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ORIGINAL RESEARCH article
Front. Phys.
Sec. Radiation Detectors and Imaging
Volume 13 - 2025 | doi: 10.3389/fphy.2025.1534629
This article is part of the Research Topic Multi-Sensor Imaging and Fusion: Methods, Evaluations, and Applications, Volume III View all 4 articles
Performance Evaluation of Photovoltaic Scenario Generation
Provisionally accepted- 1 The Open University of Chengdu, Chengdu, Sichuan Province, China
- 2 Chongqing University of Science and Technology, Chongqing, China
- 3 Chongqing Carbon Energy Technology, Chongqing, China
- 4 Sichuan Aizhong Comprehensive Energy Technology Service, Sichuan, China
- 5 Chongqing Technology and Business University, Chongqing, China
Photovoltaic scenario generation is crucial in power systems with high diversities and fluctuations.Despite recent theoretical advances, evaluating the effectiveness of photovoltaic scenario generation remains a daunting task. Most studies have adopted the mean, variance, and probability density function to assess the performance. However, it is difficult to identify the source of the shape and environmental randomness (e.g., cloud and season) from either a sample or a batch of samples. To settle on a good measurement, this paper presents an evaluation of the performance of photovoltaic scenario generation with a wide-sense stationary process. After analyzing the existing photovoltaic scenario data, we describe the movement of the solar reception process with its distribution. Based on the autoregressive model, we capture the influence of environmental randomness on the photovoltaic scenario. The proposed evaluation model is capable of benchmarking the reliability of a generated photovoltaic scenario from all of the techniques. Furthermore, the model can also estimate which month or season that a generated photovoltaic sample belongs to. The experiments show the effectiveness of the proposed model reaches beyond simple probability properties on evaluating photovoltaic scenario generation, and this indicates further application of the proposed model in practical photovoltaic systems.
Keywords: Photovoltaic Scenario Generation, Wide-sense stationary process, Autoregressive model, Environmental Randomness Analysis, Performance Benchmarking for PV Systems
Received: 26 Nov 2024; Accepted: 03 Mar 2025.
Copyright: © 2025 Ren, Yang, Luo, Wu, Mao and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
TongXin Yang, Chongqing University of Science and Technology, Chongqing, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.