Professor Kazuyuki Aihara of the Institute of Industrial Science, University of Tokyo conducted international joint research with Germany and the United Kingdom, and analyzed big data of frequency fluctuations observed in the power networks of Japan, the United States, and Europe.It was clarified that the actual frequency fluctuation has a non-normal distribution characteristic in which a change larger than the normally assumed "normal distribution" can occur.
In recent years, it has been proposed to divide the power grid and incorporate wind power generation and solar power generation into operation.Fluctuations in energy consumption and supply lead to frequency fluctuations, and sudden fluctuations damage electronic devices and the like.However, the details of how the division of the power grid and the increase in renewable energy and power transactions will affect the power grid have not been clarified.
The collaborative research group used big data of frequency-time fluctuations observed in the North American, European and Japanese power networks to analyze the statistical characteristics of the fluctuations.As a result, it was found that the frequency fluctuations of the European power grid were strongly influenced by the power transaction (power supply transaction at 15-minute intervals).In addition, it was clarified that it shows non-normal distribution characteristics with large frequency fluctuations that cannot occur with the normally assumed distribution (Gaussian distribution: a type of typical distribution of statistical data), and a mathematical model is constructed. bottom.It has also been shown that small power grids exhibit larger frequency fluctuations, and that the introduction of renewable energy and power transactions can contribute to larger frequency fluctuations.
Renewable energy and electricity transactions are expected to increase in Japan in the future.This achievement is expected to provide important basic knowledge for efficiently controlling and operating the Japanese power grid while considering stability and optimality.