A Simple Trial with the IEQ Concept

The purpose of the first trial that has been carried out with the IEQ parameter was to observe the difference in the IEQ value of an office building between two load reduction strategies. The first strategy is to use a single energy consumer for load reduction such as the HVAC system. The second strategy is to use both of the energy consumers; lighting and HVAC.

The trial was carried out for the same model office building located in Izmir. A very hot summer day for Izmir is simulated (Table 12. outlines the test parameters). First, the energy simulator is run for Izmir when the indoor operating setpoints are adjusted as optimum (lighting 600 lux and temperature 22.5° C). The resulting IEQ is then taken as reference. Next, the two load reduction strategies are tested. An arbitrary load reduction value of 25% was selected. In the HVAC only strategy, the HVAC system is adjusted to reduce consumption such that the resulting overall consumption was 75%. In the combined strategy, lighting system was set to 400 lux and the remaining load reduction was carried out by the HVAC system.

Table 12: Simulation parameters for DSR Trial

Parameter Value

City Izmir

Simulation Trial Day August 25

Average Outdoor Temperature During DSR Period 30

DSR Time 14.00 – 16.00

DSR Control Hvac only and HVAC/Lighting Combined

171 Figure 43 shows the results of the DSR simulator for the HVAC only scenario. In all of the graphs, red lines represent the case during the DSR scenario whereas blue lines represent business as usual scenario. The top left graph shows the indoor temperatures, top right graph shows lux levels, bottom left graph shows the power consumption and bottom right graph shows indoor IEQ. When the HVAC system is asked to reduce consumption, the indoor temperatures rise from their set-point values of 22.5° C to around 25.5° C. Because there is no change in lux levels, the resulting IEQ depends only on the temperature swings.

Figure 44 shows the case when both HVAC and lighting is used for load reduction. The average load reduction is equal to the previous case. However, because of the contribution of lighting, the average IEQ drop is much lower compared to the HVAC only scenario.

172 The results are summarised in Table 13. Indoor IEQ is around 1.4 percent higher when both HVAC and lighting is used to reduce power consumption compared to the case where only HVAC is used. Although the percentage value is small, it is significant because IEQ range is defined between 0.88 and 0.95 for the best and worst case indoor scenarios.

Table 13: Simulation results for DSR Trial

HVAC Only HVAC/Lighting Average Lux Level 600 lux 400 lux

Average Indoor Temperature 25.57° C 24.12° C

Average IEQ 0.910 0.923

Power Reduction %74 %74

173

4.7. Conclusion

The purpose of this chapter has been to establish a relationship between productivity of office workers and the office building. Because of the difficulties involved in including office appliances in a productivity function, the focus has been on environmental parameters. IEQ concept has been identified as the best solution to the problem of relating combined effects of individual environmental variables to human comfort and performance. It has been shown that IEQ equations that are derived by Wong and Ncube are developed to determine the acceptance of environmental conditions by the workers rather than a direct measure for performance. For this reason, these equations are compared with performance data obtained from literature review. Based on this study, Ncube et al.'s equation has been found to show better similarity hence this was selected as a productivity function.

The energy consumption model that has been explained in the previous chapter is modified to include IEQ as a DSR parameter. When a simple load reduction trial is carried out for a hot climate, it has been found that using only one parameter (temperature) as a basis for load reduction might not produce optimum IEQ (and productivity). For this reason, it can be concluded that a building automation system that needs to reduce power consumption for the purpose of DSR needs to be capable of using both the lighting and temperature as a parameter to maintain the maximum productivity in the office.

It should be reminded that the IEQ function tried in this chapter is far off from being a real productivity indicator. For this reason, it is not feasible to use this for calculating productivity loss as well as to evaluate the commercial value of using such a parameter.

174 The main usage of this indicator is to compare the environmental conditions in an office building during a DSR event and to ensure assess if more power could be shed in environmental conditions that have similar productivity indicators. In the next section, a control algorithm that can be used in an office environment for DSR purposes will be explained. This algorithm will then be tested using the building energy consumption model presented in Chapter 3.

175