Produced in Association with


SERIES 22 / Module 02 Measurement & Verification


where the purpose is to calculate the energy consumption that would have occurred without the implementation of the measures. The baseline should account for factors such as weather variations, production levels (in industrial settings), occupancy patterns, and any other relevant variables. The plan should be agreed between all


relevant parties – the end-user, supplier and independent M&V advisor where they are used – and completed prior to any energy efficiency or decarbonisation works commencing. Implementation of energy effi ciency


measures: Energy efficiency measures are implemented according to the project design. The M&V plan should specify 'Operational Verification' (OV) activities relevant to testing of EEMs as they are first installed to ensure they are commissioned effectively and performing their intended function(s). OV serves as a low cost initial step for assessing savings potential, and mitigates the risk of installation defects not being identified until further down the line when the full verification process commences. Depending on the nature and


complexity of the measures being implemented, the implementation phase, or 'construction' period, may take several weeks or months. Savings reporting: After the energy efficiency measures are in place, data on energy consumption or performance is collected according to the M&V plan. The M&V plan will have set out the required processes and in general will require the post-project data to be compared to the baseline to determine the actual energy savings achieved. The requirements of the specific


project should be clear from the Savings Report – for example, for a guaranteed savings project, was the guarantee met? And if not, what is the reconciliation process, noting that this should be set out within the contractual documentation, if not the M&V plan itself.


IPMVP M&V approaches IPMVP sets out four M&V options that can be applied depending on the requirements of a specific project. For example, requirements include the nature of the EEMs, the value of the energy savings and ongoing maintenance responsibilities for the EEMs. The list is not exhaustive, and consideration should be given to ensure the approach is suitable – for a given EEM, more than one approach may be possible. In setting out the different options,


metering of its kWh consumption. An advantage of this approach is


that energy savings can be isolated from other changes outside of the measurement boundary, but it is likely that new metering is required, and sufficient time to allow a full range of operating conditions must be captured. Option C: Whole facility


measurement This approach uses the whole-building energy data to determine savings, which is often captured via the electricity and gas data from fiscal meters. It is worth noting that if any on- site generation is already in place, this should also be included in calculating total building consumption. This approach will result in the


A clamp meter used to take wattage readings of light fittings


IPMVP considers the measurement boundary. For a facility or building in general there are two broad measurement boundaries, either the whole site, or isolated loads within the site, such as lighting, motors, or cooling loads. IPMVP further breaks these down,


with Option A and Option B describing isolated measurement boundaries and Option C and Option D describing whole facility measurement boundaries (although technically Option D could also be applied at a submeter level). Option A: Retrofi t isolation, key


parameter(s) Measurement of energy is derived from the measurement of one or more key parameters, and estimation of the others. To illustrate this, take the common application of Option A for lighting retrofit projects – often the lighting load is measured before and after the retrofit and operating hours estimated. So measured lighting load (kW) is the key parameter and hours of operation (h) the estimated parameter. The difference in lighting load before and after the EEM can be multiplied by the estimated operating hours to provide a saving in kWh terms. The estimated parameter will introduce


some uncertainty, so it is important that all parties agree on any estimates. But for


the lighting example, the measurement focuses on what a supplier is responsible for (reduction of lighting load) and not a parameter outside of their control (the end-user’s operations). An advantage of this approach is that


it is relatively low cost, quick to obtain the required measurements, and savings are not impacted by changes outside of the measurement boundary. Option B: Retrofi t isolation with all


parameter measurement Option B focuses on an isolated measurement boundary, similar to Option A, but is required to measure all relevant parameters within the boundary of the EEMs. This option can be applied where the EEM can be isolated and equipment impacted has a variable load such that baseline energy consumption within the measurement boundary is variable. The measurement will likely require


the installation of a submeter if there isn’t one already in place, and to record data for long enough to capture a full cycle of operating conditions for the isolated load. Typical applications would include


EEMs applied to cooling/ventilation systems, drives and controls, where the savings achieved are likely to vary over time according to variable demand, but where the load itself can be isolated via


measurement of the combined impact of all EEMs deployed within a building, which may be useful if there are interactions between the different measures, or if some are not possible to isolate. It will, however, capture any changes within the facility that are not part of the project being measured. This may require careful monitoring if any such changes are likely to be material, as it could lead to challenges in disaggregating the impact of the facility changes from the impact of energy efficiency measures, which is especially important where performance guarantees are involved. Under Option C, mathematical models


of consumption data are often developed, typically using regression analysis to account for variables such as external temperature or building occupancy. This results in an ‘adjusted’ baseline such as the one illustrated in the graph on page 23, calculated for a facility’s utility electricity data, which can then be extended over the reporting period. Typically, a whole facility approach is


used where savings are expected to be material (>10% of total building consumption) and where ongoing performance measurement is important. An advantage of the approach is that historic utility energy data is usually readily available for most non-domestic buildings in the UK. Option D: Calibrated simulation


Where no baseline data exists, energy simulation software can be used to predict building consumption. Models will capture the physics and information about the energy systems in the measurement boundary (which although typically applied at a whole facility level under Option D, could also be applied to a sub-set of building consumption). Engineering calculations use these details to predict consumption, which is


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EIBI | JULY � AUGUST 2024


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