achieving energy savings. Based on a generic mid-sized VAV building, the authors have used an IES simulation model to assess the impacts of a number of common control algorithm adjustments, including dead-band and proportional-band adjustments for VAV terminals, fan control and supply-air temperature control, economy cycle and minimum outside air control. Results are repeated for Sydney, Melbourne, Brisbane, Canberra and Darwin to show the way energy impacts change with climate. Combined scenarios are used to show that the difference between best practice and poor control can range as high as 90 per cent, demonstrating the fundamental importance of control. Sensitivity to control is considerably greater in milder climates. INTRODUCTION Australian office buildings consume a large amount of energy in the provision of air conditioning. The temperate Australian climate means that the associated controls play a significant role in the determination of air conditioning efficiency. As a result, optimisation of HVAC controls is a common technique for efficiency improvement. However, the estimation of the energy savings impact of individual control measures in the energy management industry tends to be crude, and the selection of control measures is frequently based on intuition rather than science. With improvements in building simulation packages, it is now possible to robustly assess the savings and impacts associated with common control methods and failures to develop a more analytical understanding of the potential of each to assist or detract from building efficiency. In this study, a base case model and a series of scenarios with common control failures or improvements have been developed. The modelling has been carried out with a standard VAV configuration, representing the most common building servicing type for medium to large buildings in Australia. The results of the base case and the scenarios have been analysed and compared to evaluate the importance of each control method. MODELLING DESCRIPTION Base case A typical Australian commercial building with a conventional, well-designed VAV HVAC system was modelled as the base case for this study. Diagrams of the building are as shown in Figure 1 and Figure 2. The total NLA is 5,000 sq m. Figure 1: View of simulation model. Figure 2: Floor plate showing zones. The simulation follows NABERS Energy Guide to Building Estimation Version 2011 June. The detailed description for the base case is provided in the appendix. Only the items associated to the subsequent scenarios are listed this section. Ventilation rate The ventilation rate during occupied hours was set at 7.5 l/s/person. Zone temperature control The zone temperature control was to 22.5 C with a dead band from 21.5 C to 23.5 C, and 0.5 C proportional bands either side of this. The VAV box minimum turndown was set to 30 per cent for perimeter zones and 50 per cent for centre zones. AHU configuration Separate AHUs were provided for each façade and for the centre zone. All AHUs were configured with a temperature economy cycle with a dewpoint lockout at 14 C and a drybulb lockout at 24 C. Minimum supply air temperature was set to 12 C. The supply air temperature was reset from 32 ECOLIBRIUM DECEMBER 2014

2 minimum to 24 C when the high select zone temperature dropped from 23.5 C to 21.5 C. AHU fans were modelled as having an efficiency of 70 per cent, motor efficiency of 90 per cent and an x2.7 turndown (representing variable pressure control). A total fan pressure of 800Pa was used. Scenarios Over 30 scenarios of different control approaches and failures have been run for Sydney, Melbourne, Brisbane, Canberra and Darwin in order to gain some insight into the impacts of a wide range of control issues and approaches on energy use. The following sections summarise some of the key findings. VAV TERMINAL CONTROL Deadband The impact of the VAV control deadband on HVAC energy use is shown in Figure 3. The scenarios used for this figure all have heating and cooling proportional bands of 0.5 C and a set-point (at the mid-point of the deadband) of 22.5 C. It can be seen that deadband plays an important role in determining energy use, particularly in the temperate climates of Canberra and Melbourne. For these locations, a reduction in deadband from 2 C to 1 C a seemingly trivial adjustment can cause total HVAC energy use to increase by in excess of 20 per cent. This reflects the dual impacts of an effective increase/decrease in operating temperature for the building plus, particularly in the region of C deadband, an increase in simultaneous heating and cooling. By contrast, in Darwin, there is little benefit to be obtained from increasing the deadband, other than the increase in effective operating temperature for the building Control Deadband ( C) Sydney Melbourne Brisbane Canberra Darwin Figure 3. Impact of deadband on HVAC energy use. Set-point The industry abounds with rules of thumb as to the impact of changing temperatures set-points on HVAC energy use. In reality, the actual impact of such a change is highly dependent on climate and (as is clear from Figure 3) assumptions in relation to deadband. To test the impact of temperature set-point in isolation, scenarios using a fixed deadband of 1 C, heating and cooling proportional bands of 0.5 C and varying set-points in the midpoint of the deadband were run. The results are shown in Figure 4. It can be seen that the impact of the set-point is quite dependent upon climate, with the cooler climates of Canberra and Melbourne showing an increase in energy use as the set-point is raised indicating dominance of heating energy, while the warmer climates all show a decrease in energy as set-point increases, reflecting the cooling-dominated nature of these buildings. Minimum VAV airflows A further parameter available for adjustment in the operation of a VAV system is the minimum flow. To test the impact of this, scenarios with 5 perimeter zone/7 centre zone and 7 perimeter/9 centre zone minimum flows were run and compared to the base case, which has 3 perimeter/5 centre zone/3 minimum flows. The results are shown in Figure 5. (3 / 5) It is apparent from Figure 5 that minimum flows have a significant impact in all temperate climates, again decreasing as the climate becomes warmer. The primary causes of the impact are increased fan and reheat energy associated with higher minimum flows. Darwin, by contrast, shows little variation with VAV minimum flows. AHU CONTROL Nominal Set-point ( C) Sydney Melbourne Brisbane Canberra Darwin Figure 4: Impact of temperature set-point on energy use. Note all scenarios in this figure use a 1 C deadband and thus use more energy than the base case (which has a 2 C deadband) Figure 5: Impact of VAV minimum flow on energy use. Fan control A wide variety of tuning and control issues can contribute positively or negatively to fan energy use. In order to characterise these issues, the base case scenario assumes a variable fan speed, variable pressure control, which is represented by a fan flow to energy relationship of x 2.7. Additional scenarios have been run comparing this to a fixed-pressure, variable-speed fan control 5 / 7 7 / 9 DECEMBER 2014 ECOLIBRIUM 33

3 (represented by an x 2 characteristic) and to a fixed-fan-speed throttling control (represented by a linear characteristic). The results are presented in Figure 6. (variable pressure, variable speed) (Reset range ) Reset range Reset range Reset range Reset range Figure 7: Impact of supply air temperature reset on energy use. Fixed pressure variable speed control Fixed speed throttling control 1 Figure 6: Impact of fan control on energy use. It is clear once more from the figure that temperate climates are highly sensitive to the fan control. Given that for most modern buildings throttling without variable speed operation is uncommon, the importance of an operating variable pressure control is apparent at around a 5 10 per cent impact on HVAC energy use. Supply air temperature control For all VAV systems, the relationship between flow and temperature is set by the relationship between box operation and the supply-air temperature control. A control that tends to drop the supply-air temperature before the boxes have started to increase flow will produce a low- temperature, low-flow operation; by contrast, a reset that tends to decrease the supplyair temperature only after the boxes are at maximum flow will produce a high-temperature, high-flow outcome. In the absence of simulation analysis, it is not clear which of these approaches produces the best outcome overall. For the purposes of the current exercise, a range of supply-air temperature resets were applied, each changing the supply-air temperature linearly over the same range as the base case but over a different range of control zone temperatures. The results are shown in Figure 7. It can be seen that at either extreme of the test scenarios, energy use increases, in some cases significantly, and that for most climates the base case reset is optimal. This indicates that in the lowest temperature scenario there will be an increase in energy use caused by overcooling and thus zone reheat, while in the highest temperature scenarios, the increased fan energy dominates. However, it is notable that the response between these limits is quite specific to each climate, with Melbourne in particular showing optimum outcomes in higher temperature supply-air flow scenarios than the other centres. This indicates that full optimisation of supply-air temperature control is climate-zone dependent, and moreover is likely to be building dependent as well. This is an area where more detailed simulation of an individual project may yield further benefits. Economy cycle In order to test the impact of different means of control on economy-cycle effectiveness, a wide variety of different economy-cycle configurations were tested relative to the base case (temperature controlled, 24 C dry-bulb lockout, 14 C dewpoint lockout). The results are shown in Figure 8. (temperature controlled, 24 C DB lockout, 14 C DP lockout) 9% 8% 7% 6% 4% 3% 2% 1% -1% No economy cycle Enthalpy controlled, 19 C DB lockout 19 C DB lockout, 7 RH lockout 19 C DB lockout 24 C DBlockout, 15 C DP lockout 19 C DB lockout 24 C DB lockout Enthalpy controlled, 15 C DP lockout Figure 8: Impact of economy cycle on energy use. Numerous observations can be made from the figure: 1. The total impact of the economy cycle is significant in all temperate centres, but smaller than many of the impacts identified in relation to zone control; 2. Excessive lockout limitations on economy-cycle operation can have a significant negative impact on economy-cycle effectiveness; 3. While the most effective scenario is enthalpy controlled, this scenario can be practically matched by the temperature controlled dew-point limited control, which is typically more robust in practice; 4. A simple temperature controlled economy cycle is very effective in Canberra, whereas in other centres some degree of humidity-related control is needed to obtain the full economy-cycle benefit; 5. Darwin, unsurprisingly, shows no economy-cycle benefit. Minimum outside-air volume control With increased emphasis on indoor environmental quality, there has been a tendency for higher minimum outside air volumes to be included in building designs. In order to compensate for the 34 ECOLIBRIUM DECEMBER 2014

4 possible energy impacts of this, there has been a marked increase in the use of CO 2 controls as an ancillary adjustment. To test the impact of this, a range of minimum outside-air quantity and CO 2 control scenarios have been undertaken. The results are shown in Figures 9 and 10. (7.5l/s/person) (no CO 2 control) 2 19% 18% 17% 16% 1 14% 13% 12% 11% 1 9% 8% 7% 6% 4% 3% 2% 1% -1% -2% 2 19% 18% 17% 16% 1 14% 13% 12% 11% 1 9% 8% 7% 6% 4% 3% 2% 1% -1% -2% 10l/s/person 11.25l/s/person 15l/s/person Figure 9: Impact of minimum outside air rates on energy use. 1000ppm 900ppm 800ppm 700ppm 600ppm Figure 10: Impact of CO 2 control on energy use. Note that all scenarios have a design minimum outside air flow of 7.5 l/s/person C0 2 control is permitted to increase airlfow above this figure. In Figure 9, it can be seen that in most climates, the building behaves as would be expected, in that increasing minimum outside-air requirements tend to increase energy use. Furthermore, the degree of impact tends to increase as one heads into colder and hotter climates. Sydney, however, shows the surprising result that the amount of minimum outside air makes little overall difference, and indeed there may be a slight benefit (similar to a mini-economy cycle, perhaps) from higher outsideair levels. In Figure 10, the analysis repeated but this time at fixed design minimum outside air flow but variable CO 2 control in addition to this minimum. Again it can be seen that the colder and hotter climates behave as expected, with lower CO 2 levels corresponding to higher energy use, while the more temperate climates, in this case both Sydney and Melbourne, show unexpected trends. In Sydney, a decreased CO 2 set-point shows improved energy performance, while in Melbourne, there is a suggestion that an optimum set-point may exist. Probably more relevant, however, is the observation that across a broad range of operation, the CO 2 set-point actually makes little difference unless one is in a more extreme climate region. COMBINED SCENARIO TESTING In real buildings, control failures tend to occur in groups rather than individually. As a result, it is worthwhile to examine the impact of combined control scenarios to understand the potential overall impact of poor control. The result of combining many of the poorer control scenarios is shown in Figure Figure 11: Impact of combined control failures and errors on energy use. It can be seen from the figure that the total impact of control failures is substantial ranging from of the order of 20 per cent in Darwin to 90 per cent in Canberra. Combination of multiple scenarios appears to slightly reduce the impact relative to direct addition of the individual scenarios. However, the total scale of impact remains similar, and clearly indicates that controls tuning measures have a substantial role to play in building optimisation. While this is overwhelmingly the case in temperate climates, the combination of multiple disadvantageous control scenarios can still have an appreciable impact in Darwin, where any one individual measure tends to appear relatively unimportant. CONCLUSION Combinahon of poor control scenarios CO2 control 700ppm SAT reset C Linear fan turndown 0.5 C deadband Temperature controlled economy cycle 19 C/7RH lockouts HVAC energy use is substantially determined by how the various HVAC system components operate and interact. Historically, simulation programs have not had adequate representation of HVAC controls to enable the representation of control tuning and optimisation scenarios. However, this situation has improved significantly in recent years. In this paper, a range of common building tuning issues have been represented by simulation of a generic VAV office building in order to explore the sensitivity of building energy use to common control methods. Key findings include: The greatest impacts on building performance occur in relation to adjustments to terminal control, with deadband and minimum VAV flows both playing a critical role. AHU control provides further modulation of energy use through adjustment of the supply- air temperature control regime. There is evidence that this needs to be optimised differently for certain climates, and may be to some extent building. DECEMBER 2014 ECOLIBRIUM 35

5 Economy-cycle control is of moderate importance. However, over-constraining of economy- cycle operation based on outside conditions can result in significant loss of effectiveness. Minimum outside-air control produces intuitively predictable outcomes in cold and hot climates but can behave unexpectedly in temperate climates such as Sydney and Melbourne, and therefore needs careful review on a buildingby-building basis to justify CO 2 control. Combined disadvantageous control scenarios can increase total HVAC energy use by up to 9 in temperate climates, dropping to 2 in tropical climates. The use of simulation has demonstrated that there is value in building tuning in all climates but particularly in the temperate climates where the majority of the Australian commercial building population is situated. Furthermore, the results of this paper illustrate that simulation can be successfully used to explore the sensitivity of a building to control issues and thus to assist in better tuning practices that are customised to both climate and building. APPENDI DETAILED DESCRIPTION FOR THE BASE-CASE MODEL A typical Australian commercial building with a conventional, well-designed VAV HVAC system was modelled as the base case for this study. The simulation follows NABERS Energy Guide to Building Estimation Version 2011 June. Basic characteristics The base model has the following characteristics: Eight-storey building with underground carpark 50 per cent WWR 25m by 25m floorplate, four perimeter and one centre zone per floor, the total area is 5,000m 2 HVAC: VAV system with electric terminal heating Floor to ceiling height 2.7m Plenum height 0.9m Building construction The following constructions were used: Glazing Double glazing with the characteristics shown in Table 1 was used in the simulation. Opaque construction The following opaque constructions were used in the simulation: Building loads The building loads are as follows: Occupancy. 10m 2 per occupant. Sensible load of 75 W/m 2 and 55 W/m 2 latent load. Equipment. 15W/m 2 Lighting power density. The lighting power density of 10 W/m 2 is distributed equally between the return plenum and the occupied zone. Table 1: Glazing characteristics Type External glazing Construction (From outside to inside) 6mm Pilkington Optifloat Green Air cavity 6mm Clear float U value (W/m 2.K) Table 2: Opaque construction details Construction description External wall Floor Underground car park floor Material (From outside to inside) Shading coefficient Ventilation and infiltration The ventilation rate during occupied hours was set at 7.5 l/s/person. % Light transmittance Thickness (mm) Concrete 150 Air cavity 25 Plasterboard 12 Carpet 6 Concrete 150 U-value correction layer Ground contact correction layer Total R-Value (sq m K/W) The infiltration through the windows was simulated by the MacroFlo module of IES. The wind pressure coefficients were determined by the ratio of the height of the window location to the building height. A median crack flow coefficient of 0.23 l/(s m P a 0.6) was selected to represent the average leakage through the windows. The crack length is equal to the window perimeter. 50 3,069 Concrete Ceiling Acoustic tile Roof Metal sheeting 5 Glass fibre Note that the total R-Values above include the surface resistances and represent typical figures in the existing building stock. The R-Value of the ground floor has been adjusted using the EN-ISO method. 36 ECOLIBRIUM DECEMBER 2014

6 Weather file The TRY weather file appropriate to the region was used. Building was modelled in Sydney, Melbourne, Brisbane, Canberra and Darwin. Modelling software Modelling was executed in IES<VE>, which was developed by Integrated Environmental Solutions Limited and has passed BESTEST accreditation. The program has been widely used in Australia and has widespread international acceptance. Schedules of operation The NABERS schedules were used for all occupancy, lighting and equipment operation. HVAC Zone temperature control The zone temperature control was to 22.5 C with a dead band from 21.5 C to 23.5 C and 0.5 C proportional bands either side of this. The VAV box minimum turndown was set to 30 per cent for perimeter zones and 50 per cent for centre zones. economy cycle with a dew-point lockout at 14 C and a drybulb lockout at 24 C. Minimum supply air temperature was set to 12 C. The supply air temperature was reset from minimum to 24 C when the high select zone temperature dropped from 23.5 C to 21.5 C. AHU fans were modelled as having an efficiency of 70 per cent, motor efficiency of 90 per cent and an x 2.7 turndown (representing variable pressure control). A total fan pressure of 800 Pa was used. Heating The heating was assumed to be direct electric terminal heating only. Cooling The chillers used in the model were a York low load water cooled scroll chiller (YCWL0260HE50) of capacity kw and two York centrifugal chillers (YMC2-S0800AA) of capacity 798 kwr. The chilled water temperature was fixed at 6 C. Part load performance data at a range of condenser water temperatures were used to look up the Coefficient of Performance (COP) over a range of operating conditions. Three cooling towers with 7W/kW of heat rejection were modelled. AHU configuration Separate AHUs were provided for each facade and for the centre zone. All AHUs were configured with a temperature DECEMBER 2014 ECOLIBRIUM 37