Section 10. Energy Sources
This section is based on data from the Estates Management Record (EMR) 2015/16, which is made publicly available online by the Higher Education Statistics Agency, HESA.
This section accounts for 8% of the total.
The scores for section 10 are weighted as follows:
|Whether a university has onsite Combined Heat and Power (CHP)||45%||Taken from
|Percentage of renewable energy generated onsite or off site compared to consumption of grid electricity.||35%||This calculation is
|Total percentage of renewable energy purchased through green tariffs||20%||Taken from (
As in previous years, universities will be scored by banding values into groups.
HESA now provides strict rules for data submission around nulls and zero. Universities are instructed to use null when they do not have the data, and are alerted to the fact that this will mean totals are not calculated by HESA.
People & Planet has interpreted nulls from the viewpoint that scores can only be awarded through transparency. So, for instance if a university submitted a null value for how much onsite CHP they have, we will assume zero and score accordingly. Likewise if a null is returned for percentage renewable energy, it is assumed zero.
Ambiguity regarding renewable energy data
In 2014, an ambiguity in the HESA EMR data came to light when considering data regarding renewable electricity bought through green tariffs. It meant that universities with high percentages of green electricity weren’t necessarily getting full credit for criterion 11.3.
EMR field EPREPGTT “Total percentage of renewable energy purchased through green tariffs” (definition) had been interpreted differently by different institutions: some interpreted it as a percentage of green to total electricity; others interpreted it as a percentage of green electricity to total energy consumption. Therefore some universities that use 100% green electricity have submitted much smaller values, e.g. 30%, because they’ve used energy as the denominator.
People & Planet contacted HESA about the issue as soon as it was recognised in 2014 and we hope that guidance or a more strict vetting process takes place in each future dataset, meaning we do not find the same incomparable data in this years EMR. Please contact us if you believe you have entered your data incorrectly in this field for the 2015/16 EMR dataset.