Hierarchical Line Loss Allocation Methods for Low-Voltage Distribution Networks with Distributed Photovoltaics
The bidirectional power flows and time-varying characteristics generated by distributed photovoltaic integration into low-voltage distribution networks pose accuracy and fairness challenges to traditional line loss allocation methods. Existing methods, based on unidirectional power flow assumptions, are unable to quantify the true contributions of PV nodes and ignore the multi-dimensional value attributes of photovoltaics. Against this background, following the principle of “who caused the incremental part of loss, who is responsible for it“, this paper proposes a hierarchical line loss allocation model for low-voltage distribution networks with distributed photovoltaics. The first layer employs an enhanced marginal loss coefficient method to allocate the baseline line losses without PV integration to original distribution network users. The second layer utilizes spatiotemporal weighted Shapley values to quantify the marginal contributions of PV nodes to line loss variations, while establishing a multi-dimensional PV value correction system based on local consumption rate, spatiotemporal matching degree, and voltage support capability, and transforms the multi-dimensional PV values into economic incentive signals through an adaptive Softmax weighting algorithm. Finally, simulation analysis validates the effectiveness of the proposed line loss allocation method.
Authors
- H.Z. Li
- Xiangang Peng (ORCID: https://orcid.org/0000-0002-5299-6554)
- Zhuoli Zhao (ORCID: https://orcid.org/0000-0003-2531-0614)
- Xiaolong Wang (ORCID: https://orcid.org/0000-0003-4210-840X)
- Haobo Zhang (ORCID: https://orcid.org/0000-0002-8770-2034)
- Haotian Cai
- Q. H. Peng (ORCID: https://orcid.org/0009-0001-4746-8191)
Institutions
- Guangdong University of Technology (CN)
Publication Details
- Journal
- Mathematics
- Published
- 2025-10-22
- DOI
- https://doi.org/10.3390/math13213366
- Primary Topic
- Optimal Power Flow Distribution
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Guangdong Power Grid Company