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A predictive tool to optimise Firminy’s district heating network

The district heating network in Firminy (Loire) uses four different energy sources (cogeneration, biogas, biomass and natural gas), so there’s no room for guesswork in its management. To get the best out its performance, SDCF – the company that manages the network – uses the Blu.e digital platform.

“In our line of work, there’s no shortage of data available. The important thing, though, is knowing how to use it to boost performance.” Bernard Sayve is the technical manager of ENGIE Cofely’s heating networks and utility power plants in South-East France – and a past master in the art of juggling figures. The Firminy network’s figures are known: 13 kilometres, a total installed capacity of 57 MW, 156 substations, 59 GWh of hot water per year, or 6,000 housing-equivalents. The heat is supplied to the network by four different energy sources, which do not cost the same to operate and do not give the manager the same flexibility of operation. The heat produced by cogeneration is less expensive than that from biogas, while a gas boiler has less inertia than a biomass boiler.

 

Easier troubleshooting

To handle this complexity more effectively, SDCF uses the Blu.e digital platform. A hypervision room, connected to a network of sensors installed throughout the heating network, gives the operators live information about the sites’ energy performances. This constant monitoring makes it easier to spot problems as they occur and streamlines network maintenance.

“Through a central screen, our agents can easily keep an eye on all of the substations. If a warning light comes on for one of them, they know they have to go and inspect that particular substation.”

The supervisory team did special training to learn how to use the new tool on their own. In time, the field teams will even be able to suggest ways to make the platform better suited to their requirements.

cartography under firminy stations

 

Choosing the right energy mix

Another benefit blu.e brings SDCF is decision support. Using the data collected by the sensors and weather forecasts, the solution calculates the optimum operating scenarios for the next seven days. In other words, blu.e predicts what can be saved on costs, energy and emissions by activating or shutting down one or more of the network’s energy sources. It never takes over from the manager, though.

“There’s always a human in control. It’s a decision tool, not an automation system. Over and above the figures, we also need to take other factors into account, such as the time it takes teams to shut down a plant.”

Pending data on the initial impact of the blu.e solution on the Firminy network’s energy performance at the end of the 2016-2017 heating season, SDCF has already set itself target savings to achieve: 5 % on the biogas plant and 5 % on the wood-fuelled boilers. Knowing how to juggle figures can pay off.

 

   |  The figures

59 GWh  of hot water per year

6,000  housing-equivalents

5 %  savings to achieve on the biogas plant and the wood-fuelled boilers

 

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