Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Bidong Liu"'
Publikováno v:
International Journal of Forecasting. 32:585-597
Temperature plays a key role in driving the electricity demand. We adopt the “recency effect”, a term drawn from psychology, to represent the fact that the electricity demand is affected by the temperatures of the preceding hours. In the load for
Publikováno v:
Energy. 98:40-49
Although combining forecasts is well-known to be an effective approach to improving forecast accuracy, the literature and case studies on combining electric load forecasts are relatively limited. In this paper, we investigate the performance of combi
Publikováno v:
2015 North American Power Symposium (NAPS).
The NPower Forecasting Challenge 2015 invited students and professionals worldwide to predict daily energy usage of a group of customers. The BigDEAL team from the Big Data Energy Analytics Laboratory landed a top 3 place in the final leaderboard. Th
Although combining forecasts is well-known to be an effective approach to improving forecast accuracy, the literature and case studies on combining load forecasts are very limited. In this paper, we investigate the performance of combining so-called
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______645::260f05ed491d6af36d91dfa374d5c02c
http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/wpaper/HSC_15_05.pdf
http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/wpaper/HSC_15_05.pdf
This paper introduces the concept of sister models, and proposes a sister model based load forecast combination method to enhance the point forecasting accuracy. Using the data from the Global Energy Forecasting Competition 2014, we create a case stu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______645::f52e6c6982fb7458209abd3533997692
http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/wpaper/HSC_15_02.pdf
http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/wpaper/HSC_15_02.pdf
Majority of the load forecasting literature has been on point forecasting, which provides the expected value for each step throughout the forecast horizon. In the smart grid era, the electricity demand is more active and less predictable than ever be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c08bbbe76d37c2bf1b736556492198a
http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/wpaper/HSC_15_01.pdf
http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/wpaper/HSC_15_01.pdf