@inproceedings{0474f9c754d549acab0d6a380ce5daa2,
title = "Statistical analysis of power systems and application to load forecasting",
abstract = "For many years, Load Forecasting (LF) has been an area of intense research. Most research has focused on short and long-term forecasting, with {"}short-term{"} generally meaning one hour in advance, to enable some power grid operations tasks. However, finer-grained prediction, at a resolution of minutes, can assist with other tasks, such as Power System State Estimation, and matching load to renewable energy generation in developing Smart Grids. To allow such ephemeral-term prediction with high accuracy, analysis of historical data sampled at high frequency is necessary. In this paper, we present statistical analysis based on three years' worth of real data obtained from the New York Independent System Operator (NYISO). The data is fine-grained, at a resolution of one sample per five minutes. The advantage of this data set is the ability to verify the applicability of our results to both large and small systems. The data and analysis presented in this paper can be used as a baseline for future LF and Smart Grid research.",
keywords = "Load forecasting, Load modeling, Power systems, Smart Grid",
author = "Yakir Loewenstern and Liran Katzir and Doron Shmilovitz",
note = "Publisher Copyright: {\textcopyright} Copyright 2015 IEEE All rights reserved.; 2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014 ; Conference date: 03-12-2014 Through 05-12-2014",
year = "2014",
doi = "https://doi.org/10.1109/EEEI.2014.7005879",
language = "الإنجليزيّة",
series = "2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014",
address = "الولايات المتّحدة",
}
