Data from the ExcEED platform: intelligence for better buildings

Sep. 20, 2019

Short story

Having comparable performance data coming from buildings that could be converted into information and useful knowledge would largely benefit key stakeholders of the building sector (building managers, designers and policy makers). The generated knowledge would improve existing and next generation buildings, thanks to the improved control, design and energy performance regulations generated.

The H2020 project ExcEED and its collaborative platform turn this into reality: as users add their buildings’ monitoring data, the intelligence embedded in the platform turns raw data into key performance indicators and geoclustered benchmarks, showing where to focus to improve the efficiency of buildings.

The key element of the platform is the user, through the data he or she provides to the platform, resulting in a more comprehensive analysis and benchmarking.

What kind of data is needed in ExcEED?  What are they needed for and how are they processed?

The data required to use the ExcEED platform

The unique selling point of the ExcEED platform lies in its combination of metadata and measured data, combined with complex KPI algorithms and geoclustering tool.

Metadata provide an overall description of the building for which monitoring data will be uploaded. They cover six categories:

  • General information over the building (height, heated surface, percentage of glazing…)
  • Heating and cooling system specification
  • Renewable energy system specification
  • Mechanical ventilation system specification
  • Lighting values
  • Environmental and energy performance certification

The measured data instead can be imported from a number of data sources including utility meters (usually provided by data collectors/aggregators), grid data (e.g. electricity market data from market operators), monitoring data stored in csv files.

When signing up to the ExcEED platform as a user, you first register your site(s), building(s) and devices, for which you will later manually input metadata and automatically upload monitoring data. You will get access to a user-friendly interface where your data can be uploaded with maximum safety. The user interface is divided in three sections:

  1. The dashboard homepage section that shows you general information
  2. The data section where data and metadata can be uploaded following the instructions
  3. The analytics section where data is handled, processed and analysed

The data interface architecture was designed to be extensible and flexible to accept new data requirements, technologies and functionalities. That is why the data management within the platform includes a basic data integrity check, synchronization and aggregation engines designed to process any kind of data, from electrical, gas and water readings to any numeric readings such as operations and environmental data.

What are the data needed for?

The uploaded data feed into our knowledge base and analytics tool, designed to support you in assessing the energy performance of you building portfolio against a wide set of key performance metrics.

You, as user, will interact with the knowledge base to:

  • Upload specific streams of time-series data (energy use, operations, environmental conditions, etc.);
  • Review the performance of your building through the set of Key Performance Indicators enabled by the data you have uploaded;
  • Run geo-clustering analysis on specific performance range you are interested in.

The breakdown analysis tool can be used to understand, extract, compare and visualize the monitoring data uploaded. The tool can be used to compare, for instance, simulated consumption for a certain building with the actual data collected. The breakdowns show your building’s energy use and associated cost, and benchmark it against the energy performance of similar buildings within the same climate zone, size, market or any other metric. You can calculate possible savings by discovering, increasing and decreasing trends over several time periods.

The operations analyser tool allows you to simulate behaviors by turning on and off the consumption in parts of the day. This way it is possible to estimate consumption and cost savings doing a what-if analysis. The tool is useful to quickly evaluate patterns of power consumption and when peak load happens. Through the platform, you are also able to set notifications and alerts in order to keep track of the consumption and cost.  After a few weeks learning phase, the tool will alert you in case of abnormal values, while you activate sentinel notifications for your meters. Alert notifications are useful to detect data disruption, incomplete reporting, suboptimal operation of devices.

The ExcEED platform as a milestone to achieve EU energy targets

Moving from traditional offline analysis against outdated datasets to online analysis against continuously updated datasets spanning over buildings from many EU member states, the ExcEED platform paves the way for next-generation building energy performance analysis.

The ExcEED knowledge base was designed around innovative ways to allow users to continuously profile their building estate with information ranging from energy measurements, energy efficient renovations to business metrics and other construction conditions. In such a context, the Knowledge Base of the ExcEED platform plays a central role in enabling the operation of advanced analysis processes that are key to the success of the EU member states in complying with energy conservation targets set from 2020 onwards.

Now it’s up to you to make the most of the ExcEED tool by uploading your data to the platform and start using the benchmarking and clustering tools available. Ready to take the challenge? Register to the platform and upload your buildings data for free.

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Read the report ‘A standard for uploading, storing and preserving data in the ExcEED database’

Read the report ‘Recommendation for a European standard for data in the field of engineering and construction’

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European UnionThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 723858. Disclaimer: The sole responsibility for the content of this material lies with the authors. It does not necessarily represent the views of the European Union, and neither EASME nor the European Commission are responsible for any use of this material.

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