Optimal Evaluation of Photovoltaic Consumption Schemes in Distribution Networks Based on BASS Model for Photovoltaic Installed Capacity Prediction

Chenyang Fu^*, Xinghua Wang, Zilv Li, Xixian Liu, Xiongfei Zhang, Zhuoli Zhao
1 School of Automation, Guangdong University of Technology, Guangzhou, 510000, China
* Corresponding Author: Chenyang Fu. Email: email

Energy Engineering https://doi.org/10.32604/ee.2025.061172

Received 18 November 2024; Accepted 04 March 2025; Published online 31 March 2025

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Abstract

With the large-scale promotion of distributed photovoltaics, new challenges have emerged in the photovoltaic consumption within distribution networks. Traditional photovoltaic consumption schemes have primarily focused on static analysis. However, as the scale of photovoltaic power generation devices grows and the methods of integration diversify, a single consumption scheme is no longer sufficient to meet the actual needs of current distribution networks. Therefore, this paper proposes an optimal evaluation method for photovoltaic consumption schemes based on BASS model predictions of installed capacity, aiming to provide an effective tool for generating and evaluating photovoltaic consumption schemes in distribution networks. First, the BASS diffusion model, combined with existing photovoltaic capacity data and roof area information, is used to predict the trends in photovoltaic installed capacity for each substation area, providing a scientific basis for consumption evaluation. Secondly, an improved random scenario simulation method is proposed for assessing the photovoltaic consumption capacity in distribution networks. This method generates photovoltaic integration schemes based on the diffusion probabilities of different regions and evaluates the consumption capacity of each scheme. Finally, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to comprehensively evaluate the generated schemes, ensuring that the selected scheme not only meets the consumption requirements but also offers high economic benefits and reliability. The effectiveness and feasibility of the proposed method are validated through simulations of the IEEE 33-node system, providing strong support for optimizing photovoltaic consumption schemes in distribution networks.