Benchmarking Research Paper

Determination of electricity benchmark

Benchmarking is a process which helps in comparing the energy performance of building with similar type of building. It is one of the best method to determine whether a school is using energy efficiently and to compare its energy consumption with that of other schools.

6.1 Features and benefits of benchmarking:

The benchmarking helps the owner of the building to determine how well each building of the school is performing. It also shows the worst and best energy users of similar buildings revealing that which school building saves most of the energy.

Benchmarking provides representative values against which one can compare the energy performance of school. comparison with benchmark of annual energy consumption

Energy intensity indicators has been established i.e. energy consumption per square meter and energy consumption per student. From the different schools, worst energy performance schools should be analyzed as that of benchmark set for the school and an action should be taken to make them energy efficient.

From the model developed in SPSS software as discussed in previous chapter, EUIobs is converted into EUI std. Now from the EUIstd three parameters mean, mode, median which could be used for establishing the electricity benchmark for schools.

6.3 Determining the measure of central tendency for EUIstd data distribution

There are three main parameters which could be used as measures of central tendency for a data distribution. These are mean, median and mode. It is required to determine which of these three measures represents the central location of a data distribution. Before these three measures, i.e. mean, median and mode are discussed, it is important to understand the significance of the following three factors which play a significant role in the selection of an appropriate measure of central tendency.

a) Normal distribution

b)

The first step of calculating the mode of the grouped data is to locate the group or class where the mode is located with the maximum frequency and then applying correlation formula to calculate the mode. The class interval corresponding to maximum frequency is called modal group. According to frequency distribution characteristics of EUIstd as shown in table 7, the modal class of EUIstd is 0-5 kWh/m² as this class has the maximum frequency i.e. 198.

The mode of the grouped data may be calculated by using the following formula as shown by the equation.

Estimated Mode = L+ ((fm-fm-1))/((fm-fm-1)+(fm-fm+1)) x W Eq. (7) where: L is the lower class boundary of the modal group fm-1 is the frequency of the group before the modal group fm is the frequency of the modal group fm+1 is the frequency of the group after the modal group w is the group width Putting the values of L, fm, fm-1, w in above equation we get,

Therefore, 10 kWh/m², is the mode of the dataset of EUIobs that has been calculated from excel and could be now compared with the mean and median to identify the most appropriate measure.

6.6