Energy Meteorology and Renewable Resources

The weather has a major influence on the planning and operation of  energy systems. In the past, these influences primarily included energy consumption in the electricity and heat sector, which are strongly influenced by temperature, but also by brightness. At the same time, extreme weather conditions such as droughts and storm events have always been able to cause safety-critical effects in conventional power plants.

The transformation of the energy system towards a high proportion of weather-dependent energy sources has significantly increased the weather dependency. In 2020, an average of more than 37% of net electricity generation in Germany was already covered by wind and solar PV systems, which once again clearly underlines the growing role of the weather. In addition, a wide range of cross-sector flexibility options are heavily dependent on local weather conditions in terms of generation, consumption and the utilization of energy supply structures.

Meteorology and geoinformatics, and the methods, models and measurement campaigns based on them, are thus being used directly in the energy industry. Therefore, the accuracy of the methods developed in these fields has a direct impact on the security of the energy supply and the economic viability of the energy transition.

In order to be able to answer energy system analysis questions on larger space and time scales, additional information about the localized generation and consumption landscape is required in addition to the weather conditions. On the one hand, this includes the location of the systems already installed, but also the estimation of new installations to be expected in the future. Consequently, it concerns not only the large number of additional planned renewable energy plants, but also, in particular, the location-specific development of controllable loads such as electrolysers, heat pumps, charging stations and storage systems.

In addition to the meteorological determined site potentials, detailed information on the energy grids, the building landscape and socio-economic effects also play an important role in order to be able to estimate future developments more accurately. Geoinformatics methods and geographic information systems (GIS) are used and further developed to link various geo-referenced data sets.
 

Real-time systems for forecasting energy generation and consumption for the next few minutes to days into the future have already been established in the day-to-day business of energy supply for several years, whereby the requirements for the quality of these systems are continuously increasing with further installations. Artificial intelligence (AI) methods have proven increasingly useful in this area, as they often meet the requirements for automation and scaling.

To create location-specific analyses, existing data sets are supplemented with current measurement data from remote sensing methods in order to better capture specific influencing factors such as local weather phenomena, shading and shadowing, turbulence, etc. Modern location-specific LIDAR measurement methods for wind field measurement and large-scale earth observation data are used here.

The capacity of overhead power lines is determined under the meteorological conditions specified in the EN 50182 standard assuming  35 °C air temperature, 900 W/m² global radiation and 0.6 m/s wind speed perpendicular to the conductor cable. Very frequently, however, the conductor cable is cooled more intensively, e.g. by lower air temperatures or lower global radiation. These cooling effects are addressed by indirect methods based on weather data. In principle, the meteorological parameters wind speed, air temperature and global radiation are converted into the continuous current carrying capacity using a conversion model like CIGRE.