Hierarchical Line Loss Allocation Methods for Low-Voltage Distribution Networks with Distributed Photovoltaics

Qingjiong Peng, Haobo Zhang, Haotian Cai, Hongwe Li, Xiaolong Wang, Xiangang Peng () and Zhuoli Zhao
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Qingjiong Peng: School of Automation, Guangdong University of Technology, Guangzhou 510006, China
Haobo Zhang: School of Automation, Guangdong University of Technology, Guangzhou 510006, China
Haotian Cai: School of Automation, Guangdong University of Technology, Guangzhou 510006, China
Hongwe Li: School of Automation, Guangdong University of Technology, Guangzhou 510006, China
Xiaolong Wang: School of Automation, Guangdong University of Technology, Guangzhou 510006, China
Xiangang Peng: School of Automation, Guangdong University of Technology, Guangzhou 510006, China
Zhuoli Zhao: School of Automation, Guangdong University of Technology, Guangzhou 510006, China

Mathematics, 2025, vol. 13, issue 21, 1-28

Abstract: 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.

Keywords: distributed photovoltaics; low-voltage distribution network; line loss allocation; marginal loss coefficient; Shapley values (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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