Dimensioning load flow scenarios for capacity analysis - A case study of the 135 kV grid in Southern Sweden
(2025) In CODEN:LUTEDX/TEIE EIEM01 20251Industrial Electrical Engineering and Automation
- Abstract (Swedish)
- Society is undergoing a great transformation with regard to the climate crisis, where electrification plays a crucial role in decarbonizing. To meet the future energy demand, improving power grid utilization is essential. This thesis develops standardized methods to evaluate and identify key parameters in terms of impact and branch loading, and to determine the probability of load flow scenarios utilizing historical data. In collaboration with E.ON Energidistribution, a case study implements the developed methods on predefined scenarios using their grid model and performing simulations in PSSE. The parameter impact on the 10 most critical branches was investigated by conducting a sensitivity analysis based on nine parameters, through... (More)
- Society is undergoing a great transformation with regard to the climate crisis, where electrification plays a crucial role in decarbonizing. To meet the future energy demand, improving power grid utilization is essential. This thesis develops standardized methods to evaluate and identify key parameters in terms of impact and branch loading, and to determine the probability of load flow scenarios utilizing historical data. In collaboration with E.ON Energidistribution, a case study implements the developed methods on predefined scenarios using their grid model and performing simulations in PSSE. The parameter impact on the 10 most critical branches was investigated by conducting a sensitivity analysis based on nine parameters, through scaling the parameters separately in the grid model, and observing the change in loading of these branches. Load was shown to be the most important parameter.
To determine probability, the method assigns each parameter to an interval, determining the range of values it may hold. Historical data is then examined to identify the frequency of all parameters concurrently falling within their assigned intervals. Two distinct approaches to interval division were explored, based on three equal segments and percentiles, respectively. A third approach for interval division was based on the sensitivity analysis, which iteratively expanded until the desired number of occurrences was found. This approach could not give an explicit historical frequency, but returned hours, with branch loadings similar to the studied case on the 10 most critical branches. Comparing branch loadings from the third approach with definitions of dimensioning load flows could, however, be used as an interpretation of the probability. The results showed that the dimensioning load flows only occurred once or never during 2020-2024, indicating that they are too conservatively defined for grid planning. Redefining these cases might lead to a higher grid utilization rate, given that more connections can take place for a given topology, however, such a thing should be done carefully, considering the accepted level of risk. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9206503
- author
- Lundqvist, Julia LU and Söderström, Vera LU
- supervisor
- organization
- course
- EIEM01 20251
- year
- 2025
- type
- H3 - Professional qualifications (4 Years - )
- subject
- keywords
- Probability, Grid Planning, Load Flow Scenarios, PSSE, Branch Loading
- publication/series
- CODEN:LUTEDX/TEIE
- report number
- 5541
- language
- English
- id
- 9206503
- date added to LUP
- 2025-07-01 13:24:08
- date last changed
- 2025-07-01 13:24:08
@misc{9206503,
abstract = {{Society is undergoing a great transformation with regard to the climate crisis, where electrification plays a crucial role in decarbonizing. To meet the future energy demand, improving power grid utilization is essential. This thesis develops standardized methods to evaluate and identify key parameters in terms of impact and branch loading, and to determine the probability of load flow scenarios utilizing historical data. In collaboration with E.ON Energidistribution, a case study implements the developed methods on predefined scenarios using their grid model and performing simulations in PSSE. The parameter impact on the 10 most critical branches was investigated by conducting a sensitivity analysis based on nine parameters, through scaling the parameters separately in the grid model, and observing the change in loading of these branches. Load was shown to be the most important parameter.
To determine probability, the method assigns each parameter to an interval, determining the range of values it may hold. Historical data is then examined to identify the frequency of all parameters concurrently falling within their assigned intervals. Two distinct approaches to interval division were explored, based on three equal segments and percentiles, respectively. A third approach for interval division was based on the sensitivity analysis, which iteratively expanded until the desired number of occurrences was found. This approach could not give an explicit historical frequency, but returned hours, with branch loadings similar to the studied case on the 10 most critical branches. Comparing branch loadings from the third approach with definitions of dimensioning load flows could, however, be used as an interpretation of the probability. The results showed that the dimensioning load flows only occurred once or never during 2020-2024, indicating that they are too conservatively defined for grid planning. Redefining these cases might lead to a higher grid utilization rate, given that more connections can take place for a given topology, however, such a thing should be done carefully, considering the accepted level of risk.}},
author = {{Lundqvist, Julia and Söderström, Vera}},
language = {{eng}},
note = {{Student Paper}},
series = {{CODEN:LUTEDX/TEIE}},
title = {{Dimensioning load flow scenarios for capacity analysis - A case study of the 135 kV grid in Southern Sweden}},
year = {{2025}},
}