A new approach

 

There is an increasing need to redefine the real estate market. Real estate, as the words describe, has the characteristics as a fixed ‘estate’. And although there is more emphasizes on the flexibility and total life cycle, the focus is mostly limited to the building itself, rather than it’s operation.

 

 

Buildings provide in essence a service to their end users, this means that after the building is complete (stacking the bricks) additional involvement by providing services gives new business perspective. We as, VolkerWessels iCity see a change in the market in which building investor are demanding such a Building as a Service approach.

 

 

Building investors have a long term perspective, around 20-30 years, in which the requirements of the user can change or even a whole new target group appears. Smart buildings have the opportunity to serve (changing) specific needs of end users instead of a generic “stacking of bricks” approach with a one size fits all model. Therefore it’s necessary to think about potential use cases in relation to a variety of persona’s. In our perspective we see an important shift from static product driven development to dynamic service driven real estate development. Data is a fundamental aspect to make this change possible.

 

 

Data is valuable

 

 

Buildings have the potential to generate much data. Although we see a tremendous increase in the application of technology, smart buildings are not common yet. There’s a huge potential for ‘data owners’ to use this data for a much more intelligent use of the building. Therefore data from the building installations, sensors, actuators and devices are valuable sources. In addition, open data, such as weather data, traffic data, demographic data and economic data give a broader view on the correlation of the data. But we have to be very cautious about how the data is processed and for what purpose. We’re an advocate of user sovereignty, in which the user governs its own data.

 

Data on itself does not provide real relevant insights, mostly, but by interpreting the data we generate valuable information. This means that next to collecting the data, an engine is necessary for the interpretation and secondly a (graphical) user interface to make information visible. When combining different sources of data we can look for correlations in the data. This would help to distinguish the cause and effect of events. But even a next step can be of significant value: machine learning and artificial intelligence (AI). The use of algorithms makes it possible to apply continuous interpretation on the data sets and let the system execute changes in setpoints or controlling installations. All this data gives information on the performance of the building and integrates the specific conditions of the building. This comes in handy when proofing certain critical performance indicators, as we see in sustainability labels (BREAAM, LEED) and indoor climate and wellbeing requirements (WELL).

 

In the traditional design phase assumptions based on averages are used about the expected performance. With these new combined sets of information, we can evaluate and adjust these assumptions based on facts and correlate to be able to continuously improve our design process.

 

Also, the processed information is valuable for different stakeholders of a certain building. We can distinguish in general the following direct stakeholders: building investor (financial and performance), building/maintenance manager (performance of systems), facility manager (services), and end users (work / live in the building).

 

The building investors can be the owner of the building and renting/leasing it to a (group of) user(s) with a (mainly) financial incentive and relevant data, or in some cases, the user of a building is also the owner and additional operational improvement can become more relevant. When managing a portfolio of buildings, an aggregation of data from different buildings can be used for cross-case analysis, and learnings from this can be adapted by the organization to improve their asset management. In most cases, a building manager / maintenance manager is hired for operational management. In Smart building, it will be possible to create a specific long term (predictive) maintenance schedule and continuous monitoring of parameters. This will also help the facility manager (mostly in commercial buildings) to increase their service quality. Defects and failures can be solved quickly and even preventive actions will help to lower the overall complaints from users of the building. As buildings become more intelligent, it opens the door for external interaction; to the energy grid connection. And that’s where InterConnect comes in.

InterConnect makes it possible

 

 

Smart buildings have an important role in the digitalization of the energy sector. Looking at the energy transition, a large amount of energy is consumed in buildings and the connected infrastructures such as charging stations for electrical vehicles. When we want to increase the use of renewable energy sources, like sun and wind.  We have to become more flexible in our energy consumption. Energy production and energy consumption fluctuate, every minute of the day, every day of the week and during the year;  to match this energy demand and supply financial energy trading markets exist.[1]

 

 

When we are able to better forecast and shift energy consumption of a building, we can align supply and demand of energy more effectively. But maybe even more important might be (data needs to demonstrate this) the ability to store energy in a building by thermal load or directly in a battery. And when using a backup battery for extra capacity during peak moments, it is possible to lower the grid connection. This sounds straightforward, but in practice it is complicated. A big variety of appliances, installations and devices have to communicate to one other; the magic of interoperability, and new  algorithms should be made to (better) forecast energy production and consumption and energy management systems need to be able to schedule and control devices and appliances.

This creates a new market for all kind of services offered by companies who create smart solutions to achieve peak shaving or peak shifting, both for the end user (company / person who pays the electricity bill) and for the DSO (Distribution Service Operator). And because every smart building or home has its own specific conditions, which can be made explicit by use of the data, service providers can offer specific services to their specific customer segment. And that’s were we see a great opportunity in the development of smart buildings: a digital marketplace.

 

 

For smartphones we are so familiar with an app store (digital marketplace) where we can find a variety of apps that make use of the technology of our phone. But in buildings we can’t really customize the services to our needs. Imagine that we can easily add or remove services to our buildings or home that not only save money and energy (not always the same) but also increase the quality of our indoor environment, our health and safety . This opens a whole new world of possibilities and meanwhile having a positive contributions to our sustainability goals!

Customer is key

 

 

The changing needs of the users (influenced by amongst others economic and health conditions) makes it more relevant to think of services, by “connecting bits” of which we can learn and adjust instead of only thinking of making a building by stacking bricks.

 

 

This new approach will lead to many new insights and challenges. We look forward to overcome these challenges together!

 

 

[1] In the Netherlands still many people think that during the day there is only one peak and one off-peak tariff, so awareness needs to be created, that during the day cause of fluctuations prices change per day, hour and even (15) minute(s).

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