Geographically weighted regression analysis of electricity consumption in Indonesian households: aligning with SDG 7

Geographically weighted regression analysis of electricity consumption in Indonesian households: aligning with SDG 7

Electricity demand forecasting
Geographically weighted regression
Minimum wage levels
Population dynamics
Poverty rates
Regional GDP

The objective of this study is to establish a thorough comprehension of the interaction of population dynamics, poverty rates, minimum wage levels, and regional GDP in relation to household electricity consumption. The main objective is to improve the precision of electricity demand predictions and prevent planning mistakes, such as the considerable surplus of 6-7 GW in the Java Bali system between 2020 and 2023, resulting in major financial losses. We evaluate and compare the models by employing several approaches, such as ordinary least square (OLS) and geographically weighted regression (GWR) with fixed and adaptive bandwidths. We use modified R-squared and corrected Akaike Information Criterion (AICc) values for this assessment. The GWR with adaptive bandwidth is shown to be the most resilient method and is subsequently chosen for modeling. The results indicate that there is a strong correlation between the number of impoverished individuals and electricity use, with a coefficient range of 0.35-0.55. Furthermore, the correlation between poverty rates and power usage is defined by a coefficient that varies between -0.0010 and -0.0030. There is a direct relationship between regional GDP and power growth, as indicated by coefficients ranging from 1,000,000 to 5,000,000. Moreover, the impact of minimum wage levels differs among different locations.

Tommy Novianto1, Rezzy Eko Caraka1,2,3,4, Prana Ugiana Gio5, Rumanintya Lisaria Putri6, Agung Sutoto6, Rung Ching Chen4, Maengseok Noh7, Bens Pardamean8,9

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Aug 5, 2024

PERI IRAWAN

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