Photovoltaic Hosting Capacity Assessment of Distribution Networks Considering Source–Load Uncertainty
Year: 2025
Type: article
Abstract: With the continuous expansion of distributed photovoltaic (PV) integration, the hosting capacity of distribution networks has become a critical issue in power system planning and operation. Under varying meteorological and load fluctuation conditions, traditional assessment methods often face adaptability and uncertainty handling challenges. To enhance the practical applicability and accuracy of hosting capacity evaluations, this paper proposes a PV hosting capacity assessment model that incorporates source–load uncertainty and constructs an alternative scenario optimization evaluation framework driven by target-oriented scenario generation. The model considers system constraints and employs the sparrow search algorithm (SSA) to optimize the maximum PV hosting capacity. On the source side, PV output scenarios with temporal characteristics are generated based on the mapping relationship between meteorological factors and PV power. On the load side, historical data are employed to extract fluctuation ranges and to introduce random perturbations to simulate load uncertainty. In addition, a PV power scenario generation method based on the Wasserstein generative adversarial network with gradient penalty (WGAN-GP) is proposed, integrating physical-data dual-driven strategies to enhance the physical consistency of generated data, while incorporating a target-driven weighted sampling mechanism to improve its learning ability for key features. Case studies verify that the proposed method demonstrates strong adaptability and accuracy under varying meteorological and load conditions.
Source: Energies
DOI: 10.3390/en18082134
Authors: Chao Chen, Weifeng Peng, Cheng Xie, Shufeng Dong, Yibo Hua
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W4409634286