In Bangladesh's distant regions, where dependable access to energy supplies is still an issue, effective energy consumption forecasting is essential for tackling the country's energy problems. In order to anticipate energy consumption in these neglected areas effectively, this study suggests a novel method that combines inverse matrix method (IMM) with linear regression method (LRM). The model produces accurate estimates by using historical data on energy use and relevant factors, such as weather patterns, population dynamics, economic indicators, and seasonal trends. A case study focusing on distant areas in Bangladesh shows how the proposed technique might be applied. The outcomes indicate how well the method captures the complex patterns of energy demand and how it may be used to guide sustainable energy management plans in these outlying regions. This study advances energy planning and resource allocation in areas with a limited supply of energy, paving the way for increased development and efficiency of the energy sector. Any rural or remote area in the globe can use these strategies to predict their short-term power consumption.
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