article · Cleaner Energy Systems
• This study describes the design and integration of a multi-loop method for a Wind Energy Conversion System (WECS) using an Active Disturbance Rejection Control (ADRC) and Proportional Integral Derivative (PI) controller. Then, using the reward function, the Integrated Time Absolute Error (ITAE), and Genetic Algorithm (GA) and Ant Colony Optimisation (ACO) were employed to achieve the optimal controllers’ settings in accordance with the needs of the poultry system. • In order to improve and optimise the efficiency of a Wind Energy Conversion System (WECS) that depends on a Permanent Magnet Synchronous Generator (PMSG), built to work under changing wind speed, this book provides a novel approach to Maximum Power Point Tracking (MPPT). • To confirm the efficacy of the suggested control strategies using the two optimisation algorithms for stabilisation and tracking setpoints, simulation tests were conducted using the Matlab Simulink toolbox. The ACO-ADRC controller continues to show noteworthy gains in terms of rising time, overshoot, settling time, and effective disturbance rejection even when many disturbances are introduced into the plant model, demonstrating the resilience of the recommended control strategy. This manuscript introduces an innovative Maximum Power Point Tracking (MPPT) strategy to improve the efficiency of Wind Energy Conversion Systems (WECS) equipped with Permanent Magnet Synchronous Generators (PMSG) under variable wind conditions. The proposed approach integrates Active Disturbance Rejection Control (ADRC) with the Perturb and Observe (P&O) algorithm, effectively addressing challenges such as external disturbances and fluctuating wind environments. By combining ADRC with P&O control, the system achieves enhanced tracking performance and adaptability.To validate the added value of this approach, we compare it with a traditional P&O strategy combined with Proportional Integral (PI) control. For the PI-based method, controller parameters Kp and Ki are optimized using Genetic Algorithm (GA) and Ant Colony Optimization (ACO) to enhance control precision. The Integrated Time Absolute Error (ITAE) objective function is employed to fine-tune these parameters, further optimizing system performance. Our analysis underscores the superiority of ADRC in disturbance rejection and quick adaptability over the PI approach.The proposed strategy is tested under two distinct wind speed profiles—constant and fluctuating—through time-domain simulations in MATLAB/Simulink. Simulation results confirm the superior performance of the ADRC-P&O method, highlighting its effectiveness in maximizing power extraction from wind energy and proving its potential for real-world applications. This study offers a significant advancement in wind energy technology by providing a robust and efficient solution for MPPT in WECS.
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DOI: 10.1016/j.cles.2024.100159
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