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

<p>In this study, we evaluate the enhanced carrying capacity of the modified IEEE 33-node distribution system, which incorporates a high percentage of distributed resource (DR) integration, utilizing the whale optimization algorithm. The evaluation employs a fuzzy comprehensive evaluation (FCE) method, wherein we construct FCE indices for factors influencing the distribution network’s carrying capacity. These indices involve calculating weight coefficients and establishing an affiliation function, culminating in the output of the final fuzzy evaluation result vector. The analysis identifies three nodes—11, 18, and 31—within the IEEE 33-node system for decentralized DR installation. Based on initial scenario data, the maximum carrying capacity of the distribution network is determined to be 40.68 MW. The analysis further reveals that the utilization rate of distributed resources reaches 100% at specific times, specifically at 2:00 AM and 6:00 AM. During the 3:00 to 5:00 AM interval, both the system voltage excursion index and the composite score for distribution network losses are calculated to be low. These findings suggest the feasibility of integrating a single regional distribution network with other energy networks, thereby facilitating multi-regional resource interconnection and enhancing the flexibility of system operations. This approach offers significant implications for improving the robustness and efficiency of electrical distribution systems.</p>
</abstract>

In this study, we evaluate the enhanced carrying capacity of the modified IEEE 33-node distribution system, which incorporates a high percentage of distributed resource (DR) integration, utilizing the whale optimization algorithm. The evaluation employs a fuzzy comprehensive evaluation (FCE) method, wherein we construct FCE indices for factors influencing the distribution network’s carrying capacity. These indices involve calculating weight coefficients and establishing an affiliation function, culminating in the output of the final fuzzy evaluation result vector. The analysis identifies three nodes—11, 18, and 31—within the IEEE 33-node system for decentralized DR installation. Based on initial scenario data, the maximum carrying capacity of the distribution network is determined to be 40.68 MW. The analysis further reveals that the utilization rate of distributed resources reaches 100% at specific times, specifically at 2:00 AM and 6:00 AM. During the 3:00 to 5:00 AM interval, both the system voltage excursion index and the composite score for distribution network losses are calculated to be low. These findings suggest the feasibility of integrating a single regional distribution network with other energy networks, thereby facilitating multi-regional resource interconnection and enhancing the flexibility of system operations. This approach offers significant implications for improving the robustness and efficiency of electrical distribution systems.

Construction and Optimization of Dynamic Assessment Indicators for Distribution Grid Carrying Capacity with High Proportion of Distributed Resource Connections

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

In this study, we evaluate the enhanced carrying capacity of the modified IEEE 33-node distribution system, which incorporates a high percentage of distributed...

Construction and Optimization of Dynamic Assessment Indicators for Distribution Grid Carrying Capacity with High Proportion of Distributed Resource Connections

Online veröffentlicht: 03. Juni 2024

Seitenbereich: -

Eingereicht: 07. Feb. 2024

Akzeptiert: 21. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1352

Schlüsselwörter
Whale optimization algorithm, Fuzzy comprehensive evaluation, Distributed resources, Carrying capacity

© 2024 Zhongqiang Zhou et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Construction and Optimization of Dynamic Assessment Indicators for Distribution Grid Carrying Capacity with High Proportion of Distributed Resource Connections

Online veröffentlicht: 03. Juni 2024

Seitenbereich: -

Eingereicht: 07. Feb. 2024

Akzeptiert: 21. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1352

SchlüsselwörterWhale optimization algorithm, Fuzzy comprehensive evaluation, Distributed resources, Carrying capacity

© 2024 Zhongqiang Zhou et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Whale optimization algorithm, Fuzzy comprehensive evaluation, Distributed resources, Carrying capacity