Treffer: Optimal Control of Wind Energy Conversion System Output Based on Adaptive Dynamic Programming.

In today's energy sector, wind power has risen to prominence as a key renewable resource, appreciated for its eco-friendliness, sustainability, and minimal environmental footprint. Over recent decades, its adoption has surged, making it the fastest-growing option among renewable energy sources. Wind energy is captured and transformed into electricity via Wind Energy Conversion Systems (WECS), which predominantly rely on wind turbines. WECS can be divided into two main categories based on their interaction with power grids: grid-connected systems and stand-alone wind energy systems. Currently, most wind energy installations are grid-connected, facilitating efficient integration and distribution of the generated electricity. The control systems for WECS are intricate, necessitating advanced optimization methods to improve the effectiveness of wind energy conversion. This paper introduces an innovative approach to crafting an adaptive optimal controller based on Adaptive Dynamic Programming (ADP), aimed at enhancing energy conversion efficiency for grid-connected wind energy systems that use Permanent Magnet Synchronous Generators (PMSG). The proposed controller leverages reinforcement learning techniques along with Lyapunov stability analysis to guarantee dependable performance across a range of operational scenarios. To demonstrate the controller's effectiveness, we implemented and simulated a complete system comprising both the WECS and the controller in the Matlab and Simulink environments. The outcomes of these simulations will be evaluated to determine the controller's performance and its potential to boost the overall operational efficiency of wind energy systems. [ABSTRACT FROM AUTHOR]