Acting on plant planning to reduce the energy bill

2023-08-24 09:30:27

The start-up Highcast has developed software that calculates the energy cost of each decision made on how to drive production systems in factories. It makes it possible to act on the planning in order to reduce the electricity bill as well as the associated CO2 emissions. Meeting with the co-founders of this company.

Vivien Robert and Flore de Lasteyrie both hold a master’s degree in Data Science from CentraleSup√©lec. In a context of a changing electricity market, they identified that certain industrial sectors were not using all the data from their factories to reduce their energy bills, which have been rising steadily in recent months, as well as to limit their environmental impact. They have developed software that analyzes plant data and calculates the energy cost of each decision made on how to drive production systems. Two years ago, they created the company Highcast, which was notably selected to be a member of the Start-Up Club of the FIM (Federation of Mechanical Industries). Interview with the two founders of Highcast, respectively CEO and CTO of this company.

Engineering Techniques: What is the new context facing manufacturers in terms of electricity?

Vivien Robert, co-founder and CEO of Highcast. Credit: Highcast

Vivien Robert: Their bill has increased a lot in recent months, and those who consume a lot of electricity, who are called electro-intensive, must find solutions to reduce it. Manufacturers are faced with a rapidly changing energy market and have to deal with large fluctuations in the price of electricity. These fluctuations are linked to the arrival of renewable energies (solar and wind), which are by nature intermittent, and which make the network more difficult to balance. Since electricity suppliers find it difficult to offer contracts at a fixed and affordable price to manufacturers, they often offer them a contract at a variable price, so that they bear part of the risk. The price of electricity then varies hour by hour, and can even become negative, when there is little demand and a lot of electricity production. In this case, manufacturers are paid to consume energy. Conversely, when there is a lot of demand and little production, the price of electricity becomes very high.

Faced with this new context, what solutions do you offer manufacturers?

Flore de Lasteyrie, co-founder and CTO of Highcast. Credit: Highcast

Flore de Lasteyrie: Today, there is a lot of energy efficiency software, which allows machine data to be analyzed to try to optimize their consumption. We are at a higher level, focusing on plant planning, especially during production and maintenance periods, which directly influence electricity consumption. Faced with the strong fluctuation in the price of electricity, manufacturers have an interest in changing the way they conduct their production systems, also including energy consumption, and no longer just variables such as the rate of return.

We have developed software that collects production data from factories and analyzes it using machine learning algorithms to understand the consequences of planning choices on electricity consumption. In parallel, our software models the specific data of the energy supplier’s contract and also makes electricity price forecasts thanks to market information. In the end, we are able to calculate the electrical cost of plant planning choices. These consumption forecasts are very reliable and produced hour by hour, on a horizon ranging from one day to several weeks in advance. Thus, when a plant carries out production planning scenarios, it can know what the consumption profile and the energy cost of its decisions will be.

Can you give us examples of applications?

Flore de Lasteyrie: When we intervene in a factory, our objective initially is to seek quick victories, that is to say to make changes that will not upset the established order, but that will have a strong impact in terms of reducing the bill. This allows us to build trust in our solution with manufacturers and to prove to them its relevance for integrating energy costs into planning choices.

For example, a foundry launches about forty fusions every day to heat metal, and each of them lasts about twenty minutes. The moment they are triggered causes significant power demand peaks, and this will determine the consumption profile of the plant. Thanks to the data analyzed by our software, we can delay these fusion launches from a few minutes to a few tens of minutes, without this changing anything in production planning, but while reducing the energy bill.

Another example is the stationery sector, which uses very energy-intensive machines. Just one of them can consume the equivalent of a quarter of a city like Metz. When these machines stop, as is the case during maintenance operations, this has a considerable impact on the network. By analyzing the data of a factory, we noticed that there was a certain flexibility on the schedule of these maintenances, and that they could be shifted easily by a few hours, without major consequences on the internal organization of the company, but while having a strong impact on the energy cost.

What are the gains made as a result of your intervention?

Vivien Robert: On average, the energy bill is reduced by 5 to 10%, or even more in sectors subject to strong fluctuations in energy consumption, such as foundries. In high-consumption factories, our solution can represent several million savings each year.

Then, we also help factories consume greener energy, promoting consumption when the energy is mainly solar, wind or nuclear, because that is when it is the cheapest.

Our intervention also makes it possible to reduce the pressure on the network managed by RTE (Electricity Transport Network) and ultimately to promote the greenest possible French energy mix. It should indeed be known that in the event of tension in France, polluting power stations with gas or coal are lit.

Finally, we can help electricity suppliers to adjust their supply and demand, by sending them electricity consumption forecasts every day at the hourly grid. They are very interested in these forecasts, because it allows them to anticipate the future consumption of their customer portfolio. Industrialists also benefit from this, since it gives them access to preferential electricity price conditions.

Where are you in developing your business?

Vivien Robert: We are working with the first customers in the foundry and papermaking sector, with whom we are testing our software. The market is changing significantly, which means that we have a lot of requests at the moment. We address all the companies which have a significant cost of electricity in their expenses, and where it is relevant to intervene on the planning. This concerns, among others, the sectors of metallurgy in the broad sense, paper and cardboard, cement and glass. The advantage of our solution is that it represents a limited investment for companies and that it is quick to implement, with results that can be significant in terms of reducing the electricity bill.

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