Modelling Feasible Operation Region of An Electricity Distribution Network: A Hybrid Simulation-Analytical Approach

The increasing integration of low-carbon technologies into electricity distribution networks necessitates a thorough understanding of the network' capacity to accommodate these changes. The feasible operation region (FOR), which describes the allowable range of power injections of a distribution network without violating the network constraints, provides a promising solution to describe the overall picture of the network capability. This paper proposes a hybrid simulation-analytical approach for the modelling of FOR boundaries. The hybrid approach uses the dataset that is obtained from simulation to calculate the errors of the analytical expressions due to some impractical assumptions. These errors are then used to adjust the parameters of the analytical FOR boundaries to improve their accuracy. To obtain the optimal parameters for the analytical expressions of FOR boundaries, an interval elimination method is used. The effectiveness of the hybrid simulation-analytical approach has been validated using a feeder of an 11kV high-voltage underground network. The results show that compared to the existing analytical approach for obtaining FOR boundaries, the hybrid approach in this study can improve the accuracy of analytical expressions for different FOR boundaries by 19%-95%. Additionally, the results demonstrate that the same types of FOR boundaries, including thermal boundaries and voltage upper/lower boundaries, tend to have similar optimal parameters, which provides practical insights for efficiently selecting parameters for different FOR boundary types.

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Published
2024-11-29
DOI
https://doi.org/10.1109/ei264398.2024.10991731
Primary Topic
Simulation Techniques and Applications
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article
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article

Modelling Feasible Operation Region of An Electricity Distribution Network: A Hybrid Simulation-Analytical Approach

Jianzhong Wu, Yue Zhou, Xun Jiang
Simulation Techniques and Applications
article

Modelling Feasible Operation Region of An Electricity Distribution Network: A Hybrid Simulation-Analytical Approach

Jianzhong Wu, Yue Zhou, Xun Jiang
article en

Abstract

The increasing integration of low-carbon technologies into electricity distribution networks necessitates a thorough understanding of the network' capacity to accommodate these changes. The feasible operation region (FOR), which describes the allowable range of power injections of a distribution network without violating the network constraints, provides a promising solution to describe the overall picture of the network capability. This paper proposes a hybrid simulation-analytical approach for the modelling of FOR boundaries. The hybrid approach uses the dataset that is obtained from simulation to calculate the errors of the analytical expressions due to some impractical assumptions. These errors are then used to adjust the parameters of the analytical FOR boundaries to improve their accuracy. To obtain the optimal parameters for the analytical expressions of FOR boundaries, an interval elimination method is used. The effectiveness of the hybrid simulation-analytical approach has been validated using a feeder of an 11kV high-voltage underground network. The results show that compared to the existing analytical approach for obtaining FOR boundaries, the hybrid approach in this study can improve the accuracy of analytical expressions for different FOR boundaries by 19%-95%. Additionally, the results demonstrate that the same types of FOR boundaries, including thermal boundaries and voltage upper/lower boundaries, tend to have similar optimal parameters, which provides practical insights for efficiently selecting parameters for different FOR boundary types.

Cardiff University (GB)
Affordable and clean energy
Openalex Percentile: Top 65%
Simulation Techniques and Applications
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Modelling Feasible Operation Region of An Electricity Distribution Network: A Hybrid Simulation-Analytical Approach — Jianzhong Wu, Yue Zhou, et al. · (2024) | TGRS Research Map | TGRS