TY  - JOUR
T1  - Zero-Shot Solar Power Efficiency Prediction Method Considering PCC-Based Climate Similarity
AU  - Kim, Dongjun 
AU  - Park, Sungwoo 
AU  - Moon, Jaeuk 
AU  - Hwang, Eenjun 
JO  - Journal of KIISE, JOK
PY  - 2023
DA  - 2023/1/14
DO  - 10.5626/JOK.2023.50.7.581
KW  - renewable energy
KW  - solar power generation
KW  - zero-shot
KW  - cold-start
KW  - weather similarity
AB  - Thermal power generation is a power generation method that occupies a large proportion in Korea and abroad due to its low unit price. However, due to its disadvantage of emitting large amounts of harmful substances that can cause health and environmental problems, renewable energy is in the spotlight as an alternative power source. Among various renewable energy generation methods, solar power generation is receiving the most attention because of its advantages such as ease in maintenance. Various solar power generation forecasting studies are being conducted to improve the uncertainty of volatile solar power generation and ensure stability in power supply. However, existing studies have limitations in that they are only applicable when there is a sufficient amount of historical power generation data. Therefore, this paper proposes a solar power generation efficiency prediction method based on zero-shot learning that utilizes historical data of similar regions by concerning weather similarity to solve the cold-start problem, a problem that occurs in prediction when historical data in the target region are lacking. Comparison results revealed that the proposed method had better performance overall in the target area, with a one-hour-based method showing the best prediction performance among other criteria.