<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>With high renewable energy sources (RESs) penetration in distribution networks, handling the uncertainties of RESs outputs and multi-time coupling problems in the dynamic network reconfiguration (DNR) is a big challenge. Besides, the existing mathematical and artificial intelligence algorithms for network reconfiguration face the problem of falling into local optima and poor convergence. To address the above challenge and problem, this paper first establishes a chance-constrained programming model to handle the uncertainties. Then the Minty algorithm is applied for efficiency and accurate static network reconfiguration (SNR) in each time interval. Finally, a branch exchange-based method is proposed to eliminate violations for the operation times of switches. Numerical simulations on the IEEE 33 system and an actual 151-bus distribution network show the superiority of the proposed algorithm over existing methods.</p>
</abstract>

With high renewable energy sources (RESs) penetration in distribution networks, handling the uncertainties of RESs outputs and multi-time coupling problems in the dynamic network reconfiguration (DNR) is a big challenge. Besides, the existing mathematical and artificial intelligence algorithms for network reconfiguration face the problem of falling into local optima and poor convergence. To address the above challenge and problem, this paper first establishes a chance-constrained programming model to handle the uncertainties. Then the Minty algorithm is applied for efficiency and accurate static network reconfiguration (SNR) in each time interval. Finally, a branch exchange-based method is proposed to eliminate violations for the operation times of switches. Numerical simulations on the IEEE 33 system and an actual 151-bus distribution network show the superiority of the proposed algorithm over existing methods.

A chance constrained dynamic network reconfiguration based on Minty algorithm in distribution networks

Shandong University of Science and Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

With high renewable energy sources (RESs) penetration in distribution networks, handling the uncertainties of RESs outputs and multi-time coupling problems in...

A chance constrained dynamic network reconfiguration based on Minty algorithm in distribution networks

Publié en ligne: 09 sept. 2023

Pages: -

Reçu: 19 nov. 2022

Accepté: 20 mars 2022

DOI: https://doi.org/10.2478/amns.2023.2.00304

Mots clés
Distribution network, Dynamic network reconfiguration, Chance-constrained programming, Minty algorithm, Renewable energy source

© 2023 Xinfu Song et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

A chance constrained dynamic network reconfiguration based on Minty algorithm in distribution networks

Publié en ligne: 09 sept. 2023

Pages: -

Reçu: 19 nov. 2022

Accepté: 20 mars 2022

DOI: https://doi.org/10.2478/amns.2023.2.00304

Mots clésDistribution network, Dynamic network reconfiguration, Chance-constrained programming, Minty algorithm, Renewable energy source

© 2023 Xinfu Song et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Distribution network, Dynamic network reconfiguration, Chance-constrained programming, Minty algorithm, Renewable energy source