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Framework for System Analyses of Smart Grid Solutions with Examples from the Gotland Case
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.ORCID iD: 0000-0001-6882-3642
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering. KTH Royal Institute of Technology.ORCID iD: 0000-0003-4763-9429
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering. KTH Royal Institute of Technology. (Reliability Centred Asset Management (RCAM) Group)ORCID iD: 0000-0002-2964-7233
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering. KTH Royal Institute of Technology. (Reliability Centred Asset Management (RCAM) Group)ORCID iD: 0000-0002-3543-9326
2016 (English)In: 2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), IEEE, 2016Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents results from a study on the impact of smart grid solutions, which includes development of a generic framework for power system analyses. The study has been performed as one of several independent studies, part of a national governmental task on smart grid in Sweden. A large amount of weather data, along with electricity consumption and wind power generation data, have been analyzed. Achieved results from these initial analyses can be used as reference material and have also been used within case studies presented. The proposed framework is flexible and numerous combinations of scenarios are possible to define. Integration of wind and solar power, analyses of transfer limits using static or dynamic rating and energy storage can be considered as well as weather effects. Results show how power systems can handle more electricity consumption and generation. The study shows that Smart Grid solutions are beneficial for resource efficient electricity grids. Moreover, different risk levels with respect to increased load can be included. Case study results show that energy storages most of the time will be unused, but that they can be used to increase the system reliability.

Place, publisher, year, edition, pages
IEEE, 2016.
Keywords [en]
Dynamic rating, Distributed generation, Energy storage, Smart Grid, Solar power generation, Weather Correlations, Wind power generation, Transfer limits
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-199935DOI: 10.1109/PMAPS.2016.7763923ISI: 000392327900001Scopus ID: 2-s2.0-85015145821ISBN: 978-1-5090-1970-0 (print)OAI: oai:DiVA.org:kth-199935DiVA, id: diva2:1066833
Conference
Probabilistic Methods Applied to Power Systems (PMAPS), 2016 International Conference on, Beijing, 16-20 Oct. 2016
Note

QC 20170206

Available from: 2017-01-19 Created: 2017-01-19 Last updated: 2017-05-19Bibliographically approved

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Wallnerström, Carl JohanBertling Tjernberg, LinaHilber, PatrikJürgensen, Jan Henning
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