Title : ( Designing Commercial Short-term Load Forecasting Software using Hybrid ANN-ARIMA Forecasting Engine )
Authors: atefeh zomorodi moghadam , Masoud Rezvanian , Ali Yektay , Mohammad Hossein Javidi Dasht Bayaz ,
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Abstract
This paper presents a smart forecasting software with the aim to predict short term electricity load. For this purpose, different forecasting engines have been utilized to reduce error. In order to devise a commercial software which can be helpful for participants of electricity market, the real constraints of these players have been considered, too. The feasibility of proposed framework is studied on a case of Mashhad electricity load data.
Keywords
, load forecasting, distrirution companies, forecasting error
@inproceedings{paperid:1066051,
author = {Zomorodi Moghadam, Atefeh and Rezvanian, Masoud and Ali Yektay and Javidi Dasht Bayaz, Mohammad Hossein},
title = {Designing Commercial Short-term Load Forecasting Software using Hybrid ANN-ARIMA Forecasting Engine},
booktitle = {32امین کنفرانس بین المللی برق},
year = {2017},
location = {تهران, IRAN},
keywords = {load forecasting; distrirution companies; forecasting error},
}
%0 Conference Proceedings
%T Designing Commercial Short-term Load Forecasting Software using Hybrid ANN-ARIMA Forecasting Engine
%A Zomorodi Moghadam, Atefeh
%A Rezvanian, Masoud
%A Ali Yektay
%A Javidi Dasht Bayaz, Mohammad Hossein
%J 32امین کنفرانس بین المللی برق
%D 2017
