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 60 88 34 EN JSEEGT Author 3 Independent Researcher Journal Article 2026 06 25 The fast adoption of renewable sources such as solar and wind energy increases sustainability in electricity generation in modern smart grids but leads to problems related to intermittency, power fluctuation, voltage instabilities, frequency changes and power imbalance that may impact the reliability and resilience of the grid. In order to solve these problems, the research proposed an Adaptive Predictive Renewable Stability Network (APRSN), which is an intelligent system for renewable energy management and increased grid stability. The APRSN integrates renewable power prediction, Adaptive Predictive Control (APC), Renewable Stability Index (RSI) based grid stability evaluation, Battery Energy Storage System (BESS) coordination and adaptive optimization into one system. APRSN constantly analyzes the information on renewable generation, demand, voltage, frequency, weather and battery states to predict the future state of the grid, evaluate its stability and take necessary control actions. The BESS coordination takes place depending on power imbalances in order to store extra renewable power and used the grid with generation deficit. The experimental evaluation of APRSN showed 99.1% accuracy of forecasting along with the improved voltage and frequency stability, reduction of renewable power fluctuations and higher renewable energy utilization and strengthening grid resilience. The results demonstrate the potential of APRSN as an integrated approach for reliable renewable-energy management in smart-grid environments. #