(untitled) (International Journal of Communication Systems and Network Technologies, 2024)
Energy optimization important problems in a smart grid setting, with user experience improvement, controlling battery energy storage, and load scheduling, are tackled in this paper. The efficiency of controllers in maximizing energy generation, user comfort, load scheduling, and real-time battery backup scheduling depends on system inputs, including dynamic pricing signals, load arrival dynamics, battery charging and discharging dynamics, and processes for producing renewable and conventional grid energy. To explore these issues, the virtual queue safety (LOT) based Lyapunov optimization approach is used in a grid-connected green smart home with an HVAC load. The main goal is to reduce the total time-averaged energy cost and the cost of thermal discomfort over a longer period. Variations in the number of occupants in the house, desired temperature circumstances, electrical consumption, output from renewable energy sources, outside temperature, and power prices are all considered in this optimization. The suggested method creates and maintains four queues for the electrical energy storage system (ESS), EV charging, and interior temperature. The algorithm’s efficacy is verified through extensive simulations. Simulation results show that the suggested strategy satisfies the user’s energy and comfort needs while achieving real-time energy optimization and a 20.15% decrease in the time-averaged energy cost.