Forecasting India’s Electricity Demand Using a Range of Probabilistic Methods

Yeqi An,Rongrong Li,Yulin Zhou

doi:10.3390/en12132574

Yeqi An, Rongrong Li + Show 1 more

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https://doi.org/10.3390/en12132574

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Journal: Energies	Publication Date: Jul 4, 2019
Citations: 7	License type: CC BY 4.0

Affiliation: China University of Petroleum, East China

Abstract

With serious energy poverty, especially concerning power shortages, the economic development of India has been severely restricted. To some extent, power exploitation can effectively alleviate the shortage of energy in India. Thus, it is significant to balance the relationship between power supply and demand, and further stabilize the two in a reasonable scope. To achieve balance, a prediction of electricity generation in India is required. Thus, in this study, five methods, the metabolism grey model, autoregressive integrated moving average, metabolic grey model-auto regressive integrated moving average model, non-linear metabolic grey model and non-linear metabolic grey model-auto regressive integrated moving average model, are applied. We combine the characteristics of linear and nonlinear models, making a prediction and comparison of Indian power generation. In this way, we enrich methods for prediction research on electrical energy, which avoids large errors in trends of electricity generation due to those accidental factors when a single predictive model is used. In terms of prediction outcomes, the average relative errors from five models above are 1.67%, 1.62%, 0.84%, 1.84%, and 1.37%, respectively, which indicates high accuracy and reference value of these methods. In conclusion, India’s power generation will continue to grow with an average annual growth rate of 5.17% in the next five years (2018–2022).

Highlights

With rapid development of the economy, the aggregate energy consumption of the world continues growing correspondingly
When MGM (1,1) is modeled, the original data is first accumulated, and the new sequence is analyzed by differential equations to achieve short-term prediction
From 1999 to 2001, India’s power generation growth rate dropped significantly by about 6%, and it was able to rebound to the average level after 2003

Summary

Introduction

With rapid development of the economy, the aggregate energy consumption of the world continues growing correspondingly. The ratio of electricity generation to whole energy consumption has increased due to the substitution of traditional fossil energy. As the third largest economy in Asia, the study of power development in India is becoming more and more significant. India will soon become the most populous country in the world [1]. Population in this country is 1.304 billion. With a massive scale of population and market, the “Economic Times” of India reported that in 2017 there were still more than 300 million people living in rural areas of India without electricity. More than 18,000 villages failed to be powered [2]

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Conclusion