Karen Pardos Olsen

Karen Pardos Olsen

Postdoc

DTU ELEKTRO
Institut for Elektroteknologi

Danmarks Tekniske Universitet

Frederiksborgvej 399

Bygning 776, rum 23

4000 Roskilde

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Projekter
CV
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CV

Uddannelse

2012 - 2015
PhD in astronomy, University of Copenhagen

Akademiske Grader

PhD

Ansættelser

2015 - 2018
Arizona State University, Postdoc

Sprogkundskaber

Dansk, Engelsk, Spansk

Ekspertise

Research interests in short: My research focuses on the development and improvement of integrated energy infrastructures needed to handle the ever-increasing penetration of renewable energy in power systems world-wide. 

Keywords: integration of renewable energy; wind power; energy storage; power system planning; simulations; multi-energy systems

Increased flexibility to handle high penetrations of variable renewable energy (VRE)

As part of the ESOM group (Energy Systems Operation and Management), I search for ways to reshape and store wind power in a multi-energy system by making connections to e.g. the hot water and gas sectors. For that work, I am involved in the EPIMES project: Enhancing wind Power Integration through optimal use of cross-sectoral flexibility in an integrated Multi-Energy System, a project which is a collaboration between DTU CEE and Chinese partners, including Tsinghua University in Beijing. On the Danish side, much work has gone into studying the flexibility options in a normal residential house, where energy can be stored as heat and smart planning using Model Predictive Control can ensure that heating takes place mostly at times with low electricity prices (see a recent paper on this here).

I use different tools to analyze the residual load between consumption and VRE generation with the aim of setting requirements for energy storage (ES) options now and in the future. See a more detailed description of this work here: https://kpolsen.github.io/research/renew/

Simulating timeseries of heat and electricity demand for different residential scenarios

In connection with the SmILES project, I am also working on making (bottom-up) realistic simulations of e.g. residential heating demand. Such algorithms become useful in cases where personal data protection laws prevent the use of actual data. In particular, we use the python module Mosaik to co-simulate several components simultaneously.

 

 

Hjemmesider

https://kpolsen.github.io/ - https://kpolsen.github.io/