NEW CHALLENGES IN ELECTRICAL SYSTEMS

Electricity has become an important, if not vital, commodity. The transition towards a low-carbon economy depends on it. But electrical systems must now address new challenges: the decentralisation of production and integration of renewable energy sources, along with the advent of ”smart grids” and the rise of new applications such as electric vehicles.

This issue concerns two categories of service:

• The smoothing of electricity production over time, so as to respond at all times to demand without having to activate costly, state-of-the-art production facilities, or to store excess production during periods of lower consumption, generally from renewable energy sources.
• The smoothing of production in space to avoid having to transport electricity on the grid to cover geographical mismatches between the place of production and place of consumption.

AN AID TO PLANNING LOW-VOLTAGE DISTRIBUTION NETWORKS

Finding the right balance for good performance of the electrical grid therefore requires a decision-making and planning aid able to predict the impact that distributed energy resources (DERs), such as photovoltaics, cogeneration or electric vehicles, will have on low-voltage networks.

This is where ”machine learning” software applications come in – such as the one developed in the Utilit-e project – which are able to continuously learn from the data provided by smart meters and thus refine their modelling so as to more accurately reflect reality.

By using mathematical machine learning methods and real data, the Utilit-e software allows Distribution System Operators (DSOs) to optimise very unbalanced low-voltage networks with a significant portion of renewable energy.
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UTILIT-E IN PRACTICAL TERMS

The traditional methods still used today by DSOs are based on data (cable lengths and cross-sections, meter outlets and phase connection types) which can be sources of error.

As it is based on real data from smart meters, Utilit-e’s digital model of a low-voltage electricity network is therefore more accurate than traditional methods.

This offers practical advantages for DSOs:

• By offering simple, cost-effective solutions to rebalance the network (by simply changing the phase of one or more meters), spending on network reinforcement is greatly reduced, by up to €10k per kilometre of digital cable.
• Optimisation of photovoltaic capacity: production can thus be doubled without reinforcement.
• The investment payback period is therefore less than two years, and highly qualified staff can concentrate on added value for the customer.

AN INNOVATION WITH A STRING OF SUCCESSES

In March 2018, Utilit-e was certified by Tenerrdis, providing a form of recognition for the innovative solution and its potential, and strengthening the company’s reputation.

In 2018, Utilit-e was a winner of the French ADEME’s i-Nov competition within the Investments for the Future Programme (IFP). The competition aims to support innovative projects by start-ups and SMEs, and to encourage rapid emergence of leading companies in their areas – such as Odit-e – with potentially global reach.

In December 2020, Bertrand Piccard’s Solar Impulse Foundation awarded its Label to the Utilit-e software, including it on the list of 1,000 innovative solutions helping to protect the environment. International recognition!

IN THE WORDS OF THE PROJECT LEADER: