상대계수법을 이용한 설 연휴에 대한 단기 전력수요예측 알고리즘Short-Term Load Forecasting Algorithm for Lunar New Year’s Holidays Using the Relative Coefficient Method
- Other Titles
- Short-Term Load Forecasting Algorithm for Lunar New Year’s Holidays Using the Relative Coefficient Method
- Authors
- 권보성; 문찬호; 송경빈
- Issue Date
- Jun-2022
- Publisher
- 한국조명.전기설비학회
- Keywords
- Lunar New Year’s Holidays; Reconstituted load method; Relative coefficient method; Short-term load forecasting
- Citation
- 조명.전기설비학회논문지, v.36, no.6, pp.9 - 17
- Journal Title
- 조명.전기설비학회논문지
- Volume
- 36
- Number
- 6
- Start Page
- 9
- End Page
- 17
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/43143
- DOI
- 10.5207/JIEIE.2022.36.6.009
- ISSN
- 1229-4691
- Abstract
- An algorithm to improve the accuracy of short-term load forecasting(STLF) for the Lunar New Year’s Holidays is proposed. The proposed algorithm can integrate the impact of temperature and behind-the-meter(BTM) solar PV generation on the load for the Lunar New Year’s Holidays. The hourly loads for the Lunar New Year’s Holidays are forecasted using the relative coefficient method.
The sensitivity of load to temperature is calculated, and the corrected loads using the calculated sensitivity are used to load forecast. In addition, the impact of BTM solar PV generation is integrated into the load forecast for the Lunar New Year’s Holidays using the reconstituted load method. Test results of load forecasts for the Lunar New Year’s Holidays from 2016 to 2020 have shown that the accuracy of load forecasting improves when the impacts of temperature and BTM solar PV generation are systematically considered in load forecasting.
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