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Ingelectus successfully completes the development of the innovative low voltage digital twin for flexibility services “DT4Flex”.

Ingelectus has completed the second and last phase of the DT4Flex project carried out with the companies Cuerva, Bamboo Energy and Smart City Cluster. The DT4Flex is an important step in grid management technology as it is a low voltage digital twin that consists of a tool capable of predicting short-term events and assessing the availability of flexibility services to solve derived problems, thus maximizing the safe penetration of new agents.

During the year of work of the second active phase of the project, the tool has been optimized to incorporate the resolution of new problems, such as neutral conductor congestion through the activation of flexibility resources. In addition, a load prediction and generation module has been developed at user level using different artificial intelligence techniques that allow the tool to anticipate future incidents.

Rubén Carmona, responsible for the project, said that “DT4Flex has been used to address many important challenges, including digital twins that faithfully represent the behavior of low voltage, the design of the communication architecture between agents of the local flexibility markets, the extension of CIM models for distribution flexibility, as well as the processing of Cuerva’s network data to develop a PoC”.

The operation of DT4Flex has been validated on the low voltage networks of several Transformer Substations within Cuerva’s living lab, using real data from the advanced low voltage supervision and smart meters located there. It should be noted that current and future scenarios have been taken into account for the tests, so that the capacities have been estimated based on different realistic and possible characteristics of both resources and scenarios.

Results

During the execution of this project, several important technological challenges have arisen that Ingelectus has been able to solve, in addition to answering questions about how the distribution, location and typology of the low voltage flexibility resources should be, or what photovoltaic penetration capacity these networks can accommodate. The results obtained are very satisfactory:

  • Increased level of low voltage network observability, both from the point of view of the operating status and the influence of nodes and connections on each other.
  • Improvement of the accuracy of the electrical knowledge of the network behavior.
  • Formulation of a linear and deterministic optimization problem with reduced convergence times and based on network physics.
  • Implementation of deep learning techniques on a necessary problem for distributors, such as predicting the future behavior of their networks.
  • Evolution of the tool to an architecture based on microservices that allows its deployment and scalability in any environment.
  • Design of a methodology that takes into account the electrical impact of flexibility to identify areas of influence where it is more advantageous to locate flexibility resources.
  • Development of an extension of the tool that allows calculating the photovoltaic hosting capacity of low voltage grids.
  • Inclusion of economic criteria for the cost of activating flexibility services so that the solution is not only optimal from a technical point of view but also the most cost-effective option.

The validation of the DT4Flex tool in a relevant environment such as Cuerva’s living lab has opened up its capacity for application in any computing environment, without forgetting to highlight that “knowing the possibilities offered by the flexibility service providers and simulating the requirements that will be demanded of them to participate in network management are aspects that will make it easier for distributors to effectively manage future prospects”, said Rubén Carmona. 

In the same line of results, DT4Flex will allow distribution system operators to execute with accuracy by ensuring that this participation of flexibility resources in network management will be done under equal conditions and that the results provided by the tool will respond only to technical and economic optimization criteria. These results confirm that investment in network digitization is something that distributors must take into account when moving forward and competing in the market.

 

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