Keele University, based in Newcastle-under-Lyme, Staffordshire, England, is developing a "Smart Energy Network Demonstrator" as part of a European and UK funding project. (https://www.keele.ac.uk/business/smartenergynetworkdemonstrator)

In a technical exchange of experience, more than 10 participants, researchers from the University and employees of Siemens Great Britain in Wildpoldsried were able to obtain information about the IREN2 project and participate in the results of our work. The focus of the English guest’s interest was the island capability of the IREN2 system - the stable operation of a local grid decoupled from the main electricity grid. In a live demo our "guests from the island" convinced themselves about the capabilities of our island demonstrator and were impressed by the technical implementation.

https://de.wikipedia.org/wiki/Keele_University

There are supposed to be clouds over Wildpoldsried, too. In order to know if and when a cloud is likely to move in front of the sun, a so-called fisheye camera has been watching the sky for some time now. In contrast to normal cameras or surveillance cameras, this camera has a very curved lens and corresponding optics and can thus capture the entire sky hemisphere. The camera is mounted on one of the containers in the Energy Campus Wildpoldsried and provides a picture of the sky every 5 seconds. An image recognition process is used to evaluate and determine the shading of the sun for about 10 minutes in advance, in order to predict the power collapse of photovoltaic systems by clouds.

The aim is to include this information in the control of the system, for example, in time to start an additional generator or to curtail a PV early. Large power gradients in the grid are thereby avoided. This can optimize the dimensioning of electrical storage and thereby optimize the cost of such systems; similarly, contractual commitments to the behavior of microgrids at the grid point of common coupling are better met.

In addition to the camera, the method consists of an artificial neural network for the calculation of the probable cloud movements and thus the probability of covering the sun. Supplementary intelligence also takes into account phenomena such as cloud speed, the spontaneous appearance and disappearance, and other cloud specifics to make the prediction even more reliable.

On December 13th and 14th, 2018, the seventh meeting of the IREN2 consortium took place in Wildpoldsried. Almost 20 participants of the project partners reported on the progress of the past half-year.

In addition, the focus was on the planning of the residual term of IREN2, the project completion and the design of the transition to a follow-up project, which will be called "pebbles". The content of the talks with Mayor Arno Zengerle included the relocation of the energy campus to a new area and the cooperation between the community and the pebbles consortium.

A joint dinner in the "Hirsch" and many conversations on the edge rounded off the good event in pre-Christmas mood.

For the operation of autarkic energy systems, the most accurate prediction possible of the expected generation is eminent for stable and optimized operation. As part of the research carried out in IREN2, measurements were taken at various photovoltaic plants and the forecasts compared with the actual course. Different prognosis procedures were used.

In the research project, methods were developed that could greatly improve the quality of previous forecasts. In doing so, effective radiation values are calculated by mathematical methods taking into account all geometrical properties of the plant and geography of the location, which better map the course of production over the day.

The results are impressive - the forecasts have been improved by 40% and achieve an average accuracy of more than 90% - more than 95% on sunny days. Since mid-November 2017, these methods have been successfully implemented in the IREN2 system in Wildpoldsried.