Enhancing the self-consumption of photovoltaic (PV) energy is essential for attaining energy sustainability and diminishing reliance on traditional thermal electricity generation. This work presents a load shaping optimization strategy to improve the utilization of photovoltaic (PV) power in consumer-side energy management systems (EMS) that incorporate distributed PV panel generation and energy storage systems (ESS). The approach represents customizable load operating schedules as rectangular blocks, utilizing their flexibility to synchronize energy consumption with PV output profiles. The suggested optimization methodology defines the scheduling issue as a mixed-integer linear programming (MILP) model. The aim is to optimize PV power self-consumption by reducing the disparity between PV output and modified load profiles, while complying with limitations like load device working hours, consecutive operation mandates, energy storage system (ESS) capacity, and base load consumption. A simulation study is done to test the method's performance, using 10 changeable loads, a 100 kW PV panel system, and a 50 kWh energy storage system. Simulation findings indicate that the suggested strategy markedly enhances PV power utilization relative to random load operation. This method optimizes the load profile to align with the PV output, hence increasing self-consumption and reducing the excess PV power stored in the energy storage system. The customized schedules synchronize peak load operation with PV power peak output, thereby diminishing the grid contracted power and enhancing energy efficiency. This paper emphasizes the practical advantages of incorporating load shaping techniques into energy management systems for smart buildings and industrial facilities, facilitating the wider deployment of renewable energy sources. The results offer significant understanding for attaining carbon neutrality and complying with regulations for green energy use.