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Application of time series analysis in forecasting coal production and consumption in the philippines

By: Publication details: Chennai ICT Academy 2022Edition: Vol.13(1), OctDescription: 2798-2804pSubject(s): Online resources: In: ICTACT Journal on Soft Computing (IJSC)Summary: Energy is the backbone of a country’s economic and technological development. For a country to be competitive in the global market and secure sustainable development, energy must be efficiently used. The Philippines’s main source of energy is coal. Historical data shows that the country’s energy and coal consumption has been continuously increasing. With this, careful energy planning is required to develop policies that ensure sufficient energy supply in the future. This paper focuses on forecasting coal production and consumption in the Philippines. For the purpose of forecasting, the autoregressive integrated moving average (ARIMA) model is applied to reveal that ARIMA (1, 2, 0) is the best model to forecast coal production. For coal consumption, the best model identified was ARIMA (0, 2, 1). The models have undergone residual analyses and forecast evaluations to ensure that the ‘best’ models found are statistically appropriate models. The forecasts show that in the following years, Philippine coal production will decrease, while the coal consumption rate will increase. In addition, it is predicted that the Philippines will need to import a total of 133.1983 MMT of coal to meet the coal consumption from 2021 to 2025.
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Energy is the backbone of a country’s economic and technological
development. For a country to be competitive in the global market and
secure sustainable development, energy must be efficiently used. The
Philippines’s main source of energy is coal. Historical data shows that
the country’s energy and coal consumption has been continuously
increasing. With this, careful energy planning is required to develop
policies that ensure sufficient energy supply in the future. This paper
focuses on forecasting coal production and consumption in the
Philippines. For the purpose of forecasting, the autoregressive
integrated moving average (ARIMA) model is applied to reveal that
ARIMA (1, 2, 0) is the best model to forecast coal production. For coal
consumption, the best model identified was ARIMA (0, 2, 1). The
models have undergone residual analyses and forecast evaluations to
ensure that the ‘best’ models found are statistically appropriate models.
The forecasts show that in the following years, Philippine coal
production will decrease, while the coal consumption rate will increase.
In addition, it is predicted that the Philippines will need to import a total
of 133.1983 MMT of coal to meet the coal consumption from 2021 to
2025.

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