Using blinds, day-lighting, and geyser temperature settings to reduce electricity consumption and pricing patterns in energy-efficient buildings

Depending on the building architecture, usage, and energy consumption patterns, over US$ 60 billion was expended annually on electric lighting in commercial buildings. Therefore, the paper focuses on the development of energy-efficient buildings that minimize energy consumption through integrated energy-efficient design processes. This can serve as a practical guide to design buildings that can lower the energy requirements and a strategy to reduce energy consumption. In this study, predictive analytics were used to examine how blinds, daylighting, and geyser temperature settings can reduce electricity consumption and pricing patterns. A panel of expert judges was used to validate the 5-point Likert scale residential electricity load management questionnaire used to gather survey data for the statistical analysis in a Windhoek suburb, Namibia. The main goal of this study was to investigate how blinds, day-lighting, and geyser temperature settings can be used to save energy, reduce electricity consumption, and costs for sustainable growth and development. The results from this investigation indicate a perfect Gaussian histogram of 15 electricity price jumps confirming 15 four-way stepwise interaction effects. Optimal 0.5 Quetelet curve index offers average citizen energy efficiency awareness, education, and behavior modification for affordable electricity. Females generally set hotter geyser temperatures and are higher energy consumers. Blinds reduce electricity consumption by 50% in summer, 25% in winter, and day-lighting by 25%. These were the least cost and optimal solutions to the rising electricity consumption and pricing patterns problem. Adopting the findings or the outcomes of this paper could provide more optimal and sustainable energy consumption thereby reducing pressure on the power grid.