Citation

Sarker, Md. Tanjil and Alam, Mohammed Jaber and Ramasamy, Gobbi and Nasir Uddin, Mohammed (2024) Energy demand forecasting of remote areas using linear regression and inverse matrix analysis. International Journal of Electrical and Computer Engineering (IJECE), 14 (1). p. 129. ISSN 2088-8708

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Abstract

Efficient energy demand forecasting is pivotal for addressing energy challenges in remote areas of Bangladesh, where reliable access to energy resources remains a concern. This study proposes an innovative approach that combines linear regression analysis (LRA) and inverse matrix calculation (IMC) to forecast energy demand accurately in these underserved regions. By leveraging historical energy consumption data and pertinent predictors, such as meteorological conditions, population dynamics, economic indicators, and seasonal patterns, the model provides reliable forecasts. The application of the proposed methodology is demonstrated through a case study focused on remote regions of Bangladesh. The results showcase the approach's effectiveness in capturing the intricate dynamics of energy demand and its potential to inform sustainable energy management strategies in these remote areas. This research contributes to the advancement of energyplanning and resource allocation in regions facing energy scarcity, fostering a path towards improved energy efficiency and development. These techniques can be applied to estimate short-term electricity demand for any rural or isolated region worldwide

Item Type:	Article
Uncontrolled Keywords:	Electrical power
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1001-1841 Production of electric energy or power. Powerplants. Central stations
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	04 Mar 2024 02:11
Last Modified:	04 Mar 2024 02:11
URII:	http://shdl.mmu.edu.my/id/eprint/12152

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