Statistical analysis of environment and climate drifts on energy profile of smart grid consumers

Energy consumption is directly affected by living standards and lifestyles of the consumers. Energy profiles of different smart grid consumers, such as (a) Residential, (b) Commercial, and (c) Industries directly relates to climate drift, weather parameters, and environment. Keeping in mind the aforesaid factors, there is an emergent need of designing correlation models for demand and weather parameters namely: (a) Dry Bulb Temperature, (b) Relative Humidity, (c) Dew Point, (d) Cloud Cover, and (e) Wind Speed. In this paper, we discussed different environmental and weather parameters that affect consumer demand. Moreover, correlation models are developed, such as (a) Spearman, (b) Pearson, and (c) Kendall, an interrelation between weather drift (independent), demand (load, dependent parameter), and month (January and June). Furthermore, we considered United State (Texas), and month of each season for more validation and evaluating the relation between the demand and weather parameters.