Energy saving is certainly everyone's goal now. The price of electricity will multiply, inflation will tighten and next winter will be historically painful for property owners. There is also a desire to break away from Russian fossil energy. But how to achieve new significant savings when many energy efficiency improvement measures have already been taken over the years, which have corrected the biggest energy problems. Answer: you have to look for several smaller streams of savings - many small streams together add up to a significant savings.
The share of electricity and heat in the property's maintenance costs is significant, i.e. 30-40%. The aim is to keep the conditions of the properties within certain reference values and, at best, also taking into account its actual use. It is precisely in this area that savings can be obtained by utilizing data when control is carried out more precisely. Simply put: adapt energy-consuming functions more precisely to the real use of the property.
More energy-efficient property management with the analytics from several data streams
Outside temperature is an obvious factor to consider, as are wind and sunlight. The utilization rates of the facilities at different times indicate the need to create good conditions. Good operating conditions consist of indoor temperature, air freshness, humidity and cleanliness. All of these can be measured directly and, in addition, indirect data streams can be utilized. For example, the utilization rate can be deduced with reasonable accuracy from the data of the lighting system. The conditions do not have to be at the same level when there is no use, for example the temperature can be raised or lowered depending on the use. By combining several data streams, analytics can be created that can be utilized in a completely new way in property management.
In practice, price spikes caused by energy demand can be prepared for, for example, by heating a little more in advance and reducing energy consumption when general demand is high. This is called demand responce.
Optimizing energy usage – more savings and more responsibility on climate
With the help of the solution developed by Finnish Eeneman and German artificial intelligence solution Unetiq, energy can be saved by 10-15%. In this solution, Platform of Trust collects the data needed for optimization. The solution learns about the operation of the property and continuously improves its accuracy. Demand response can also be linked to this, in which case the property is heated when the most renewable electricity production is available on the market. Optimizing energy use can be seen in wallets as well as in responsibility for the climate.
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