This study proposes intelligent control strategies for optimizing the grid integration of photovoltaic (PV) and wind energy in hybrid systems using an adaptive neuro-fuzzy inference system (ANFIS). terest in hybrid renewable energy systems involving the solar and wind resources. Their intermittent and nonlinear natures, however, pose great challenges w th regards to quality of. The research deploys proportional integral derivative controllers for voltage regulation, and fuzzy logic controllers as intelligent management. However, the intermittent and fluctuating nature of these energy sources leads to unstable power output, negatively impacting supply reliability and power quality. By integrating Maximum Power Point Tracking (MPPT) techniques, the system maximizes efficiency, while the ANFIS-based controller ensures adaptive management.
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