Artificial Intelligence–Driven Optimization of Integrated Solar Photovoltaic and Smart Home Systems: A Case Study of Residential Energy Efficiency and Predictive Maintenance in Photovoltaic Plus Energy Storage Systems

The integration of solar photovoltaic (PV) systems with smart home technologies represents a key strategy for addressing environmental challenges in residential energy management, such as high consumption, grid dependency, and equipment degradation. This case study is structured in two parts: the first examines the basic synergy between SunPower solar PV systems and energy-controlling smart home devices (e.g., thermostats, lights, and plugs), demonstrating a 24% reduction in household energy use and associated environmental benefits like lower carbon emissions. The second part advances this by incorporating an artificial intelligence–driven integration layer between Tesla Solar PV systems and Google Nest Smart Thermostats, enabling real-time optimization via API communication, predictive analytics, and weather forecasting while maintaining user-defined comfort levels. Simulations show 35% savings on HVAC operations (equating to an additional 15% total energy reduction), 20–30% equipment lifespan extension, and 15% maintenance cost reductions, yielding overall 39% energy savings and further minimizing environmental impacts. This prospective case, grounded in real-world data, offers interdisciplinary insights into sustainable energy transitions, with pedagogical tools for exploring technology, policy, and equity.