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Digital Ants as an Efficient Means of Improving Power Grids

The energy transition changes everything. The on-going expansion of renewable energy sources makes grid planning increasingly complex. IAV has developed a method for automatic planning of distribution grids with a clearly structured comparison of different expansion scenarios.

The energy transition is changing many aspects of Germany’s power industry. Increasing numbers of local energy producers are feeding their fluctuating yield into the grids that have not been suitably prepared for this hitherto. This means that the grid operators have to invest in their existing infrastructure to bring it in line with the new challenges. The existing grid has to be made fit for the future with minimum investments in copper infrastructure and intelligent systems.

This is a typical optimization task and one that is also commonplace in automotive engineering. In recent years, IAV has used numerous optimization methods to handle complex issues with many parameters and is now in a position to transfer the resulting know-how to other industries. Power grid planning is one of these new areas that involves a particularly high level of complexity. “We’re dealing with hundreds or thousands of grid nodes, as well as a comprehensive set of rules regarding structure topology”, explains Dr. Michael Schollmeyer, Smart Grid Team Manager at IAV. “For example, certain electrical limit values have to be respected in order to prevent damage to the equipment that could cause power failures.”

Avoiding misdirected investments and using synergies

When it comes to strategic grid planning, such as connecting both new wind turbines and new industrial estates to the grid, there are simply so many possible solutions that the grid operators can no longer cope without suitable tools. However, the high level of complexity in strategic target grid planning is simply not a problem for the IAV solution. “Our highly automated method autonomously devises and analyses thousands of different grid variants, helping distribution grid operators to avoid reactive grid planning, preventing misdirected investments and making specific use of synergies”, summarizes Lukas Ruck, project manager at IAV.

The core element of the process consists of a variation on the ant colony optimization algorithm often used to devise efficient dot-to-dot connections for distribution tasks in logistics. Ants foraging for food act as the role model as they search for the shortest possible connection between their anthill and a source of food. But IAV’s engineers have made considerable additions to the traditional ant colony optimization algorithm to take account of the complexity involved in power distribution grids, as otherwise it could only plan ring and string lines.

Strommasten und Windräder unterstützen das Stromnetz.

In the IAV solution, the electrical attributes of the grid plan are imported and supplemented with geoinformation for every node point. “For example, the grid operator can stipulate the permissible length of rings and branch lines or the maximum number of local grid stations per ring”, says Schollmeyer. “Furthermore, our process is capable of modeling substations, transformer stations and sectioning points. It can also model string lines to a string or ring starting from the substation or transformer station.”

Every iteration supplies an improved grid

Once all necessary information is available, the algorithm proceeds with iterative generation of multiple possible solutions for efficient connection of the individual points. In this case, “efficient” means a grid with lowest possible investment and operating costs that still fulfills all load flow and short-circuit requirements. A learning algorithm ensures that the resulting grid structures get better with every iteration. The result is an efficient grid with minimum overall costs that fulfills all demands in terms of high supply quality. “Our optimization process makes no concessions in terms of reliability or safety while achieving the required supply quality in all grid situations with less investment”, says Ruck.

IAV offers strategic grid planning as a service. The algorithm has already proven its practical suitability in cooperation projects with several distribution grid operators. It was used in one of the projects to reduce the length of the power circuits in an existing grid to allow for specific reductions in high-maintenance overhead power lines. At the same time, two new industrial estates were to be integrated in the target grid that should have a clearly manageable structure. IAV’s target grid solved this task in less time at around 20% less investment costs than the manually planned grid produced by the project partner.

The project showed that the experience and technical expertise of the distribution grid operator can be well combined with the solutions proposed by the algorithm, resulting in numerous possible options for devising the target grid and its precise details in terms of routing, sectioning points and other important parameters which could then be discussed.


The article was published in automotion 02/2019, the automotive engineering magazine of IAV. Here you can order the automotion free of charge.