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A local flexibility market is being tested on Rome’s electricity grid

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A local flexibility market is being tested on Rome’s electricity grid

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In the RomeFlex project, the city’s electrical infrastructure is being prepared for the growing energy needs, with the cooperation of Siemens.


The peak demand of Rome’s electricity supply network is expected to increase from 2,200 MW to 3,300 MW in the next ten years. The Italian capital is not alone in this challenge: due to increasing energy demands and changing consumer habits, it is increasingly necessary to expand the capacity of electricity networks worldwide and in Hungary as well.

The Roman distribution network operator (Distribution System Operator / DSO) For this reason, the Areti company is also planning to speed up digitization in order to replace costly and time-consuming hardware infrastructure investments and make its network more intelligent, thus more resilient and future-proof, in a software way. Therefore, and in order to be able to expand its capacities without power outages and voltage fluctuations, Areti has developed a framework for flexibility services, which are now being tested in conjunction with Siemens technology within the framework of the RomeFlex sample program.

Starting this February, users connected to the medium and low voltage networks managed by Rome’s DSO (such as university campuses) will be able to participate in a local flexibility electricity management market using intelligent solutions. Users operating as prosumers (producer-consumer) can thus trade on a “demand-response basis” with the energy available to them or produced from renewable sources.

During the process, which requires a higher level of network management than before, Siemens software is used to test the bottlenecks of the city’s electrical infrastructure, as well as its ability to manage voltage fluctuations. Building on this information and applying Siemens’ digital twin technology, the increasingly complex network structure will be more manageable with the help of simulations, and possible problems and failures can be predicted.

Based on the data collected during the sample program and the algorithm-based operating experience, the network operator will be able to make more cost-effective decisions for its future developments. And the authorities responsible for city management and the energy market regulators will receive more detailed information for planning further investments, as well as for the development of a national flexibility regulation.

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