Load Management Strategy for Residential Stand-Alone Photovoltaic Systems using Mixed-Integer Linear Programming

Accessibility to electricity has been a pain point to residential end-users mostly in remote and rural areas due to high installation costs and high tariff rates. This paper presents a standalone PV system for a typical residential building that incorporates load management using mixed-integer linear programming. This was evaluated by taking the energy profile of a building and using forecasted solar irradiance to obtained optimal sizing of PV and battery system. The appliances considered under this study were classified into controllable and uncontrollable as prescribed by the owner. The scheduling pattern of appliances was modeled using the mixed-integer linear programming constrained due to battery state of charge, season variation, and present load demand. Three cases were considered during the implementation of this study, the initial capacity of the battery bank was rated at 25kWh, the battery state of charge (SOC) was maintained at less than 50% of its capacity throughout the cases, also, the demand satisfaction of the end-users varies between 78%-88% which ensures higher weighted appliances in terms of priority were guaranteed for operation. The significance of this paper is to enable residential users to improve their standard of living with respect to an available and accessible source of power (photovoltaic system) with optimal scheduling of appliances