Gerald M. Lohmann

ORCID: 0000-0001-9971-6268
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About
Contact & Profiles
Research Areas
  • Solar Radiation and Photovoltaics
  • Photovoltaic System Optimization Techniques
  • Energy Load and Power Forecasting
  • Advanced Thermodynamics and Statistical Mechanics
  • Complex Systems and Time Series Analysis
  • Solar Thermal and Photovoltaic Systems
  • Marine and Coastal Research
  • Radiation Effects and Dosimetry
  • Plant Water Relations and Carbon Dynamics
  • Wind Energy Research and Development
  • Meteorological Phenomena and Simulations
  • Integrated Energy Systems Optimization
  • Energy, Environment, Economic Growth
  • Air Traffic Management and Optimization
  • Atmospheric and Environmental Gas Dynamics
  • Chaos control and synchronization
  • stochastic dynamics and bifurcation
  • Electric Power System Optimization
  • Wind and Air Flow Studies
  • Fractional Differential Equations Solutions
  • Social Acceptance of Renewable Energy
  • Fractal and DNA sequence analysis
  • Aerospace and Aviation Technology
  • Atmospheric aerosols and clouds

Carl von Ossietzky Universität Oldenburg
2016-2018

Czech Academy of Sciences, Institute of Physics
2014

Wind and solar power are known to be highly influenced by weather events may ramp up or down abruptly. Such in the production influence not only availability of energy, but also stability entire grid. By analysing significant amounts data from several regions around world with resolutions seconds minutes, we provide strong evidence that renewable wind sources exhibit multiple types variability nonlinearity time scale {\it seconds} characterise their stochastic properties. In contrast...

10.1088/1367-2630/18/6/063027 article EN cc-by New Journal of Physics 2016-06-24

Abstract. Characterizing spatiotemporal irradiance variability is important for the successful grid integration of increasing numbers photovoltaic (PV) power systems. Using 1 Hz data recorded by as many 99 pyranometers during HD(CP)2 Observational Prototype Experiment (HOPE), we analyze field clear-sky index k* (i.e., normalized to conditions) and sub-minute increments changes over specified intervals time) distances between tens meters about 10 km. By means a simple classification scheme...

10.5194/acp-16-6365-2016 article EN cc-by Atmospheric chemistry and physics 2016-05-25

Abstract. Observations of turbulence are analysed for the afternoon and evening transition (AET) during Boundary-Layer Late Afternoon Sunset Turbulence (BLLAST) experimental field campaign that took place in Lannemezan (foothills Pyrenees) summer 2011. The case 2 July is further studied because properties lower atmosphere (up to 300 m above ground level) were sampled with Meteorological Mini Aerial Vehicle (M2AV) from turbulently mixed stably stratified atmospheric conditions. Additionally,...

10.5194/acp-16-8009-2016 article EN cc-by Atmospheric chemistry and physics 2016-07-01

Abstract. Characterizations of short-term variability in solar radiation are required to successfully integrate large numbers photovoltaic power systems into the electrical grid. Previous studies have used ground-based irradiance observations with a range different temporal resolutions and systematic analysis effects averaging on representation is lacking. Using high-resolution surface data original between 0.01 1 s from six locations Northern Hemisphere, we characterize changes resulting...

10.5194/amt-11-3131-2018 article EN cc-by Atmospheric measurement techniques 2018-05-31

Abstract. Characterizations of short-term variability in solar radiation are required to successfully integrate large numbers photovoltaic power systems into the electrical grid. Previous studies have used ground-based irradiance observations with a range different temporal resolutions, and systematic analysis effects averaging on representation is lacking. Using high-resolution surface data original resolutions between 0.01 s 1 from six locations Northern Hemisphere, we characterize changes...

10.5194/amt-2017-309 preprint EN cc-by 2017-11-15

The power from wind and solar exhibits a nonlinear flickering variability, which typically occurs at time scales of few seconds. We show that high-frequency monitoring such renewable powers enables us to detect transition, controlled by the field size, where output qualitatively changes its behaviour type diffusive stochastic behaviour. find intermittency strong non-Gaussian behavior in cumulative total field, even for country-wide installation still survives both sources. To overcome short...

10.48550/arxiv.1505.01638 preprint EN other-oa arXiv (Cornell University) 2015-01-01

Abstract. Characterizing spatio-temporal irradiance variability is important for the successful grid integration of increasing numbers photovoltaic (PV) power systems. Using 1 Hz data recorded by as many 99 pyranometers during HD(CP)2 Observational Prototype Experiment HOPE, we analyze field clearsky index k∗ (i.e. normalized to conditions) and sub-minute increments changes over specified intervals time) distances between tens meters about ten kilometers. By means a simple classification...

10.5194/acp-2016-2 preprint EN cc-by 2016-01-19

Europe's energy transition towards renewable sources is imperative for achieving sustainability and mitigating climate change. However, the intermittency of solar wind power necessitates a detailed evaluation their combined potential. This study analyzes spatiotemporal distribution variability resources across Europe from 1979-2022, using ERA5 reanalysis data. Empirical Orthogonal Function (EOF) analysis used to characterize patterns in irradiance speed up multidecadal timescales. Also,...

10.5194/egusphere-egu24-15765 preprint EN 2024-03-09

Abstract. The article analyses airborne observations of turbulence in vertical and horizontal direction during the afternoon transition from turbulently mixed to stably stratified atmospheric conditions. data were obtained four flights at 14:30, 16:30, 18:30 20:30 UTC with Meteorological Mini Aerial Vehicle M2AV BLLAST field experiment summer 2011, which corresponds 18:30, 22:30 local time. Sunset was 19:42 UTC. anisotropy ratio defined here as variance wind speed changes a mean value about...

10.5194/acp-2015-1060 article EN cc-by 2016-01-29
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