Appliance scheduling optimization with micro-grid in smart home network

The fast emerging smart grid technology provides greater information flow, flexibility and control to both electricity consumers and electricity suppliers. Of these benefits, the two way flow of information between consumer and electricity producer in smart grid opened new vistas of applications. Smart home appliances are connected to home area network (HAN) to co-ordinate power usage demanded for the home under control. We are, therefore, witnessing an increasing interest in smart homes from the point of view of optimal energy management, renewable green energy sources and smart appliances. Hence, the problem of scheduling of smart appliances operations in a given time range with set of energy sources like national grid and local generation micro-grid is investigated in this thesis. Renewable energy source that is adopted in this thesis is a photovoltaic panel as a power producing appliance. Appliance operation is modeled in terms of un-interruptible sequence phases, given in load demand profile with a goal of minimizing electricity cost fulfilling duration, energy requirement, and user preference constraints. An optimization algorithm which can provide a schedule plan for smart home appliances usage is proposed based on the mixed integer linear programming technique. The effect of adding a photovoltaic system in the home results in reduction of electricity bill and the peak demand of the home and export of energy to the national grid in times when solar energy production is more than the demand of the home. The situation is modeled using Matlab with Yalmip library to exploit the state-of-the-art Gurobi solver for obtaining the timing of appliance scheduling in the smart home in comparable time to be true as real time process for demand side management.