A Study on the Patent Trend of AI-based Renewable Power Generation Forecasting Technologies
- Authors
- Jang, Moon-Jong; Kim, Taehoon; Oh, Eunsung
- Issue Date
- Apr-2023
- Publisher
- Korean Institute of Electrical Engineers
- Keywords
- Artificial intelligence; forecasting; international patent classification; patent trend; renewable
- Citation
- Transactions of the Korean Institute of Electrical Engineers, v.72, no.4, pp 496 - 502
- Pages
- 7
- Journal Title
- Transactions of the Korean Institute of Electrical Engineers
- Volume
- 72
- Number
- 4
- Start Page
- 496
- End Page
- 502
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/91845
- DOI
- 10.5370/KIEE.2023.72.4.496
- ISSN
- 1975-8359
2287-4364
- Abstract
- In order to utilize renewable power generation that contains uncertainty due to natural intermittence, it is essential to develop renewable power generation forecasting technologies. This paper focuses on identifying the technology development of artificial intelligence (AI)-based renewable power generation by the analysis of patents. In this study, AI-based renewable power generation forecasting technology is comprehensively defined, and related patent applications are systematically identified to analyze country, period, and technological trends. The results indicate that 1) renewable power generation forecasting has reached a technological maturity in Japan, the United States, and Europe, 2) to overcome this, AI technology has been being grafted onto renewable power generation forecasting, 3) the use of meteorological data was described as a major right, and AI technology was described as an applicable additional item due to the characteristics of AI technology patents. Copyright © The Korean Institute of Electrical Engineers.
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