Proceedings of the 2015 2nd International Forum on Electrical Engineering and Automation (IFEEA 2015)

Heat Load Forecasting of District Heating System Based on Numerical Weather Prediction Model

Authors
Hongying Yang, Shuanglong Jin, Shuanglei Feng, Bo Wang, Fei Zhang, Jianfeng Che
Corresponding Author
Hongying Yang
Available Online January 2016.
DOI
https://doi.org/10.2991/ifeea-15.2016.1How to use a DOI?
Keywords
Heating Load Forecast; Numerical Weather Prediction; Artificial Neural Network; Temperature; Weather Forecast
Abstract
This paper reports an application of Numerical Weather Prediction (NWP) in the heat load forecasting field. The NWP is applied to obtain the correlated weather parameters of the heat load, and then the properly structured Artificial Neural Network (ANN) model is designed to perform the prediction. Satisfactory experimental results are obtained by using actual heat load data in the north of China. The experimental result shows that the proposed NWP based method can predict the heat load precisely. Comparing with the traditional weather forecast based-method, the proposed method can effectively improve the forecasting accuracy.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2015 2nd International Forum on Electrical Engineering and Automation (IFEEA 2015)
Part of series
Advances in Engineering Research
Publication Date
January 2016
ISBN
978-94-6252-153-7
ISSN
2352-5401
DOI
https://doi.org/10.2991/ifeea-15.2016.1How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Hongying Yang
AU  - Shuanglong Jin
AU  - Shuanglei Feng
AU  - Bo Wang
AU  - Fei Zhang
AU  - Jianfeng Che
PY  - 2016/01
DA  - 2016/01
TI  - Heat Load Forecasting of District Heating System Based on Numerical Weather Prediction Model
BT  - 2015 2nd International Forum on Electrical Engineering and Automation (IFEEA 2015)
PB  - Atlantis Press
SP  - 1
EP  - 5
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifeea-15.2016.1
DO  - https://doi.org/10.2991/ifeea-15.2016.1
ID  - Yang2016/01
ER  -