How To Move Towards Automated Measurement & Verification (M&V)

Measurement and Verification (M&V) is the term given to the process of quantifying the energy surplus delivered by a specific load management measure. M&V is typically used to verify that programs and systems actually work as anticipated during operation, which is critical when payments are directly linked to the energy surplus created.

This post reviews the evolution and challenges M&V faces with modern energy management programmes, for which the nature and scale of resources calls for (semi-)automated system of measuring and verifying energy surplus.


M&V is currently used by any organisation that needs to prove the achievement of demand reduction in utility resources, such as energy and water:

    • Energy Service Companies (ESCos) and energy professionals use M&V for Energy Performance Contracts (EPC) whereby they implement energy efficiency improvements and guarantee the energy savings, and for Energy Performance Related Payments (EPRP), where a portion of the consultants fee is contingent on a verified improvement in energy performance. If the savings fall short, they cover the difference or get paid less.


    • LEED consultants use M&V for extra Leadership in Energy and Environmental Design (LEED) credits, where they verify that the building continues to work to its potential for at least a given period. The U.S. Green Building Council has yet revamped the M&V credit for LEED for New Construction v4, considering the complexity and costs associated to delivering full M&V reports. Projects can now achieve credits for installing advanced metering for major end-use loads, which is the mandatory first step to any analysis.


    • Demand Response aggregators for settlement with end-users, meaning determination of the demand reductions achieved by individual program or market participants, and of the corresponding financial payments or penalties owed to or from each participant [1].

    • Energy retailers for complying to legal obligation on EU member states to achieve new energy savings year on year from 1 January 2014 to 31 December 2020 of 1.5% of the annual energy sales to final customers of all energy distributors and all retail energy sales companies by volume, averaged over the most recent three-year period prior to 1 January 2013. In Ireland, obligated parties under the EEOS are energy distributors and retail energy sales companies that have market sales in Ireland of greater than 600 GWh final sales in any relevant year, regardless of the sector they supply [2]. For this, the EU Energy Efficiency Directive (2012) calls for “measurement, control and verification systems to be used to verify savings by obligated parties”. Obligated parties can choose to achieve energy savings independently or through partnerships with service providers in the market, where white certificates or energy carbon credits can be traded against verified savings.


  • .. and any load management programme where a party earns revenues based on the power/energy surplus created or reductions in Greenhouse Gas Emissions.




Cities have evolved to become smart urban developments where information and communication technology have enabled availability of such assets for effective management of production, distribution and consumption of energy. As such, the nature and range of resources available for load management programs has expanded greatly.

Modern load management programs are getting more and more complex, focusing on a larger customer base and targeting all kind of resources, as opposed to more straightforward on/off programs limited to industrial customers.

While such an expansion opens the door for better management of energy throughout via innovative load management programs, it introduces some major challenges in terms of M&V. Comprehensive submetering/sensing is not cost-effective for small installations, and end-users are not necessarily energy experts and won’t be able to monitor and rectify deviations as they occur. Without M&V, the impact of individual actions cannot be validated creating conflicts between parties regarding payments.

Another issue with current M&V procedures is that M&V is very often one snapshot in time, where the manual effort of measuring the reduction/surplus achieved cannot be continuous and repeated frequently. As such, energy surplus levels achieved are not maintained and long-term savings are unknown.




Automating the process of measuring and verifying the energy surplus achieved by a specific load management measures must involve three major steps:

  • Automated capture of the baseline (the reference energy use before the load management event)
  • Automated calculation of the energy surplus (the results achieved after load management event)
  • Automated detection of deviations (the guarantee that long-term results are maintained)


Automated Capture of the baseline

System configuration
A (semi-) automated M&V system must have some level of configuration as to what events are being implemented, so that the correct data sets and algorithms are applied for measuring the impact of each event. This list includes:

  • Types of events (on/off, equipment retrofitting, awareness campaign, gaming, etc)
  • Event’s typical baseline period
  • Data available for M&V (Utility meter interval kWh data, powermeter demand and kWh data, environmental data from sensors, online data, work schedules, etc)

Such information allows the M&V system to tackle the problem with the most appropriate way of determining savings (e.g. Option A, B, C or D for the IPMVP). In general, the system will try to establish a regression model or Proxy/Average day to compare the post-event measurements to.

System operation
During system operation, the following stages must happen to guarantee that the load management event triggers the M&V process:

  • Identification of events
  • Selection of baseline period
  • Production of similar-day forecast or regression model using combinations of routines variables and static factors known

Automated calculation of the energy surplus

The calculation consists of subtracting the real measurements from the energy that would have been consumed had the load management event never occurred. The latter is automatically computed by the M&V system using the forecast/models computed in the previous step, and helps evaluate the energy surplus achieved.

Automated detection of deviations

For many load management programs, ensuring that the energy surplus (or savings in that case) are maintained over time is mandatory. Without someone to regularly monitor and make sense out of the measurements, this calls for the (semi-) automated M&V system to embed analytics that will:

  • Identify abnormalities/deviations as they occur
  • Notify/recommend end-users with action plan to fix problems detected

The concept here is to automate the task of the energy consultants and get the system to learn whether a measurement is inline with the expected pattern and whether deviations have occurred that require attention. This is illustrated below, where having no advanced analytics prevents the system to report on successful compliance to expected pattern.

In a second example, the M&V system being adapted with advanced analytics has some context to identify whether the measurements match the expected pattern, and notifications can emerge from that analysis to assist end-users in rectifying anomalies.


The Wattics M&V tool powered by Sentinel analytics has been designed along the mechanisms pictured above. The tool streamlines the M&V process for energy efficiency projects in 10 steps aligned on IPMVP, and is mostly used by ESCos and other energy professionals for their energy efficiency projects. Baseline/reporting periods as well routine/non-routine adjustments can be quickly set, and regression model and savings are automatically computed, as well as the final M&V report which is distributed to interested parties. The Wattics Sentinel Analytics engine then runs in the background to ensure that the modified consumption pattern become the reference one and are maintained long after the load management event.



STEP 1: Define your Energy Conservation Project

Project Definition

STEP 2: Specify the Energy Conservation Measures Implemented


STEP 3: Set your Baseline Period


STEP 4: Set your Reporting Period

Reporting Period

STEP 5: Include Routine Adjustments

Routine Adjustments

STEP 6: Include Non-Routine Adjustments

Routine Adjustments

STEP 7: Select the best Energy Model generated



STEP 8: Visualise the kWh and € Savings Achieved


STEP 9: Write up your Executive Summary


STEP 10: Export your M&V Report



A semi-automated M&V system based on regression analysis has been implemented by Wattics for all types of energy, and is commercially available as part of Wattics SaaS energy management platform. A fully automated M&V system based on proxy/average day is also being piloted as part of two European Projects where Wattics is involved:

  • VIMSEN EU FP7 project (Demand Response for small prosumers)
  • CHARGED EU H2020 project (Gamified energy management within public buildings)

There exist major challenges in regards to access to real-time data, which prevents M&V systems from running continuously during and after load management events. There is hope that the Internet of Energy things is the answer to such a challenge, and that the combination of web-enabled energy things with advanced demand-side analytics tools will enable widespread application of automated M&V.

Pushing the M&V process to software systems enforces transparency in the results achieved by any load management program, and is a potential resolution to ongoing disputes where calculations from end-customer, energy professional, aggregators and grid operator may differ. Making that process automated goes one step further to tackle the increasing complexity of modern load management programmes.

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