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Authors: Q. Gao 1 ; Y. Su 2 ; L. B. Wu 3 and Y. Zhou 3

Affiliations: 1 Fudan University, School of Computer Science and Yangpu District, China ; 2 State Grid Shanghai Municipal Electric Power Company, Pudong New District and Shanghai, China ; 3 Fudan University, School of Computer Science, Yangpu District, Fudan University, School of Economics, Yangpu District, Shanghai 200433 and, China

Keyword(s): appliances level forecast;energy saving;high accuracy

Abstract: Accurately forecasting the electricity demand and feedback on separate appliances can lead to natural energy-saving behaviors and higher energy efficiency. In this paper, a supervised additive factor hidden Markov model including the exogenic influencing factors is developed to forecast the electricity usage of appliance in building based on the hourly data, where the model is trained with the first part of appliances data to get optimized parameters and tuned with aggregate electricity data in forecasting. The model successfully forecast the usage of all appliances for a mall building and the accuracies for appliances are all larger than 60%, which is higher than most similar analyses, especially same frequency data analysis. By adding the influence factors, the AFHMM model gives a more accurate result in lower frequency data, which can be widely used in energy monitoring of buildings.

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Paper citation in several formats:
Gao, Q.; Su, Y.; Wu, L. and Zhou, Y. (2018). Forecasting Electricity Consumption of Appliances based on the Additive Factor Hidden Markov Model. In Proceedings of the International Workshop on Environmental Management, Science and Engineering - IWEMSE; ISBN 978-989-758-344-5, SciTePress, pages 193-200. DOI: 10.5220/0007558801930200

@conference{iwemse18,
author={Q. Gao. and Y. Su. and L. B. Wu. and Y. Zhou.},
title={Forecasting Electricity Consumption of Appliances based on the Additive Factor Hidden Markov Model},
booktitle={Proceedings of the International Workshop on Environmental Management, Science and Engineering - IWEMSE},
year={2018},
pages={193-200},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007558801930200},
isbn={978-989-758-344-5},
}

TY - CONF

JO - Proceedings of the International Workshop on Environmental Management, Science and Engineering - IWEMSE
TI - Forecasting Electricity Consumption of Appliances based on the Additive Factor Hidden Markov Model
SN - 978-989-758-344-5
AU - Gao, Q.
AU - Su, Y.
AU - Wu, L.
AU - Zhou, Y.
PY - 2018
SP - 193
EP - 200
DO - 10.5220/0007558801930200
PB - SciTePress

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