Wind power has an excellent ability and capacity to contribute with rapid frequency control to the grid. The project ´The potential and cost of wind power to provide system services to the grid’, co-financed by Energimyndigheten and Vindforsk, has focused on possible and cost-efficient contribution from wind power to the system service Fast Frequency Reserve (FFR). That is, to maintain a power reserve to be able to rapidly (within 0.7 seconds) support the grid, if the frequency drops below a certain level (around 49.7 Hz).

Within the project RISE has modelled a generic and public land-based wind turbine of 3.4 MW and 130 metres diameter. A wind-power curve has been generated, based on the optimal rotor speed, through aero-elastic simulations. The corresponding maximal energy production has then been calculated. This is how wind turbines normally operates today.

By modifying the turbine control by increasing the rotor speed for winds below rated wind, the somewhat lower production has been calculated. However, the advantage of the higher rotor speed is the power reserve by the turbine inertia. This reserve can rapidly be transformed into extra grid power, if the frequency for some reason rapidly should decrease. As a third step, different levels of additional Fast Frequency Reserve have been added to analyse the behaviour of the turbine and the ability to handle the transient.

As an example: For wind speeds of 4 m/s the optimal rotor speed is 5 rpm. If running at 7 rpm instead, the power can be increased by 500 kW within less than 1 second. This higher power can remain under 5 seconds to counteract the decrease in frequency. During this time period, other, more inert counteractions can be activated, and the wind generator can slowly revert into optimal production at 5 rpm.

In total 11 880 simulations have been executed, with different combinations of mean wind speed, location, rotor speed concept and added extra power. The results show that by increasing the rotor speed at wind speeds between 3 and 9 m/s, an extra rotational inertia is generated which can be used to instantly increase the power output and counteract a drop in frequency in the grid. After the power increase, the rotor speed decreases to the optimal speed again and the turbine can revert in optimal aerodynamic conditions.

European Network of Transmission System Operators for Electricity (ENTSO-E) has defined a worst-case scenario which implies a momentary loss of 1450 MW. To be able to handle this drop, a FFR of about 280 MW needs to be added within 0.7 seconds to ensure that the frequency will not drop below 49 Hz. Frequencies lower than this hazard a total collapse of the grid.

Having the generic wind turbine of 3.4 MW as a starting point, 1400 of those are needed to produce 17.8 GWh annually (which was the yearly production in Sweden 2017, consisting of 4500 wind turbines whereof the most of them were smaller in size). By order these units interact, a mean value of 200 kW of power reserve is sufficient to handle the worst-case scenario (1400 x 200 kW = 280 MW). A minor number of the turbines are not in operation at all, others are operating above rated wind; these units are not contributing to the power reserve in the study. However, half of the total number of generators are operating at low wind speeds and then generating above 400 kW of FFR. By adding up all units, the worst-case scenario will therefore always be managed.

Except for a small decrease in production, the problem is that a coordinated and active control of the wind turbines is needed. This will probably be a future requirement for connecting additional wind power to the grid. The calculations show that the decrease in production will remain on approximately 1% for the 280 MW power reserve. On a national level this would imply that wind power production would decrease from 17.8 GWh per year to 17.6 GWh. If an even larger amount of wind power would contribute, the loss of production would be even smaller.

In the future each wind turbine will probably be connected by internet directly to the market. The turbine control will adjust the rotor speed depending on the demand and compensation for energy production and power reserve respectively. In case of low energy market price and high FFR-compensation the rotor speed will increase. In case of high energy price and low FFR-compensation the rotor speed will decrease and be closer to the optimal rotational speed.

This is a likely and resource efficient solution for a robust grid dominated by wind power.

ANM4L aims at demonstrating how innovative active network management (ANM) solutions can increase the integration of renewable energy sources (RES) in electricity distribution networks.

ANM solutions will consider both management of active and reactive power to avoid overload situations, maintain voltages within limits, minimize the need of RES curtailment, and enable further RES uptake even when the theoretical design limit of the network has been reached.

Core research and development activities are the development of:

• Active network management methods for local energy systems.
• Business models to provide decision support for market players.
• An integrated toolbox to support the planning and operation of the distribution system, considering the developed ANM methods and business models.

The toolbox, methods and business models for ANM will be demonstrated in Sweden and Hungary. The project will also prepare solutions and recommendations for replication in other local and regional energy systems.

This project has received funding in the framework of the joint programming initiative ERA-Net Smart Energy Systems’ focus initiative Integrated, Regional Energy Systems, with support from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 775970.