Is Urbanisation Rate a Feasible Supplemental Parameter in Forecasting Electricity Consumption in China?

Joint Authors

Yang, Biao
Li, Yingcheng
Wei, Haokun
Lu, Huan

Source

Journal of Engineering

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-7, 7 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-01-20

Country of Publication

Egypt

No. of Pages

7

Main Subjects

Civil Engineering

Abstract EN

Traditional method of forecasting electricity consumption based only on GDP was sometimes ineffective.

In this paper, urbanisation rate (UR) was introduced as an additional predictor to improve the electricity demand forecast in China at provincial scale, which was previously based only on GDP.

Historical data of Shaanxi province from 2000 to 2013 was collected and used as case study.

Four regression models were proposed and GDP, UR, and electricity consumption (EC) were used to establish the parameters in each model.

The model with least average error of hypothetical forecast results in the latest three years was selected as the optimal forecast model.

This optimal model divides total EC into four parts, of which forecasts can be made separately.

It was found that GDP was only better correlated than UR on household EC, whilst UR was better on the three sectors of industries.

It was concluded that UR is a valid predictor to forecast electricity demand at provincial level in China nowadays.

Being provided the planned value of GDP and UR from the government, EC in 2015 were forecasted as 131.3 GWh.

American Psychological Association (APA)

Yang, Biao& Li, Yingcheng& Wei, Haokun& Lu, Huan. 2016. Is Urbanisation Rate a Feasible Supplemental Parameter in Forecasting Electricity Consumption in China?. Journal of Engineering،Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1108356

Modern Language Association (MLA)

Yang, Biao…[et al.]. Is Urbanisation Rate a Feasible Supplemental Parameter in Forecasting Electricity Consumption in China?. Journal of Engineering No. 2016 (2016), pp.1-7.
https://search.emarefa.net/detail/BIM-1108356

American Medical Association (AMA)

Yang, Biao& Li, Yingcheng& Wei, Haokun& Lu, Huan. Is Urbanisation Rate a Feasible Supplemental Parameter in Forecasting Electricity Consumption in China?. Journal of Engineering. 2016. Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1108356

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1108356