Multi-Objective Approach for Distribution System Planning Considering Stochastic Customer-Owned Distributed Energy Resources
The installation of distributed energy resources (DERs) by end-customers has increased significantly in recent years. While customer-owned DERs offer various benefits, their integration adds complexity to distribution system planning due to the unpredictability of their quantity, sizes, and location...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10908807/ |
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| Summary: | The installation of distributed energy resources (DERs) by end-customers has increased significantly in recent years. While customer-owned DERs offer various benefits, their integration adds complexity to distribution system planning due to the unpredictability of their quantity, sizes, and locations. Consequently, they are referred to as stochastic customer-owned DERs in this study. In the specialized literature, optimization-based DER allocation is often explored; however, these allocation problems typically assume that the distribution system operator has control over the allocation of DERs within the grid, whereas real-world investments are predominantly driven by end-customers. Therefore, in this article, a multi-objective planning approach is proposed considering stochastic customer-owned DERs. This approach simultaneously addresses dynamic network reconfiguration, capacitors allocation, and dynamic adjustment of on-load tap changer transformer. The main objective is to minimize power loss costs and improve the system’s voltage profile by minimizing a novel voltage consistency indicator (VCI) introduced in this article. The optimization problem is solved using the Multi-objective Cuckoo Search, with the final solution selected through the Fuzzy Decision-making Method. Additionally, the Monte Carlo Method is employed to address uncertainties related to load, DER generation, and the quantity, sizes, and locations of customer-owned DERs. Finally, the results highlighted the importance of conducting a multi-period analysis, as it led to improvements compared to the static analysis. The proposed approach effectively reduced the VCI by 72.41% and minimized the power loss costs by 68.56% compared to the original system. |
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| ISSN: | 2169-3536 |