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22 Jan 2021

Going real-time with grid management

Going real-time with grid management
Image credit: Fraunhofer IEE

The EU-SysFlex Project, a EU funded Horizon 2020 initiative, consists of eight European demonstration projects addressing the provision of flexibility between different voltage levels. New algorithms and tools developed in the German demonstrator of the EU-SysFlex Project have opened the way for real-time coordination of flexibility to manage intermittent renewable energy resources on the grid.

The key players in the development of the algorithms are the Fraunhofer Institute for Energy Economics and Energy System Technology (IEE), and the University of Kassel (e2n).

The algorithms developed will coordinate the utilisation of active and reactive power flexibility, which can be provided to the distribution system operator (DSO), and from the DSO to the transmission system operator (TSO). Such coordination and optimisation between the DSO and TSO is crucial for the security and cost-effective operation of a grid with a high penetration of renewable energy resources.

In Germany, the share of renewable energy in total electrical consumption is nearing 50%, and since 2017 has been around 100% in the project demonstration region, part of the supply area of MITNETZ STROM, the local DSO. The upshot of this has been the implementation of substantial re-dispatch measures to avoid overloading and voltage violations on the transmission and distribution grids. However, the re-dispatch potential in the transmission grid is limited due to the decreasing capacity of conventional power plants.

The re-dispatch potential can be increased by utilising renewable energy resources in the distribution grid. To avoid TSOs adopting congestion solutions that conflict with those put in place by the DSOs, a coordination mechanism is needed. The optimisation algorithms of the German demonstration, led by MITNETZ STROM and E.ON (a German energy company) follows earlier projects (“IMOWEN” for the core optimization algorithm and “SysDL 2.0” for the demonstrator infrastructure) which both ran from 2014 to 2018.

The current project is focused on expanding and hardening the algorithms for real-time operation and making them more resilient to errors, as well as undertaking a live field test. The EU-SysFlex demonstrator furthermore combines reactive and active power flexibility optimisation and provision.

The ‘magic’ of grid optimisation takes place in the penultimate step, where the grid layout uses either actual measurement data or forecast data. In particular, the active and reactive power flows have to be accurately estimated in order to obtain realistic  flexibility. The core of the optimisation itself is based on an interior point algorithm.

The main challenge of using  algorithms in grid operations is the high level of complexity and high requirement regarding availability and reliability, with the need for fast and efficient handling to meet a real-time, online application.

Furthermore, various technical, economic and regulatory constraints and requirements need to be taken into account in the computations.

In cycles of 15 minutes, all the requirements of the DSO and TSO which concern the technical behaviour of grid assets, such as P and Q (active and reactive power) capability curves or droop control behaviour, need to be met. This means that individual computations need to be much faster, on the sub-minute scale, and some need to be triggered spontaneously by the user.

For the grid connection point level and asset level, the P and Q flexibilities are computed in an optimisation module using nonlinear mathematical optimisation  algorithms. Flexibilities are calculated via two individual optimisations, i.e., a maximum as well as minimum active power capability. Internally in the optimisation module, algorithms adjust the mathematical model based on the actual grid state.

The process starts with the integration of external data, including topological grid data, asset data, grid measurement data and forecast data up to 48 hours ahead. All of these data points are converted to a harmonised internal format using communication interfaces and conversion tools.

Current and forecast grid states are then computed based on the current and forecast generation and consumption data. For current grid states, state estimation techniques are applied by a state estimation module.

For all grid states, (n-0) and (n-1) congestion analyses are applied. 

In case of congestion, appropriate measures are determined according to the current regulatory framework and new P and Q schedules for generation are provided by a  congestion management module.

Finally, clustering of the generating assets with respect to sensitivity on grid connection point, cost and type is applied and the flexibility is prepared and provided from DSO to TSO via a communication interface.

Contrary to the current approach where the TSOs often solve grid problems without considering the requirements in the distribution grid, the German demonstrator is shown to enable more reliable and efficient operation of both grids. This goal was addressed by generating suitable congestion-free P and Q flexibility from the control centre optimisation tool and offering them to the TSO.


The project partners say that one of the main challenges was to meet the real-time capability of the system starting with the processing of data and performing all necessary optimisations for the current moment and for 48 hours ahead on a 15-minute cycle. Other challenges include missing or incorrect data and validation of each step to move to the next one.

The partners say the outstanding character of these newly developed tools and optimisation algorithms is their robustness and applicability in a real-time operational  environment. In the German demonstrator, they manage more than one hundred wind and solar PV generators with a combined installed capacity of about 5GW across four large regions of MITNETZ STROM grids.

In order to provide useful active power flexibility to the TSO, each generator has to be considered individually in terms of costs and sensitivity to the grid connection points and a combined PQ  optimisation approach is necessary to ensure that active power requests from the TSO do not cause any grid constraint violations within the distribution grid.

The field test is set to take place in 2021, having been delayed by the COVID-19 pandemic.

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