In order to inform the Decarbonisation Options Assessment process, (the process of identifying and evaluating decarbonisation options that could be implemented to reduce energy demand, optimise energy efficiency, and/or deploy low and zero carbon technologies), the baseline energy/carbon performance of the building(s) should first be assessed and validated.
Setting a baseline year for energy /carbon performance gives a set point against which any change can be measured. For emissions reduction of an operational estate this must reflect the energy and associated emissions used within. Typically, a baseline year will cover a reporting period of 12 months, often either the calendar or fiscal year. It is also sensible to pick a year where there is relatively good data, both on the organisational estate and portfolio, and its energy consumption.
This performance information can firstly be used to support the selection of suitable building(s) for a Decarbonisation Options Assessment, and secondly, would be used to calculate the relative carbon savings potential of individual or aggregated carbon/energy reduction opportunities identified during a Decarbonisation Options Assessment.
To baseline the energy/carbon performance the following information should be obtained:
> Building Type/Use
> Building Floor Area
> Energy consumption data (kWh) for a representative (minimum) 12-month period, utilising half-hourly / smart meter data as a priority. Consumption data should be disaggregated for all energy types (e.g. electricity, natural gas, district heating, fuels, other). When determining the 12-month period, it is important to ensure that a representative 12 month-period is chosen, particularly with the impact of COVID-19, which could have resulted in abnormal energy consumption for some building types
> Renewables generation / onsite consumption for a (minimum) 12-month period
> Available information on patterns of energy use (e.g. building use, building occupancy)
> Energy Performance Certificates (EPCs)
Appendix 2 includes a Baseline Energy/Carbon Performance and Benchmarking template which can be used to record the baseline energy/carbon performance and the following information.
Under a typical PPP FM SLS, the FM services would generally include for monitoring and reporting of energy consumption records (incl. meter readings) and may additionally require specific monitoring reports to be produced as agreed between the Authority and Project Co. Therefore energy/carbon performance data should be readily available.
Energy data can vary in type and quality dependent on what is available. In all instances the best available data should be used. A guide to the order of energy data preference is as follows:
> Energy data through a half hourly meter - this could be through a fiscal meter or sub-meter
> Energy data through a manual meter read- this could be through a fiscal meter or sub-meter
> Energy data through an apportionment of the building area for use (for example where the building is partially occupied by the organisation)
> Applying similar energy performance of similar buildings where no data is available
> Using ratings from assessments such as an Energy Performance Certificate (EPC)
Energy data should be collected in consistent units, typically kWh, which may require some conversion for certain energy sources such as oil, LPG, or natural gas which can be recorded in volume. A useful conversion table is provided in Greenhouse gas reporting: conversion factors 2021 - GOV.UK (www.gov.uk) detailed reference contained within Appendix 4.
For the purposes of setting a baseline, only annual energy consumption is required. However, it is recommended that at least three years' worth of data is used particularly with the impact of COVID-19, which could have resulted in abnormal energy consumption for some building types, as this enables any anomalies to be identified. Data analysis should be completed to ensure that the three years' consumption data (ideally one either side of the baseline if possible) are similar. If there are any significant variations, then these should be investigated to ensure that a representative dataset is utilised for the baseline.