Realistic Home Energy Management System Considering the Life Cycle of Photovoltaic and Energy Storage Systems

Home Energy Management Systems (HEMSs) have become necessary due to energy security and climate change concerns. Scheduling the operating time of household appliances is one most effective strategies used by HEMSs reduce electricity costs, with several studies proposing optimization for scheduling home grid usage cost. This work considers costs from Renewable Sources (RESs) Storage (ESSs) in appliance-scheduling strategy flow management. The objectives are reducing real cost while maintaining a longer battery lifespan, charging/discharging losses, using PV power efficiently. To achieve this, we developed pricing model usage, addition modeling based on Levelized Cost (LCOE) systems. PV-battery models were introduced into problem solved Augmented Grey Wolf Optimization (AGWO) Particle Swarm (PSO) algorithms MATLAB. We an efficient management algorithm. collected data Vigo, Spain, simulated four scenarios. results show that proposed system AGWO PSO reduced 25.87% 25.98%, respectively. Compared existing energy-usage-pricing model, losses 40.429% extended lifespan 68.282%. Similarly, 45.540% 84.56%. Moreover, reached breakeven point shorter time.