STEAG New Energies (SNE) holds up to 51 percent shares in a total of 15 wind farms in Germany (7) and France (8). Two wind farms in Poland are wholly owned by the STEAG subsidiary. The entire wind farm portfolio with 228 MW installed capacity comprises 89 plants that are all centrally monitored from the Saarbrücken headquarter in Germany via an online information system. As coordinator in the SNE division Plant Operation Wind Energy and Special Plants, Daniel Schwarz leads a team with five experts being responsible for technical operation management.
“The main factor for the economic success of the wind energy plants is for them is to ensure high availability and long service life“, says Schwarz. However, in spite of tried and tested strategies for optimization and operation management, the processes undergo creeping changes, and faults become increasingly difficult to be detected by conventinal control system. This results in malfunctions or even total failures, in the worst case in times of peak generation. To minimize such problems, SNE is now going to rely on a software solution by the affiliate company STEAG Energy Services (SES). “We have placed an order with SES to implement the IT solution SR::SPC at all wind farms technically operated by ourselves to begin with. Going forward, we will use the software to monitor and optimize 53 wind energy plants with an installed capacity of 128 MW“, says Daniel Schwarz. Besides the biggest German site in Ullersdorf, these are the French wind farms Guégon, Lanouée, La Madeleine, Onze Muids, Quesnoy 1, and Woelfling.
In the STEAG group, decades of experience in the construction and operation of conventional power plants have led to the development of powerful IT technologies for application in the energy industry. Now renewable power plants of SNE benefit from these intelligent technologies and the huge amount of data accumulated over the years by STEAG’s control systems as well. The SES system for predictive analytics uses so-called neural networks that are modeled on the human nervous system. “On the basis of sensor-based data, the software models the reference condition of a plant and compares it with the actual condition. If there are deviations from previously defined performance indicators, changes and faults can be detected early on“, explains Peter Karl Krüger, head of the division System Technologies at SES. However, this technology is not just an early warning system, but it is mainly used to optimize plants’ modes of operation and to decrease maintenance costs.
“Since 2016, we have been testing SR::SPC in a pilot project in Ullersdorf. The test results have entirely convinced us of the benefit and the performance ability of the system“, says Daniel Schwarz. Currently he and his staff are still fine-tuning the technical infrastructure of the 53 wind energy plants before the software is to be implemented later this month. “SES is training our staff for the application. Moreover, they perform software and hardware maintenance and provide support”, adds Schwarz.