GTS Press Journal of Sustainable Energy Environment and Green Technologies 1 1 2026 08 04 Mitigating Renewable Power Fluctuations through Adaptive Predictive Control for Grid Stability Enhancement 41 60 34 EN JSEEGT Author 3 Independent Researcher Journal Article 2026 06 25 The swift incorporation of renewable energy technologies like solar and wind power increases the sustainability of power production in contemporary smart grids. Nonetheless, renewable intermittency, power variations, voltage instability, frequency fluctuation, and power imbalances have a huge impact on grid reliability and resilience. The Adaptive Predictive Renewable Stability Network (APRSN), which is proposed as an integrated intelligent structure to manage renewable energy sources for power networks, is designed to solve these issues. APRSN consists of renewable energy prediction, Adaptive Predictive Control (APC), Renewable Stability Index (RSI)-based stability analysis, Battery Energy Storage System (BESS) management, and adaptive optimization, which are all implemented with the one architecture. APRSN gathers instantaneous renewable, load, voltage, frequency, and weather data from smart grid networks, analyzes the future status of generation and demand, evaluates the stability of the power network using RSI, and then optimally controls the system. Furthermore, BESS charges and discharges energy depending on the power balance. Experimental evaluation proves excellent results for the proposed method in terms of 99.1% forecasting accuracy, voltage, and frequency stability, power fluctuations, renewable usage, and resilience. #