**5. Results and discussion**

Considering the limited data sets that were simulated, making any generalizations based on the simulation results in this case study would seem ambitious. The results are nevertheless important and can provide the basis for a more general representation of using variable set points on static pressure control.

Simulations were performed for different values of the gain Kpath (0 to 1 with a step of 0.25). Three mean outdoor temperature levels were considered (-20, 0 and +20°C). Outdoor temperature varied as a ±4°C sinusoidal swing during a 24 hour period. Simulations included heat gain from solar radiation, and the simulated dates were in January, April, July and October. The energy consumption of 0°C outdoor conditions was determined as a mean between the usage of April and October.

The two upper diagrams of Fig. 9 show the pressure difference set points (left) and ventilation flow rates (right) during a day for different values of Kpath. The remaining diagrams show how CO2 responses in each of the rooms became for different values of Kpath.


• Although minimum flow rates were sufficient for a Kpath of 1.0, the system was unable to provide enough air during occupancy. This shows in the CO2 responses. It can be explained by first looking at a condition where all dampers are closed and secondly a condition where dampers are not closed. In the first case the fan delivers the minimum flow rate at 200 Pa pressure difference. The dampers are in their minimum positions (30% open). Then some dampers start to open, and as a result, the fan pressure difference drops. To compensate for the pressure drop, the fan increases speed to maintain the 200 Pa set point. The new flow rate is not sufficiently large to change the set point to a larger value (2880 m3/h). Thus, no changes in set point, even while the amount of air varied.

146 Energy Efficiency – The Innovative Ways for Smart Energy, the Future Towards Modern Utilities

and 18°C, dependent on outdoor temperature.

**5. Results and discussion** 

points on static pressure control.

between the usage of April and October.

rooms.

flow rate (to maintain IAQ at no occupant load).

in Fig. 8.

pressure set point (Kpath) was calculated from a minimum flow rate of 0.8 m3/s at design pressure difference, and from a minimum pressure difference of 200 Pa. These values were chosen from the fan characteristics. Hence, the steady state paths of control were as shown

Room CO2 set points were 700 ppm and supply air temperature was controlled between 15

**Figure 8.** Paths of the pressure difference set point of the fan as a function of the correction gain Kpath.

Considering the limited data sets that were simulated, making any generalizations based on the simulation results in this case study would seem ambitious. The results are nevertheless important and can provide the basis for a more general representation of using variable set

Simulations were performed for different values of the gain Kpath (0 to 1 with a step of 0.25). Three mean outdoor temperature levels were considered (-20, 0 and +20°C). Outdoor temperature varied as a ±4°C sinusoidal swing during a 24 hour period. Simulations included heat gain from solar radiation, and the simulated dates were in January, April, July and October. The energy consumption of 0°C outdoor conditions was determined as a mean

The two upper diagrams of Fig. 9 show the pressure difference set points (left) and ventilation flow rates (right) during a day for different values of Kpath. The remaining diagrams show how CO2 responses in each of the rooms became for different values of Kpath. • Minimum flow rates to the zones decreased with an increasing Kpath. However, due to a relatively wide minimum position on the dampers, all zones got a sufficient minimum

• For Kpath approximately equal to 0.75, the flow rates to room 3 and 4 were marginally insufficient. The CO2 level then rose slightly above the set point level (above the offset).

It was at this point the maximum energy savings for this system were obtained. • A Kpath value equal to or below approximately 0.70 provided proper CO2 control of all

**Figure 9.** Simulation results of the system with pressure difference reset. The two upper diagrams show the SP and flow rate during a day. The remaining diagrams show CO2 concentrations of the rooms.

In figure Fig. 10, the corresponding room temperature responses are shown for the different values of Kpath. The effects from solar radiation on rooms with windows orientated in different directions can be seen here. Rooms with windows facing east naturally got high solar radiation early in the day, while windows facing west got high radiation later in the day. As flow rates were decreased, temperatures of course increased. Consequently, while deciding on a value of Kpath, also thermal conditions should be assessed.

Energy Efficient Control of Fans in Ventilation Systems 149

**Figure 11.** Energy usage (%) as a function of Kpath and outdoor temperature (relative to a VAV system with Kpath =0). The left diagram shows total energy usage (local heaters and lights included), and the right diagram shows energy usage for the AHU only. Location was Narvik, Northern Norway.

Reducing the energy consumption of the AHU using variable set point for control of fan pressure difference is possible. This study has suggested reductions up to 40% for the air conditioning process, as a result of implementing a more efficient control procedure for the fans. The main criteria to achieve this, is to choose the optimum value of Kpath. Too low values will generate lower energy reductions. Too high values may lead to instability of the control loop, or no control at all. Influence on the results from other factors may also be important. The controller used for fan control is particularly important. Not so much which controller function that is addressed (P, PI or PID), but more how the controller parameters are determined. In this study, a PI controller was used on the fan, and parameters were determined from a modified Ziegler Nichols step response method. It was assumed that this gave fairly optimized control. It is likely that for larger ventilation systems using CO2 DCV (or other types of DCV), the maximum value of the correction factor Kpath (=0.7) will be lower than suggested in this case study, and other controller functions and parameters must

It is thus difficult to produce generalized numbers for Kpath. The allowable level of correction

Since the factor Kpath obviously depends on occupancy, its maximum value will vary with the various load patterns that occur in the rooms, improved result can be obtained by

• The measured CO2 concentrations (or any other control variables) in the rooms can be used as measures of inadequate control. A too large value of Kpath will lead to augmented CO2 levels above set point in the rooms. If levels are augmented, Kpath is

• If concentrations can be maintained at the set points, Kpath will be increased until

of the set point must be found and assessed for each individual case.

adjusting it automatically. This can be done as follows (also refer to Fig. 12):

**6. Conclusions** 

be used to achieve the best possible results.

simply decreased by a controller.

concentrations starts to rise above set point.

**Figure 10.** Room air temperatures during a day in July (+20°C outdoor temperature) in Narvik, Norway

Energy usage was compared to an identical VAV system with Kpath gain equal to zero. In Fig. 11, percentage energy usage is shown as a function of Kpath, for different outdoor temperatures. Energy usage was of course also affected by the degree of variation to the set point, i.e. the variation of Kpath. The results generally indicate that energy usage for the AHU (and for the complete building) can be reduced considerably by utilizing variable set point control of the fan. The lack of integral function of the local zone controllers showed as a positive offset (up to 40 ppm). To account for the offset and to provide the correct flow rate to the rooms (specified in terms of a set point), the integral term should be utilized also for local control. In the simulations, the offset during full loads caused the flow rate never to reach design conditions.

Another important factor is damper authority. Low authority means that the dampers must produce a relatively high pressure drop before noticeably affecting flow rate. The dampers must then alter positions quite a bit to obtain the required flow regulation. In some cases this can lead to poor control and risk of instability, and will also affect flow rates to other rooms. Pressure independent VAV boxes represent a more sophisticated alternative. Other rooms are not affected to the same degree as for pure damper control. However, even these will suffer if damper authority is low.

**Figure 11.** Energy usage (%) as a function of Kpath and outdoor temperature (relative to a VAV system with Kpath =0). The left diagram shows total energy usage (local heaters and lights included), and the right diagram shows energy usage for the AHU only. Location was Narvik, Northern Norway.

#### **6. Conclusions**

148 Energy Efficiency – The Innovative Ways for Smart Energy, the Future Towards Modern Utilities

deciding on a value of Kpath, also thermal conditions should be assessed.

In figure Fig. 10, the corresponding room temperature responses are shown for the different values of Kpath. The effects from solar radiation on rooms with windows orientated in different directions can be seen here. Rooms with windows facing east naturally got high solar radiation early in the day, while windows facing west got high radiation later in the day. As flow rates were decreased, temperatures of course increased. Consequently, while

**Figure 10.** Room air temperatures during a day in July (+20°C outdoor temperature) in Narvik, Norway

Energy usage was compared to an identical VAV system with Kpath gain equal to zero. In Fig. 11, percentage energy usage is shown as a function of Kpath, for different outdoor temperatures. Energy usage was of course also affected by the degree of variation to the set point, i.e. the variation of Kpath. The results generally indicate that energy usage for the AHU (and for the complete building) can be reduced considerably by utilizing variable set point control of the fan. The lack of integral function of the local zone controllers showed as a positive offset (up to 40 ppm). To account for the offset and to provide the correct flow rate to the rooms (specified in terms of a set point), the integral term should be utilized also for local control. In the simulations, the offset during full loads caused the flow rate never to reach design conditions. Another important factor is damper authority. Low authority means that the dampers must produce a relatively high pressure drop before noticeably affecting flow rate. The dampers must then alter positions quite a bit to obtain the required flow regulation. In some cases this can lead to poor control and risk of instability, and will also affect flow rates to other rooms. Pressure independent VAV boxes represent a more sophisticated alternative. Other rooms are not affected to the same degree as for pure damper control. However, even these

will suffer if damper authority is low.

Reducing the energy consumption of the AHU using variable set point for control of fan pressure difference is possible. This study has suggested reductions up to 40% for the air conditioning process, as a result of implementing a more efficient control procedure for the fans. The main criteria to achieve this, is to choose the optimum value of Kpath. Too low values will generate lower energy reductions. Too high values may lead to instability of the control loop, or no control at all. Influence on the results from other factors may also be important. The controller used for fan control is particularly important. Not so much which controller function that is addressed (P, PI or PID), but more how the controller parameters are determined. In this study, a PI controller was used on the fan, and parameters were determined from a modified Ziegler Nichols step response method. It was assumed that this gave fairly optimized control. It is likely that for larger ventilation systems using CO2 DCV (or other types of DCV), the maximum value of the correction factor Kpath (=0.7) will be lower than suggested in this case study, and other controller functions and parameters must be used to achieve the best possible results.

It is thus difficult to produce generalized numbers for Kpath. The allowable level of correction of the set point must be found and assessed for each individual case.

Since the factor Kpath obviously depends on occupancy, its maximum value will vary with the various load patterns that occur in the rooms, improved result can be obtained by adjusting it automatically. This can be done as follows (also refer to Fig. 12):


Most commercial controllers allow for programming and are thus able to incorporate the algorithm presented above without major implications.

**Chapter 7** 

© 2012 Šešlija et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2012 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

**Increasing the Energy Efficiency** 

Dragan Šešlija, Ivana Ignjatović and Slobodan Dudić

have to be undertaken in all branches of human enterprise.

recently placed on the energy efficient use of compressed air.

The increase of energy efficiency is a general trend in a worldwide relation. According to the Kyoto Protocol from 1997, the EU has to reduce greenhouse gas emission by 8% below the level from 1990 by the 2008 - 2012 period. To achieve these reductions, substantial efforts

One of the important industry utilities that has to be encompassed by this energy policy are compressed air systems (CASs). The application of compressed air has had a growing trend due to its easy and safe generation, manipulation, and usage. In previous years, the research efforts in this domain were concentrated on the CASs development and application aimed at boosting the productivity regardless of the energy consumption. With increased awareness of the energy costs as well as the effects of greenhouse gas emission, the attention has been

The experience gained in numerous CAS optimisation projects, as well as the opinions of the experts in the field, indicated that many industrial systems are missing the chance to improve energy savings with the relatively low costs of projects for increasing energy efficiency. Energy saving measures in CASs that have been identified in the course of energy audits in the small and medium industrial enterprises may yield an average energy saving of nearly 15%, with a payback of two years, the energy saving potential in some of them amounting from 30% up to even 60% (USDOE, 2001). The basis for all decisions concerning energy efficiency of the existing CASs is the understanding of the way of their functioning and existence of appropriate data. In that sense, it would be necessary to make measurements of consumed

electricity of compressors, airflow, system leakage and pressure drop in the system.

Besides energy savings, increasing energy efficiency of CASs may ensure other significant benefits for the enterprise. Energy saving measures imply a high monitoring level of CASs and

and reproduction in any medium, provided the original work is properly cited.

**in Compressed Air Systems** 

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/47873

**1. Introduction** 

**Figure 12.** Fan static pressure difference control system (supply side only). The CO2 concentrations of the zones (or exhaust) are used to determine the degree of set point variation (represented by Kpath).
