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Correlation analysis reveals that sunshine, global radiation, and temperature significantly influence energy consumption in London, indicating a complex interaction of environmental factors.
After the industrial revolution, and entering the 21stcentury, energy consumption has grown more rapidly than expected as the usage of technology and machines for both commercial and residential purposes continuously increase. An inevitable consequence is the artificial damage of natural environment which could lead to climate change in certain areas. On the other hand, the variation of climate and weather conditions could also influence energy use. Hence, how do they correlate with each other becomes a more noticeable issue nowadays. In this paper, a regional weather and energy dataset in London is chosen, and by using Pearson Coefficient, a correlation analysis is implemented between weather parameters and energy consumption. The result show that out of various weather variables, sunshine, global radiation and temperature take the highest weight in influencing the household energy demand in London. These three factors are then used to fit a linear regression model to further emphasize their sensitivity level to energy consumption.
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Bowei Wang (2025) studied this question.
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