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¼ö·Ï»çÇ× Á¶¸íÀü±â¼³ºñÇÐȸ³í¹®Áö, Vol.36 No.06 (2022-06)
ÆäÀÌÁö ½ÃÀÛÆäÀÌÁö(9) ÃÑÆäÀÌÁö(9)
ISSN 1225-1135
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ÁÖÁ¦¾î ; Lunar New Year¡¯s Holidays; Reconstituted load method; Relative coefficient method; Short-term load forecasting
¿ä¾à2 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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DOI http://doi.org/10.5207/JIEIE.2022.36.6.009