NDLI: Artificial Intelligence Applications in Estimating Invisible Solar Power Generation

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Artificial Intelligence Applications in Estimating Invisible Solar Power Generation

Content Provider	MDPI
Author	Wu, Yuan-Kang Lai, Yi-Hui Huang, Cheng-Liang Phuong, Nguyen Thi Bich Tan, Wen-Shan
Copyright Year	2022
Description	In recent years, the penetration of photovoltaic (PV) power generation in Taiwan has increased significantly. However, most photovoltaic facilities, especially for small-scale sites, do not include relevant monitoring and real-time measurement devices. The invisible power generation from these PV sites would cause a huge challenge on power system scheduling. Therefore, appropriate methods to estimate invisible PV power generation are needed. The main purpose of this paper is to propose an improved fuzzy model for estimating the PV power generation, which includes the clustering processing for PV sites, selection of representative PV sites, and the improvement of the conventional fuzzy model. First, this research uses the K-nearest neighbor (KNN) algorithm to fill in some of the missing data; then, two clustering algorithms are applied to cluster all the photovoltaic sites. Next, the relationship between the power generation of a single PV site and the total generation of all sites at the same cluster is further analyzed to select the representative PV sites. Finally, an improved fuzzy model is implemented to estimate the PV power generation. This research used actual data that were measured from PV sites in Taiwan for the estimation, verification, and comparison study. The numerical results demonstrate that the proposed method can obtain an average estimation error about 7% by using limit measurements from PV sites, highlighting the high efficiency and practicability of the proposed method.
Starting Page	1312
e-ISSN	19961073
DOI	10.3390/en15041312
Journal	Energies
Issue Number	4
Volume Number	15
Language	English
Publisher	MDPI
Publisher Date	2022-02-11
Access Restriction	Open
Subject Keyword	Energies Industrial Engineering Solar Photovoltaic Invisible Power Generation Representative Pv Sites Power Estimation Fuzzy Systems
Content Type	Text
Resource Type	Article

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