Reducing energy consumption in buildings is of key significance in the current context of global warming. Big data is already playing an effective role in controlling energy expenditure and is set to revolutionize energy saving models. The sector, however, must control its own astronomical consumption to stay relevant in the race of energy saving.
For around ten years, home automation products have been enabling individuals and companies to take control of their homes and offices. Lighting, heating, opening: everything is programmed and controlled remotely. This is definitely a long-term trend. EDF launching its new subsidiary, Sowee (at the end of 2016) which is entirely dedicated to connected home services proves the same. This eponymous offering binds a mobile control station and an intelligent thermostat with a natural gas contract.
Here, big data helps in collecting, processing and gaining a perspective through the data then obtained. This allows retrospecting and comparing energy consumption with immediate neighbors and neighboring cities.
Start-ups and professionals working for energy efficiency offer different means of action to communities. For example, Intent coordinates with urban and construction stakeholders to share their data and develop predictive maintenance applications. Deepki offers real estate managers tools for tracking energy performance.
Big data and connected objects will help implement two structural innovations that will further control energy expenditure when using smart grids. The first one is distributed load shedding which is controlled interruption of electric supply to a large number of consumers. “This may concern heating or air-conditioning units which will be interrupted for a period long enough to re-balance the electric supply and demand but at the same time, short enough to cause any discomfort to users,” Energie 3.0 tells us. The second innovation is decentralized peer-to-peer networks, which avoids loss of energy while transmitting it from building to building.
However, the green revolution promised by big data must also go through an improvement in the practices of the sector itself. Behind the billions of data produced each day, there are energy-consuming farm servers. In the end of 2016, a study by ENR’CERT showed that the average consumption per square meter of a data center was nearly 37 times than that of a house. Their earlier article talked about high energy consumption due to air conditioning (necessary for cooling the servers) and how it’s important to save cost by making use of the waste heat. Simple but ingenious solutions have already been devised. For instance, the swimming pool at la Butte-aux-Cailles (in Paris) gets heat from the servers installed in its basement!
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