David Cardona-Vásquez

David Cardona-Vásquez

he / him

Ph.D.in Engineering, Computer Engineer, and Economist with experience in energy systems and markets. Strong focus on machine learning, data analytics, optimization and economic regulation.

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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

portfolio

ÖSpeicher - 2023

(2023) - A consulting project developed for the Austrian Power Grid, the country’s ISO, to determine medium-term storage requirements for the Austrian power system

publications

On the aggregation of input data for energy system models

Published in Elektrotechnik und Informationstechnik, 2022

Exploratory analysis of the effects of different input-data aggregation strategies on the accuracy and tractability of energy system models

Recommended citation: Cardona-Vasquez, D., DiTondo, D., Wogrin, S. (2022). "On the aggregation of input data for energy system models." Elektrotechnik und Informationstechnik. 139(8).

Effect of the intermittency of non-conventional renewable energy sources on the volatility of the Colombian spot price

Published in Renewable Energy, 2024

Enhanced Time Series Aggregation for energy system models using an a-posteriori approach based on sets of active constraints.

Recommended citation: Cardona-Vasquez, D., Garcia-Rendon, J., Arango-Manrique, A. (2024). "EEffect of the intermittency of non-conventional renewable energy sources on the volatility of the Colombian spot price." Renewable Energy. 232(121073).

Disaggregation of energy system optimization models using machine learning for identification of active constraints

Published in Sustainable Energy, Grids and Networks, 2025

Disaggregation of energy system optimization models using machine learning for identification of active constraints.

Recommended citation: Cardona-Vasquez, D., Konrad, A., Werner, Y., Wogrin, S. (2025). "Disaggregation of energy system optimization models using machine learning for identification of active constraints." Sustainable Energy, Grids and Networks. 43(101772).

talks

Improving accuracy of energy system models for an efficient energy transition: basis-oriented aggregation and machine learning

Published:

In this talk, we present the results of applying a recently developed method, called Basis-Oriented time series aggregation, to improve the tractability of energy system models. We use machine learning techniques on previous runs to identify independent partitions of the time index that allow for a parallelized run of the model; greatly improving the running times of large scale optimization models.

teaching

Applied Energy Planning - 2022 to 2025

Masters course, Graz University of Technology, Institute of Electricity Economics and Energy Innovation, 2022

Master’s level course where we teach the students the basics of energy systems planning. The course is divided into two parts: the first one, taught by a different instructor, is about the basics energy systems modeling using optimization, while the second, the one taught by me, is about data analysis and manipulation to run the optimization problems. In my part, the students familiarize themselves with the data sources, tools and common practices used in energy systems modeling, they also have an initial exposure to the applications of machine learning in energy systems modeling.

Link to the course here

Micro and Macroeconomics for Electrical Engineers - 2022 to 2024

Masters course, Graz University of Technology, Institute of Electricity Economics and Energy Innovation, 2022

Master’s level course where we teach the students the basics of economics. The course is divided into two parts: the first one, taught by a different instructor, lays the microeconomic foundations like basic utility theory, consumer theory and basic industrial organization. The second part, the one taught by me, is about macroeconomics, where students learn about general concepts like GDP, inflation, unemployment, and the role of the government in the economy; and also they learn about how all of these affect business decisions and everyday life of the people.

Link to the course here

Special Problems in Electricity Economics - 2024 and 2025

Masters course, Graz University of Technology, Institute of Electricity Economics and Energy Innovation, 2024

Master’s level course where we introduce to the students the basic tools of financial mathematics and project finance. In this course, the students learn about how companies make real-world business decisions using technical and economic information.

Link to the course here

Energy and Environment - 2025

Masters course, Graz University of Technology, Institute of Electricity Economics and Energy Innovation, 2025

Master’s level course where we teach the students the basics of the interplay between the environment and energy related activities. The course is divided into two parts: the first one, taught by me, lays the economic foundations about natural resource economics; there, the students learn concepts like the externalities, public goods and environmental valuation. The second part, taught by a different instructor, focuses on recent technologies with an emphasis of lifecycle analysis.

Link to the course here