Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings 2023 IEEE PES Innovative Smart Grid Technologies - Asia, ISGT Asia 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (electronic) | 9798350327748 |
| ISBN (print) | 9798350327755 |
| Publication status | Published - 2023 |
| Event | 2023 IEEE PES Innovative Smart Grid Technologies - Asia, ISGT Asia 2023 - Auckland, New Zealand Duration: 21 Nov 2023 → 24 Nov 2023 |
Publication series
| Name | IEEE PES Innovative Smart Grid Technologies |
|---|---|
| ISSN (Print) | 2378-8534 |
| ISSN (electronic) | 2378-8542 |
Abstract
With the ongoing electrification of heat and mobility a large amount of high-power devices is added to the distribution system level. Their so far assumed power behavior is expected to change in case of an active participation in emerging power flexibility markets. Thus, conventional grid planning approaches, that use simultaneity factors and determined power values, incompletely map the utilization potentials of the grids utilities due to the new active and reactive power flexibilities. To derive possibly needed grid reinforcement measures, knowledge about the occurring grid operational constraints is required. One approach to enable system operators to use these flexibilities in the context of vertical system level cooperation is the aggregation of power flexibilities at the vertical interconnection as a feasible operation region (FOR). This paper focusses on the comparison of methods, that emerged from the adaption of a particle swarm optimization (PSO) algorithm, which aims on identifying the FOR but also the grid operation constraints, i.e. voltage band, thermal line currents and transformer rating, in the active and reactive power plane. This is done to improve the integration of new devices in the planning process towards active distribution grids by comprehensively identifying constraining limits. As an exemplary case-study a generic low-voltage network with simple string topology is used. Results show, that post-processing data driven methods are significantly faster in regards to computation time, but need significantly higher data storage in contrast to an additional sampling strategy with the PSO algorithm. As key factor, the PSO algorithm only finds solutions that comply with the grid operational constraints, whereas the data driven approaches can over and underestimate the resulting polygonal area. The main contribution of this paper is the methodological comparison of PSO based approaches towards an improved system planning process of active distribution grids.
Keywords
- Active Distribution Grid Planning, Feasible Operation Region, Method Comparison, Particle Swarm optimization
ASJC Scopus subject areas
- Computer Science(all)
- Artificial Intelligence
- Computer Science(all)
- Computer Networks and Communications
- Energy(all)
- Energy Engineering and Power Technology
- Energy(all)
- Renewable Energy, Sustainability and the Environment
- Engineering(all)
- Electrical and Electronic Engineering
- Engineering(all)
- Safety, Risk, Reliability and Quality
Sustainable Development Goals
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Proceedings 2023 IEEE PES Innovative Smart Grid Technologies - Asia, ISGT Asia 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (IEEE PES Innovative Smart Grid Technologies).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Comparison of Adapted PSO Methods Regarding the Determination of Grid Operation Constraints in the Vertical Active and Reactive Power Plane
AU - Wingenfelder, M.
AU - Hofmann, L.
N1 - Funding Information: This research was funded by German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e. V. DLR) – funding ref. 01MZ18011B.)
PY - 2023
Y1 - 2023
N2 - With the ongoing electrification of heat and mobility a large amount of high-power devices is added to the distribution system level. Their so far assumed power behavior is expected to change in case of an active participation in emerging power flexibility markets. Thus, conventional grid planning approaches, that use simultaneity factors and determined power values, incompletely map the utilization potentials of the grids utilities due to the new active and reactive power flexibilities. To derive possibly needed grid reinforcement measures, knowledge about the occurring grid operational constraints is required. One approach to enable system operators to use these flexibilities in the context of vertical system level cooperation is the aggregation of power flexibilities at the vertical interconnection as a feasible operation region (FOR). This paper focusses on the comparison of methods, that emerged from the adaption of a particle swarm optimization (PSO) algorithm, which aims on identifying the FOR but also the grid operation constraints, i.e. voltage band, thermal line currents and transformer rating, in the active and reactive power plane. This is done to improve the integration of new devices in the planning process towards active distribution grids by comprehensively identifying constraining limits. As an exemplary case-study a generic low-voltage network with simple string topology is used. Results show, that post-processing data driven methods are significantly faster in regards to computation time, but need significantly higher data storage in contrast to an additional sampling strategy with the PSO algorithm. As key factor, the PSO algorithm only finds solutions that comply with the grid operational constraints, whereas the data driven approaches can over and underestimate the resulting polygonal area. The main contribution of this paper is the methodological comparison of PSO based approaches towards an improved system planning process of active distribution grids.
AB - With the ongoing electrification of heat and mobility a large amount of high-power devices is added to the distribution system level. Their so far assumed power behavior is expected to change in case of an active participation in emerging power flexibility markets. Thus, conventional grid planning approaches, that use simultaneity factors and determined power values, incompletely map the utilization potentials of the grids utilities due to the new active and reactive power flexibilities. To derive possibly needed grid reinforcement measures, knowledge about the occurring grid operational constraints is required. One approach to enable system operators to use these flexibilities in the context of vertical system level cooperation is the aggregation of power flexibilities at the vertical interconnection as a feasible operation region (FOR). This paper focusses on the comparison of methods, that emerged from the adaption of a particle swarm optimization (PSO) algorithm, which aims on identifying the FOR but also the grid operation constraints, i.e. voltage band, thermal line currents and transformer rating, in the active and reactive power plane. This is done to improve the integration of new devices in the planning process towards active distribution grids by comprehensively identifying constraining limits. As an exemplary case-study a generic low-voltage network with simple string topology is used. Results show, that post-processing data driven methods are significantly faster in regards to computation time, but need significantly higher data storage in contrast to an additional sampling strategy with the PSO algorithm. As key factor, the PSO algorithm only finds solutions that comply with the grid operational constraints, whereas the data driven approaches can over and underestimate the resulting polygonal area. The main contribution of this paper is the methodological comparison of PSO based approaches towards an improved system planning process of active distribution grids.
KW - Active Distribution Grid Planning
KW - Feasible Operation Region
KW - Method Comparison
KW - Particle Swarm optimization
UR - http://www.scopus.com/inward/record.url?scp=85182923515&partnerID=8YFLogxK
U2 - 10.1109/ISGTAsia54891.2023.10372677
DO - 10.1109/ISGTAsia54891.2023.10372677
M3 - Conference contribution
AN - SCOPUS:85182923515
SN - 9798350327755
T3 - IEEE PES Innovative Smart Grid Technologies
BT - Proceedings 2023 IEEE PES Innovative Smart Grid Technologies - Asia, ISGT Asia 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE PES Innovative Smart Grid Technologies - Asia, ISGT Asia 2023
Y2 - 21 November 2023 through 24 November 2023
ER -