Details
| Original language | English |
|---|---|
| Article number | 687 |
| Journal | ENERGIES |
| Volume | 14 |
| Issue number | 3 |
| Publication status | Published - 29 Jan 2021 |
Abstract
Keywords
- Active distribution grid, Aggregation of flexibilities, DSO/DSO-cooperation, Equivalent PQ-capability, Feasible operation region, Hierarchical grid control, Optimization-based sampling, PQ-flexibility area, PQ-flexibility map, TSO/DSO-cooperation
ASJC Scopus subject areas
- Mathematics(all)
- Control and Optimization
- Energy(all)
- Energy (miscellaneous)
- Energy(all)
- Energy Engineering and Power Technology
- Engineering(all)
- Electrical and Electronic Engineering
- Energy(all)
- Fuel Technology
- Energy(all)
- Renewable Energy, Sustainability and the Environment
Sustainable Development Goals
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In: ENERGIES, Vol. 14, No. 3, 687, 29.01.2021.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Survey and Comparison of Optimization-Based Aggregation Methods for the Determination of the Flexibility Potentials at Vertical System Interconnections
AU - Sarstedt, Marcel
AU - Kluß, Leonard
AU - Gerster, Johannes
AU - Meldau, Tobias
AU - Hofmann, Lutz
N1 - Funding Information: Funding: This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) project number—359921210.
PY - 2021/1/29
Y1 - 2021/1/29
N2 - The aggregation of operational active and reactive power flexibilities as the feasible operation region (FOR) is a main component of a hierarchical multi-voltage-level grid control as well as the cooperation of transmission and distribution system operators at vertical system interconnections. This article presents a new optimization-based aggregation approach, based on a modified particle swarm optimization (PSO) and compares it to non-linear and linear programming. The approach is to combine the advantages of stochastic and optimization-based methods to achieve an appropriate aggregation of flexibilities while obtaining additional meta information during the iterative solution process. The general principles for sampling an FOR are introduced in a survey of aggregation methods from the literature and the adaptation of the classic optimal power flow problem. The investigations are based on simulations of the Cigré medium voltage test system and are divided into three parts. The improvement of the classic PSO algorithm regarding the determination of the FOR are presented. The most suitable of four sampling strategies from the literature is identified and selected for the comparison of the optimization methods. The analysis of the results reveals a better performance of the modified PSO in sampling the FOR compared to the other optimization methods.
AB - The aggregation of operational active and reactive power flexibilities as the feasible operation region (FOR) is a main component of a hierarchical multi-voltage-level grid control as well as the cooperation of transmission and distribution system operators at vertical system interconnections. This article presents a new optimization-based aggregation approach, based on a modified particle swarm optimization (PSO) and compares it to non-linear and linear programming. The approach is to combine the advantages of stochastic and optimization-based methods to achieve an appropriate aggregation of flexibilities while obtaining additional meta information during the iterative solution process. The general principles for sampling an FOR are introduced in a survey of aggregation methods from the literature and the adaptation of the classic optimal power flow problem. The investigations are based on simulations of the Cigré medium voltage test system and are divided into three parts. The improvement of the classic PSO algorithm regarding the determination of the FOR are presented. The most suitable of four sampling strategies from the literature is identified and selected for the comparison of the optimization methods. The analysis of the results reveals a better performance of the modified PSO in sampling the FOR compared to the other optimization methods.
KW - Active distribution grid
KW - Aggregation of flexibilities
KW - DSO/DSO-cooperation
KW - Equivalent PQ-capability
KW - Feasible operation region
KW - Hierarchical grid control
KW - Optimization-based sampling
KW - PQ-flexibility area
KW - PQ-flexibility map
KW - TSO/DSO-cooperation
UR - http://www.scopus.com/inward/record.url?scp=85102152846&partnerID=8YFLogxK
U2 - 10.3390/en14030687
DO - 10.3390/en14030687
M3 - Article
VL - 14
JO - ENERGIES
JF - ENERGIES
SN - 1996-1073
IS - 3
M1 - 687
ER -