One challenge facing the utility is management of peak demands. Demand response management has proven to be a significant way of reducing these peaks. Scheduling of electrical appliances and proper design of the electricity tariffs are some of the mechanisms used in demand response management to reduce these peaks. It was therefore the aim of this study to come out with scheduling scheme to reduce peaking in the grid taking into account occupancy error detection factor. In this study a mixed integer linear programming based smart appliance scheduling scheme with real-time pricing and algorithm to service as motion sensor were proposed. Significant savings on the community's electricity bill were realized using the proposed schemes. Savings made on occupancy error detection alone were not significant compared to the total power consumed by the community, but it must be realized that this is just a conceptual study and it does not represent reality. It was therefore recommended that the proposed scheduling scheme incorporating occupancy error detection mechanism should be deployed in a real community of residential housing and simulated in realistic conditions. Read more