After WorksStrategic Asset

Monitoring

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Monitoring it’s a key topic to understand whether a building is working properly and users behave in the correct way. In order to have some inputs about this topic a lecture from Passive House institute was presented in Darmstadt.

The main questions are: which factors we have to measure to compare calculated data with real building? How to match measured data with real data?

To know if the user behavior in correct, you have to ask directly to the users. That is what Passive House Institute did with two buildings in Darmstadt. They measured and analyzed the data of energy consumption over three years, then asked to people if they’re satisfied, 90% are satisfied and 50% are very satisfied. Survey will be done again in two years. A minimum percentage of unsatisfied people is considered acceptable and inevitable.

When planning a monitoring there are two extreme options: minimal monitoring VS scientific monitoring. You should decide according to what is needed and which are the limitations.

It’ easier to have data on final energy side and is more difficult to have it at the useful energy level. The measurement is done on heat generation, on storage that have some losses and on distribution with losses. If the losses are few the measurement data can be used.

Minimum measurements technology required is manual reading of general meters (heat supply, thermal solar supply, power consumption, water consumption…), minimum 1 per year, best every month.

If you have a gas meter and a heat meter after the boiler you can calculate the efficiency of the boiler. You can add single meter on single flats, so you can know the system losses.

If you need a very detailed monitoring, you can have a single circuit.

In case the heat generator is a heat pump it’s important to know also the cold source temperature.

In efficient building is important to monitor electrical energy consumption, because there are more electrical consumption than heating.

Which are the influencing factors in monitoring?

  • Thermal quality building
  • User behavior (people, clothing, activity)
  • Weather condition
  • Function building services

The calculation according to the building codes algorithms are not suitable for comparison with consumption numbers, they are not accurate enough. Demand is different between consumption, to design you should make a calculation more connected with reality (e.g. Passive House Planning Package).

The deviation from law to reality (at least in Germany) is mainly in overestimation of internal gains. With PHPP they measured heating consumption very accurately, with energy losses and gains (solar gains, internal heat gains…).

In high performing buildings there are big difference due to indoor temperature. Typically internal temperature is about 21.5°C (according to past monitoring).

Ventilation can change heating demand; in passive house an air change rate from 0.2 to 0.5 can be a quite big difference (1.5 kWh/m2y).

Summing all the possible influences can up to double the consumption, in theory, but they are not present at the same time.

For hot water there is a big data fluctuation. In single house it’s difficult to predict the user behavior, in many apartment instead it can work because you can do statistics and so you can refer to average values.

At least control should be done permanently (minimum one annual date required). Deviation can be clarified by more accurate monitoring.

Rebound effect and saving potential

In passive houses the user behavior can influence the consumption very much.

In insulated building people use to have higher temperature inside; anyway in high performance houses, even if people don’t behave correctly, the extra consumption is not very high in absolute value, better than in renovated houses (not passive).

Some examples

The measurement of 32 flats in Hannover (passive houses) shows that some need more heating, some need less, statistics show a typical standard deviation (1,2 kWh7m2y). The average value fits the PHPP calculation.

Measurement accuracy is not better than +/- 3 KWh/m2y.

PADIHAM AND TREVISO DREEAM PROJECT PILOT SITE MONITORING

In these projects SinCeO2, partner of DREEAM Project, use an innovative methodology to calculate energy saved.

First of all they find the key performance index of the buildings. This means facing with a big amount of data, that should be collected (276 gas bills for dwelling). Another problem is that many little actions of each tenant has an influence on the global energy consumption (e.g. number of people living in each house, hours that they spend at home, habits of use).

They installed different meters in each house and connected them with the cloud. They collected data before and after renovation.

They calculated the energy consumption with real degree days so using the real internal and external temperature. With this approach the data fits much better the real consumption than calculating it with theoretical degree days. It fits even better if data about user behavior is included.

The new consumption of each dwelling was obtained and the energy generated by solar panels was measured to determinate not only the savings derived from improvements that affect consumption, but the saving derived from self-consumption.

During the monitoring is fundamental to know all the boundary conditions, for example how many hours people stay at home. If boundary conditions change model must be adapted to understand the real energy consumption. In Treviso was done a program in DEXCELL program to know exactly how many people stay in the home.

Places for people, owner of the 109 properties in Padiham, selected 9 household to be monitored. The monitoring continued also during the works, so it could be possible to see differences as each part of the renovation was completed. They monitored internal and external temperature, humidity, kWh consumption.

The challenges of this monitoring approach were:

  • Recurring connectivity issues
  • Tenant engagement
  • Location of site
  • Staff resources
  • Staff knowledge

After this monitoring period they understand that a careful costumer selection is a key starting point and is also important to work closely with contractor. Ensuring kit works correctly on site will aid tenant engagement and management of monitoring project. A good partner for communication and support it is very important.

During the meeting in Treviso 2019, Ing. Fontela from Exeleria shows the application of software and the decision support system to identify the best and cost-effective renovation scenarios for the Dreeam pilot sites.

They created a building portfolio, where buildings are pre-selected according to some archetypes. The archetypes are defined according to the building typology, age, energy performance indicator, component make-up, U-value and occupancy level or usage profile. U-values are one of the key inputs to accurately develop the energy analysis, but in most of the case they are unknown, so field measurements are needed. Also ventilation rates are often unknown, because closely linked to user behavior, so assumption must to be made in the energy calculations. Real consumption data is not available, because energy bills are private issues.

Some one site measurements have been done in the pilot sites to assess the U value, also thermographic analysis and system analysis have been done in place.

They did an inventory database for four countries across EU identifying the potential interventions and the building information. Into the Dreeam tool they implemented a building model that provides different combination of options, providing thousand of potential solutions. Then they combined also information about the preferred options by the owner and local legal requirements.

During the analysis they learn that each country provides different level of detail in terms of input data and prices can vary quite a lot in different country. Sometimes manual input and assumptions are needed for complex active solutions.

The tool was tested compared with the CARRIER tool to check the difference. Difference is less than 3%, so the accuracy is guarantee.

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