COPA model

Climate based Optimization of renewable Power Allocation (COPA) is a renewable electricity system model based on the principle that long-term climate change mitigation goals need high levels of renewable electricity penetration. The model therefore aims at exploring the characteristics of such systems and focuses on the underlying meteorological processes that strongly drive the dynamics of renewable electricity generation. Currently, the model is able to depict solar PV, wind, and hydropower production.

The model takes as input timeseries of renewable power production from solar PV, wind, and hydro power and minimizes the amount of thermal backup power production by optimizing the choice of renewable production locations, i.e. by optimizing the portfolio of renewable power production options in a linear programming approach. Additionally, other flexibility mechanisms such as storage and demand side response can be implemented in the model. Thermal power production is not modelled in great detail, although this is possible, wherever sufficient data is available.

The model was first developed for Brazil, but aims at reaching global coverage. For that reason we are using globally available climatological datasets - either from temporally and spatially highly resolved reanalysis products such as the MERRA and ECMWF interim reanalysis or from future climate change scenarios. Those products have been validated for utilization in energy system models against ground measurements for different world regions and we aim at additionally validating locations around the globe.

Data is prepared in R, using R-Studio. The optimization runs in GAMS.

Publications

Journal articles

Schmidt, J., Cancella, R., Pereira Jr., A.O., 2016. An optimal mix of solar PV, wind and hydro power for a low-carbon electricity supply in Brazil. Renewable Energy 85, 137-147.
link (gated) early working paper (free)

Schmidt, J., Cancella, R., Pereira Jr., A.O., 2016. The effect of windpower on long-term variability of combined hydro-wind resources: The case of Brazil. Renewable and Sustainable Energy Reviews 55, 131;141.
link (gated) early working paper (free)

Schmidt, J., Cancella, R., Pereira Jr., A.O., n.d. The role of wind power and solar PV in reducing risks in the Brazilian hydro-thermal power system. Energy.
link (gated)

Master thesis (completed)

Sebastian Mosshammer: Validation of MERRA-data with a wind power simulation model in comparison to real production quantities. University of Natural Resources and Life Sciences, Vienna.

Johann Baumgartner: Modelling the aggregated wind power generation of windparks in comparison to measured output for two case studies in Austria and New Zealand (in German). University of Natural Resources and Life Sciences, Vienna.

Datasets & Code

R-Code for deriving wind power production from MERRA-2 wind speeds for single wind parks

The zip-file contains a list of functions useful to derive wind power production from MERRA-2 wind speeds. In particular, we provide an extensive list of functions for vertical and horizontal interpolation of wind speeds, and for bias correction. The respective background is described in the two master theses above (by Sebastian Mooshammer and Johann Baumgartner, who also wrote the code). There is an example script included for a wind farm in New Zealand, including real production data (for validation and bias correction) and the necessary MERRA-2 files.

Download scripts and datasets

6-hourly wind power production for four Brazilian states for the period 1979-2014 simulated from ECMWF-interim

This data set contains a 6-hourly production timeseries for the period 1979-2014 for wind power for one turbine (Time zone UTC, in kWh) for the Bahia (BA), Cear√° (CE), Rio Grande do Norte (RN), and Rio Grande do Sul (RS). We used the ECMWF-interim reanalysis dataset to derive windspeeds and calibrated windspeed data against ground measurements. Reanalysis data points are chosen so that the simulated wind production is similar to the wind regime of wind turbines in operation in 2014/2015. We simulated power output from an Enercon E82 turbine. The exact procedure applied can be found in our paper: link (gated) early working paper (free).

Download data set

When using, please cite

Schmidt, J., Cancella, R., Pereira Jr., A.O., 2016. The effect of windpower on long-term variability of combined hydro-wind resources: The case of Brazil. Renewable and Sustainable Energy Reviews 55, 131;141.

Daily inflows into Brazilian hydropower plants for the period 1979-2014 for the four Brazilian subsystems.

I used Natural Inflow Data from ONS and the deck of PDE 2022 # to generate the data. Please observe that the production data was not calibrated against real production values in the system.

Download data set

When using, please cite

Schmidt, J., Cancella, R., Pereira Jr., A.O., 2016. An optimal mix of solar PV, wind and hydro power for a low-carbon electricity supply in Brazil. Renewable Energy 85, 137-147.



Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Research Projects


Project Title

Duration

Institution

Partners

A renewable electricity system with high shares of intermittent production: the case of Brazil

1/2014-6/2015

Energy Planning Program, Federal University of Rio de Janeiro

-

Integrating renewable electricity systems with the biomass conversion sector: a focus on extreme meteorological events

9/2016-8/2018

Institute for Sustainable Economic Development, University of Natural Resources and Life Sciences, Vienna

Energy Engineering, Luleå University of Technology

Main model developer

Johannes Schmidt