Forecasting Electricity Demand In Ghana With The Sarima Model

Authors

  • Prince Yaw Andoh Andoh Kwame Nkrumah University of Science and Technology
  • C. K. K. Sekyere Kwame Nkrumah University of Science and Technology
  • L. D. Mensah Kwame Nkrumah University of Science and Technology
  • D. E.K. Dzebre Kwame Nkrumah University of Science and Technology

DOI:

https://doi.org/10.37385/jaets.v3i1.288

Keywords:

Electricity demand, Forecasting SARIMA, Ghana

Abstract

Demand forecasting is a challenging subject of interest to many organizations whose main focus is to improve their steady growing customer request/demand, and help in increasing their revenue generation. The story is no different in the power industry. It is quite difficult for power or electrical producers to store high quantum of the energy produced, hence this poses a challenge in estimating precisely the quantum of electrical energy in order to equate demand and supply of powers as well as reducing or eliminating the rising transmission losses. This study explores potential time series models in electricity demand prediction or forecasting for the Western Regions of Ghana. Secondary data was sourced formally from the regional headquarters of ECG to aid in research design to be able to estimate the quantum of electricity needed by consumers in the region. This was done using time series data analysis toolpak software. Results show that the models formulated are viable for future consumption forecasts and other investment in alternative power source projects in meeting these future demands. Since there are up-surging energy demand patterns in the region, the flexibility of the formulated models can be very useful and supplementary to framing effective and efficient energy policies.

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Published

2021-12-23

How to Cite

Andoh, P. Y. A., C. K. K. Sekyere, L. D. Mensah, & D. E.K. Dzebre. (2021). Forecasting Electricity Demand In Ghana With The Sarima Model. Journal of Applied Engineering and Technological Science (JAETS), 3(1), 1–9. https://doi.org/10.37385/jaets.v3i1.288