Solar Energy System Simulation with Respect to Cybersecurity Using Decoy Device

The rapid expansion of renewable energy deployment has placed solar photovoltaic (PV) at the forefront of the clean power supply for the residential, commercial and industrial users. With their insertion into smart Grids, though these systems are facing increasing exposure to cyber physical threats to stability simulation and protection system that embedded with solar panels, inverters and battery management units along with smart sensing using LDR, PIR, IR, temperature sensors, and actuator responses through LED and buzzer notifications. A multi-layered cybersecurity framework is designed, including AI-powered anomaly detection for timely threat detection, blockchain-enabled decentralized logging to provide tamper-proof audit records, honeypot-derived decoy devices to divert attackers, and a Moving Target Defence (MTD) function for adaptive system reconfiguration against dynamic threats. The system is implemented on Raspberry Pi and ESP32 boards to facilitate real-time data acquisition, secure processing, and visualization of solar performance data, environmental parameters, and intrusion attempts. Experimental validation confirms the system's accurate estimation of solar irradiance, effective inverter–battery interaction, and strong intrusion resilience based on coordinated responses. Furthermore, the decoy-based deception method proposed in this work effectively misdirects adversaries from important resources while ensuring operational continuity. The findings identify a new paradigm for incorporating sustainable energy management with sophisticated cybersecurity measures and provide a resilient, scalable, and smart model for future decentralized smart grid infrastructures.