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Forecasting Pakistan's electricity based on improved discrete grey polynomial model

Dang Luo (School of Mathematics and Statistics, North China University of Water Resource and Electric Power, Zhengzhou, China)
Muffarah Ambreen (School of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, China)
Assad Latif (School of Management and Economics, North-China University of Water Conservancy and Electric Power, Zhengzhou, China)
Xiaolei Wang (School of Mathematics and Statistics, North China University of Water Resources and Electric Power, Zhengzhou, China)

Grey Systems: Theory and Application

ISSN: 2043-9377

Article publication date: 14 May 2020

Issue publication date: 19 May 2020

154

Abstract

Purpose

Electricity plays an important role in the economic condition of any country. Nowadays, Pakistan is badly affected by shortage of electricity, which directly affected the economic growth of state. The purpose of this study is to propose an improved grey model DGPM(1,1,N) to forecast Pakistan's production of electricity, installed capacity and consumption.

Design/methodology/approach

To significantly simulate and predict accuracy, the discrete grey polynomial model DGPM(1,1,N) is improved with new information priority accumulation. The particle swarm optimization (PSO) algorithm is used for parameter optimization. The value of parameter is adjusted into improved grey model. By adjusting the parameter value in the model, the accuracy of prediction is enhanced.

Findings

The installed capacity of electricity needs more attention to improvement through implementation of effective polices, resolving major issues and funding scheme to fulfill the electricity demand of country. And improved DGPM(1,1,N) has better accuracy than original DGPM(1,1,N), DGM(1,1), nongrey models, linear regression and Holt–Winters methods.

Practical implications

This paper provides a practical and efficient improved grey method to predict the electricity production, consumption and installed capacity in Pakistan. This research and suggestion will help Pakistani government to formulate better policies to decrease the consumption of electricity and increase the installed capacity of electricity.

Originality/value

This paper not only improves the grey model with accumulation generation operator but also forecasts Pakistan's electricity production, installed capacity and consumption. It is a new idea to predict the installed capacity of electricity and the findings provide suggestions for the government to make policies.

Keywords

Acknowledgements

This research is supported by National Natural Science Foundation of China under Grant (No. 51979106), Scientific and Technological Plan Fund Project of Henan Province under Grant (No. 182102310014), Key Research Project Plan of Henan Universities under Grant (No.18A630030) and the Quality Curriculum of Postgraduate Education in Henan Province (Grey System Theory under Grant HNYJS2015KC02).

Citation

Luo, D., Ambreen, M., Latif, A. and Wang, X. (2020), "Forecasting Pakistan's electricity based on improved discrete grey polynomial model", Grey Systems: Theory and Application, Vol. 10 No. 2, pp. 215-230. https://doi.org/10.1108/GS-12-2019-0060

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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