Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal Indonesian Journal of Electrical Engineering and Computer Science
Motaz Daadoo
Palestine Technical University

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Forecasting for smart energy: an accurate and effificient negative binomial additive model Yousef-Awwad Daraghmi; Eman Yaser Daraghmi; Motaz Daadoo; Samer Alsaadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 2: November 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i2.pp1000-1006

Abstract

Smart energy requires accurate and effificient short-term electric load forecasting to enable effificient energy management and active real-time power control. Forecasting accuracy is inflfluenced by the char acteristics of electrical load particularly overdispersion, nonlinearity, autocorrelation and seasonal patterns. Although several fundamental forecasting methods have been proposed, accurate and effificient forecasting methods that can consider all electric load characteristics are still needed. Therefore, we propose a novel model for short-term electric load forecasting. The model adopts the negative binomial additive models (NBAM) for handling overdispersion and capturing the nonlinearity of electric load. To address the season ality, the daily load pattern is classifified into high, moderate, and low seasons, and the autocorrelation of load is modeled separately in each season. We also consider the effificiency of forecasting since the NBAM captures the behavior of predictors by smooth functions that are estimated via a scoring algorithm which has low computational demand. The proposed NBAM is applied to real-world data set from Jericho city, and its accuracy and effificiency outperform those of the other models used in this context.
Co-Authors Eman Yaser Daraghmi Samer Alsaadi Yousef-Awwad Daraghmi