Optimizing Sustainable Power Delivery in Sensor Networks through Hybrid Energy Harvesting for Autonomous Energy Storage Solutions

The increasing proliferation of low-power embedded systems and Internet of Things (IoT) devices, especially in remote or energy-constrained environments, has intensified the demand for sustainable and autonomous energy solutions. Traditional battery-powered systems face limitations in longevity, maintenance, and environmental adaptability, prompting the exploration of alternative energy harvesting techniques. This study investigates four energy harvesting methods—solar, vibration, radio frequency (RF), and capacitor-based storage—to evaluate their performance and suitability for reliable power delivery in such applications. MATLAB simulations were employed to model the energy output of each technique across a normalized input range (0 to 1), ensuring a consistent basis for comparison. Results showed that solar energy harvesting, using an 18% efficient photovoltaic panel with a 0.02 m² surface area, and vibration-based systems with 150 N/m stiffness and 0.002 m displacement, both achieved a normalized peak output of 1.0. RF harvesting, utilizing 1 W transmission power and a gain of 2 at both ends, performed less efficiently with a peak below 0.4. Capacitor storage, modeled with a 0.01 F capacitor over a 1V to 5V voltage range, demonstrated a parabolic output curve with peak performance at mid-range inputs. These results highlight the potential of integrating solar and vibration energy harvesting methods, complemented by capacitor-based buffering, to form robust hybrid power systems. The study contributes to knowledge by providing a comparative performance analysis of multiple harvesting techniques under standardized conditions and offers design insights for engineers developing energy-resilient embedded and sensor-based applications. The implications suggest that hybrid energy systems, supported by smart energy management strategies, can significantly enhance the operational autonomy, reliability, and sustainability of next-generation IoT deployments.