Up until now, experts at Swissgrid have calculated the anticipated transfer losses on the basis of calendar days, weather forecasts, and grid operator plans in neighboring countries. The new algorithm developed by Siemens researchers derives the projected transfer losses directly from electricity consumption forecasts. Along with data from the past, the system also uses variables such as current load flows, power generation figures for renewable sources, weather data, and water levels in pumped-storage hydroelectric power stations.
The error rate for consumption forecasts at Swissgrid now stands at 11 percent; the new algorithm will improve this figure by one percentage point, which translates into savings of approximately 200,000 euros per year.
Siemens' forecasting method is based on an artificial neural network - software that functions in a manner similar to the human brain. Siemens CT develops neural networks in order to calculate the behavior of highly complex systems, which might include wind farms, gas turbines, or even stock markets.
Based on historical data, the software learns to make the most accurate predictions possible. The system's learning capability makes it particularly suitable for adjusting grid operation to the fluctuating power outputs associated with renewable energy sources. The most efficient use of existing power networks is a building block of the energy revolution.
Dr. Norbert Aschenbrenner | Siemens InnovationNews
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TU Graz researchers show that enzyme function inhibits battery ageing
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Astronomers from Bonn and Tautenburg in Thuringia (Germany) used the 100-m radio telescope at Effelsberg to observe several galaxy clusters. At the edges of these large accumulations of dark matter, stellar systems (galaxies), hot gas, and charged particles, they found magnetic fields that are exceptionally ordered over distances of many million light years. This makes them the most extended magnetic fields in the universe known so far.
The results will be published on March 22 in the journal „Astronomy & Astrophysics“.
Galaxy clusters are the largest gravitationally bound structures in the universe. With a typical extent of about 10 million light years, i.e. 100 times the...
Researchers at the Goethe University Frankfurt, together with partners from the University of Tübingen in Germany and Queen Mary University as well as Francis Crick Institute from London (UK) have developed a novel technology to decipher the secret ubiquitin code.
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In the eternal search for next generation high-efficiency solar cells and LEDs, scientists at Los Alamos National Laboratory and their partners are creating...
Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are less stable. Now researchers at the Technical University of Munich (TUM) have, for the first time ever, produced a composite material combining silicon nanosheets and a polymer that is both UV-resistant and easy to process. This brings the scientists a significant step closer to industrial applications like flexible displays and photosensors.
Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are...
Enzymes behave differently in a test tube compared with the molecular scrum of a living cell. Chemists from the University of Basel have now been able to simulate these confined natural conditions in artificial vesicles for the first time. As reported in the academic journal Small, the results are offering better insight into the development of nanoreactors and artificial organelles.
Enzymes behave differently in a test tube compared with the molecular scrum of a living cell. Chemists from the University of Basel have now been able to...
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