What role does measurement and verification (M&V) play?

Energy performance measurement and verification (M&V) at system level can be complex. The lack of suitable metrics to measure system efficiency is a major challenge. One solution could be to define outcome-based metrics, such as total energy use of a particular functional system (lighting, heating etc.) per unit area (kWh/m3) [ASE 2016, chapter 1.8].

With increased digitalisation, data gathering and aggregation has become more accessible. Easy-to-install, plug-and-play energy monitoring systems providing both real-time and historical energy consumption data have been introduced to the market in recent years. They collect electricity and gas consumption data down to appliance level, using clamps and submeters, and then send the data every 15 minutes to a processing unit which can be integrated into the device, or an external unit connected via the internet. The data come back in an aggregated format, which makes it straightforward to compare them with targets and predicted values. This evolution in energy monitoring technology has brought energy management within the reach of SMEs [ECI 2020].

Measurements play a crucial role both before and after putting the energy savings measures in place. There is a dilemma between seeking to improve system efficiency by intervening at the design level, with the high degree of uncertainty this entails for certain input values, or acting when the system is already in operation, but with a more limited potential for making changes [ASE 2016, chapter 1.3]. Monitoring and measuring are of great assistance in both cases. In the first case they are needed to verify the predictions made in the design phase and to improve the design of similar systems in the future. In the second case, they are needed to detect potential adjustments and improvement measures when the system is already in operation (e.g. in the set points of control systems).

Both goals can be achieved by using a digital twin, which is a digital replication of the physical system. It uses real-time measurement data from the physical world fed into a sophisticated digital model of the system.