Blinds systems, daylighting, natural convection, and shielding thermostat from heating appliances are known to reduce electricity consumption, reduce energy wastage, reduce energy bills, reduce spurious errors in thermostatic controls, reduces over-heating of compressors, reduces the incidence of burnt motors, and fire hazards. Predictive modeling using the multivariate logistic stepwise statistical procedure selects from a set of independent variables of electricity load management survey data gathered from Windhoek City, Namibia to develop the best and optimal model in the study. The results indicate that keeping heat-producing appliances away from the thermostat so that it can give accurate readings is highly interconnected to using blinds systems to reduce inlet heat in summer and heat loss in cold months. Also, small changes in data values can lead to large coefficient estimates and there is a perfect (100.0%) correlation between the dependent and independent variables. In addition, the proportion of the variance explained in the developed model was 97.0%. However, there were also no multicollinearity problems in the data and the developed model was optimal and fairly accurate.
Keywords blinds systems, daylighting, energy balance, energy consumption, energy savings, waste reduction