Know what you’re measuring: monitoring for optimal insight
To guide companies through the energy transition, it is important to have up-to-date insights into energy flows. This is necessary in order to predict future flows and make meaningful network adjustments. Determining when to plan expansion or ‘inspansion’ is critical for efficient, cost-effective, and sustainable deployment. Both the quality and quantity of data are essential here. Using the right data also makes it possible to identify problems in time, before production outages occur.
Determining exactly what should be measured is, therefore, essential:
- Are power or energy consumption being measured?
- For what purposes are we measuring?
Not unimportantly, from the very first steps, ICT should also be taken into consideration. Is a (reliable) data connection in place? Who should have access to the data? In what way is access granted? Electricity consumption can, in certain cases, be considered sensitive business data. Another often forgotten step: thinking about management and organizational aspects: who will be responsible for the data? What will that person do with it?
More than connecting metering devices and collecting data
A choice also needs to be made between measuring energy and power exclusively, or also monitoring Power Quality. The advantage of Power Quality monitoring is to safeguard business processes when installations change. If Power Quality monitoring is included, it is very important to interpret data correctly. The question can be asked: who within the company has the knowledge to understand this data?
Performing measurements in an electrical installation involves more than connecting metering devices and collecting data. You need to know what you are measuring and interpret data correctly. It is also important to determine what you will not be measuring – and what impact that will have. It is also essential to verify that measurement devices are properly connected and that any deviations in the installation will not distort the results. Installations tend to have a long history and documentation can leave a great deal to be desired. In fact, poor documentation can often cause problems. Because you can only work on aspects such as load balancing, nesting or optimization when you know all your data is in order.
Smart metering in practice at Sligro Food Group
Some time ago, Sligro Food Group installed metering equipment to map the consumption of its own facilities. This Dutch listed company supplies over 75,000 food and non-food items to consumers, food retailers, hospitality operators, institutional customers and other large-scale users. The measurement results were remarkable: solar panels appeared to be consuming energy, while heat pumps seemed to be generating power. “We were keen to identify the possible causes of this unexpected data and to have the measurement results validated. We also wanted to ensure that such anomalies would be prevented in the future,” said Mark Stabel, technical buyer electrical engineering, Sligro Food Group.
HyTEPS, as an independent party, checked and validated all measurements, uncovered historical errors in the installation and provided internal training. The outcome? Due to inconsistencies in the installation meant the overall picture contained errors – despite the fact that the installers had perfectly connected everything by the book. What had gone wrong? Every installation has its own history, which is not always documented. If an installer goes bankrupt, for instance, it is questionable whether documentation can still be traced. You must then rely solely on what you find on site and, above all, never assume that a certain color always represents a certain phase, for example. It only takes one cable swap or use of the wrong color to introduce confusion. It is crucial that the entire installation is unambiguous, as switched cables can cause the current of the phases not to add up. Checking everything also means you know precisely what you are actually measuring.
Often, equipment is delivered with no commissioning support and no quality control. Technicians connect everything according to the manual, but with no explanation of what to look out for. Then, if something has been reversed somewhere in the wiring, or the network documentation is not in order, measurement results end up being unusable. To find out exactly what you don’t know requires significant knowledge of statistics. If measurements indicate strange phenomena such as very high reactive power, you might quickly assume there’s a PQ issue. But it could also be the case that the measurements are the result of an error in the installation! In such a case, you need to be able to make the right connections and that requires building up experience. Based on our knowledge, we gave Sligro’s installers customized training on common errors and discussed what to look out for.
If power is measured with 1% deviation and one kW is measured, the uncertainty is 10W. This is negligible for a power measurement. However, if an energy measurement is done using the same data, the measurement error may deviate 0.01kWh every hour. There are 8760 hours in a year, so the measurement error per year could be 87.6 kWh – while measurements only show a 1kW load with 1% deviation.
HyTEPS has ensured that it is now possible to work with validated measurement data. Installers recognize the importance of bringing equipment to validate or asking another party to take care of validation. This was a unique project for HyTEPS because it went beyond purely technical analysis, in which measurements are taken, problems detected, and a solution implemented. In this case, there was also a focus on processes in the field and on training. Installers who do an excellent job of realizing connections and carrying out measurements have started to look differently at connecting and measuring in the context of a large installation, with the realization that you can’t always be sure whether documentation and previous connections are in order.
“For Sligro Food Group this is the first step towards a fully electric truck fleet, the measurement data will eventually drive the full load management of the truck fleet via an API link.” – Mark Stabel, Electrical Engineering Technical Buyer, Sligro Food Group.
Three main causes of measurement uncertainty
Common measurement errors
In the example below, cable colors have been swapped, while maintaining rotating field.
In this example, the current transformers have been placed the wrong way around.