Cem Özen
Data/Atmospheric Scientist · Renewable Energy Forecaster
About Me
I’m a computational meteorologist with a PhD in Atmospheric Sciences, focused on applying meteorological data and machine learning to the energy sector. I have also an extensive experience in wind resource assessment in different corporate companies in leading positions.
I specialize in building end-to-end forecasting systems using meteorological data (ECMWF HRES, Subseasonal, Seasonal, DWD ICON-EU, ICON-D2, NOAA-GFS), bias correction methods by using hindcasts/reforecasts, and climate-energy indicators across Europe.
Currently, I work at Vitus Commodities, delivering operational wind, solar, and demand forecasts and weather related indexes for trading strategies — ranging from hourly to seasonal timescales.
Dashboards
Climate Forecastory
An interactive dashboard that visualizes climate change and renewable energy potential across Europe — designed specifically for energy analysts, traders, and researchers.
The dashboard integrates state-of-the-art climate projections (RCP 2.6, 4.5, 8.5) with customized indicators like wind capacity factor, solar potential, total precipitation, and wind speed at 100m. Users can explore how these variables evolve over time and geography, compare scenarios, and analyze long-term trends at any location.
What I Work On
Wind, Solar, Energy Demand Forecasts
Forecasting renewable energy sources and energy demand using ensemble and deterministic weather models.
Energy Market Indices
Generating meteorological indexes spcealized for energy trading.
Climate Indices
Climate model outputs and its impact on the energy markets.
Energy Price & System Direction Forecasts
Forecasting energy prices and the system’s net direction which is essential for energy trading and reducing imbalance costs.
CV Highlights
PhD in Atmospheric Sciences, Istanbul Technical University
Specialized in wind energy forecast from hours up to months.
Professional Experience
- Developed operational forecasting systems both for wind and solar
- Led wind resource assessments, SCADA analysis, and performance evaluation
- Led an energy trading team optimizing wind and solar portfolios to reduce imbalance penalties
- Built dynamic R dashboards connected to wind farm SCADA systems
- Researched climate change effects on wind energy investments
Technical Skills
Programming languages: R, Python, Bash, SQL
Machine learning frameworks: H2O, Keras, Torch
Wind resource assessment tools: WindPro, Meteodyn, Windographer, WAsP, PVSyst
Atmospheric science & meteorology: WRF, RegCM, CDO
GIS: QGIS, GlobalMapper, terra library of R
Teaching & Courses
Delivered hands-on R courses on energy markets and forecasting.
Languages
Turkish (native)
English (proficiency)