Distribution System Reconfiguration using Multi-Stage Evolutionary Strategy for Constraints Satisfaction in Faulted Conditions

When a constraint violation occurs due to adding a new load to distribution systems, it can be resolved by reconfiguring the distribution systems by changing the states of switches and/or by minimum necessary investment. However, it is difficult to reconfigure the distribution system while satisfying the constraints made more severe by the new load installation. To find distribution system candidates that satisfy the severe constraints, this paper propose a multi-stage constrained multiobjective evolutionary algorithm (CMOEA). The proposed CMOEA dynamically changes the selection pressure at each search stage for constraints in normal and fault states, and it efficiently finds distribution system candidates that satisfy the severe constraints. Furthermore, the proposed CMOEA equals the number of sections and minimizes the number of remote/manual switch replacements as much as possible. The effectiveness of the proposed CMOEA is verified by case studies using a large-scale distribution system model equipped with many manual and remote switches.

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Publication Details

Journal
IEEJ Transactions on Power and Energy
Published
2025-06-30
DOI
https://doi.org/10.1541/ieejpes.145.457
Primary Topic
Optimal Power Flow Distribution
Type
article
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article

Distribution System Reconfiguration using Multi-Stage Evolutionary Strategy for Constraints Satisfaction in Faulted Conditions

Ken‐ichi Iwata, Shinya Sekizaki, Tomohiro Hayashida, Kazuhisa Hikoyama et al.
IEEJ Transactions on Power and Energy
Optimal Power Flow Distribution
article

Distribution System Reconfiguration using Multi-Stage Evolutionary Strategy for Constraints Satisfaction in Faulted Conditions

Ken‐ichi Iwata, Shinya Sekizaki, Tomohiro Hayashida, Kazuhisa Hikoyama, Yasuyuki Kunii, T. Kawakami, Takaaki Muto
article en

Abstract

When a constraint violation occurs due to adding a new load to distribution systems, it can be resolved by reconfiguring the distribution systems by changing the states of switches and/or by minimum necessary investment. However, it is difficult to reconfigure the distribution system while satisfying the constraints made more severe by the new load installation. To find distribution system candidates that satisfy the severe constraints, this paper propose a multi-stage constrained multiobjective evolutionary algorithm (CMOEA). The proposed CMOEA dynamically changes the selection pressure at each search stage for constraints in normal and fault states, and it efficiently finds distribution system candidates that satisfy the severe constraints. Furthermore, the proposed CMOEA equals the number of sections and minimizes the number of remote/manual switch replacements as much as possible. The effectiveness of the proposed CMOEA is verified by case studies using a large-scale distribution system model equipped with many manual and remote switches.

IEEJ Transactions on Power and EnergyVol. 145(7)
Hiroshima University (JP), Chubu Electric Power (Japan) (JP)
Climate action
Openalex Percentile: Top 87%
Optimal Power Flow Distribution
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Distribution System Reconfiguration using Multi-Stage Evolutionary Strategy for Constraints Satisfaction in Faulted Conditions — Ken‐ichi Iwata, Shinya Sekizaki, et al. · IEEJ Transactions on Power and Energy (2025) | TGRS Research Map | TGRS