@inproceedings{cde104d081d34f07a20a0dd4a8524673,
title = "Electricity price and demand forecasting under smart grid environment",
abstract = "In this paper, the development of electricity price and demand forecasting, with the emergence of demand response programs, is investigated. Short Term Load/Price Forecasting (STL/PF) is performed for an electricity market that offers Demand Response (DR) Programs. The change in the forecasting errors, of both electricity price and demand, over years of inactive and active DR is monitored. Commonly used prediction methods, namely; Least Squares-Support Vector Machines (LS-SVM), and Random Forests (RF), are used for forecasting, to ensure the generality of the results. The Australian National Electricity Market (ANEM), specifically Victoria region, is used as a subject case study. It was concluded that adding DR programs decreases the volatility of electricity price, with no validated effect on demand.",
keywords = "Demand Response, Electricity Market, Forecasting, Power Demand, Smart Grid",
author = "Dina Masri and Hatem Zeineldin and Woon, \{Wei Lee\}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 15th IEEE International Conference on Environment and Electrical Engineering, EEEIC 2015 ; Conference date: 10-06-2015 Through 13-06-2015",
year = "2015",
month = jul,
day = "22",
doi = "10.1109/EEEIC.2015.7165472",
language = "British English",
series = "2015 IEEE 15th International Conference on Environment and Electrical Engineering, EEEIC 2015 - Conference Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1956--1960",
booktitle = "2015 IEEE 15th International Conference on Environment and Electrical Engineering, EEEIC 2015 - Conference Proceedings",
address = "United States",
}