Optimization and intelligent power management control for an autonomous hybrid wind turbine photovoltaic diesel generator with batteries.

In this paper, a critical issue related to power management control in autonomous hybrid systems is presented. Specifically, challenges in optimizing the performance of energy sources and backup systems are proposed, especially under conditions of heavy loads or low renewable energy output. The problem lies in the need for an efficient control mechanism that can enhance power availability while protecting and extending the lifespan of the various power sources in the system. Furthermore, it is necessary to adapt the system's operations to variations in climatic conditions for sustained effectiveness. To address the identified problem. It is proposed the use of an intelligent power management control (IPMC) system employing fuzzy logic control (FLC). The IPMC is designed to optimize the performance of energy sources and backup systems. It aims to predict and adjust the system's operating processes based on variations in climatic conditions, providing a dynamic and adaptive control strategy. The integration of FLC is specifically emphasized for its effectiveness in balancing multiple power sources and ensuring a steady and secure operation of the system. The proposed IPMC with FLC offers several advantages over existing strategies. Firstly, it showcases enhanced power availability, particularly under challenging conditions such as heavy loads or low renewable energy output. Secondly, the system protects and extends the lifespan of the power sources, contributing to long-term sustainability. The dynamic adaptation to climatic variations adds a layer of resilience to the system, making it well-suited for diverse geographical and climatic conditions. The use of realistic data and simulations in MATLAB/Simulink, along with real-time findings from the RT-LAB simulator, indicates the reliability and practical applicability of the proposed IPMC strategy. Efficient load supply and preserved batteries further underscore the benefits of the fuzzy logic-based control strategy in achieving a well-balanced and secure system operation.

Performances improvements and torque ripple minimization for VSI fed induction machine with direct control torque.

This paper describes a torque ripple reduction technique with constant switching frequency for direct torque control (DTC) of an induction motor (IM). This method enables a minimum torque ripple control. In order to obtain a constant switching frequency and hence a torque ripple reduction, we propose a control technique for IM. It consists of controlling directly the electromagnetic torque by using a modulated hysteresis controller. The design methodology is based on space vector modulation (SVM) of electrical machines with digital vector control. MATLAB simulations supported with experimental study are used. The simulation and experimental results of this proposed algorithm show an adequate dynamic to IM; however, the research can be extended to include synchronous motors as well. The implementation of the proposed algorithm is described. It doesn't require any PI controller in the torque control loop. The hardware inverter is controlled digitally using a Texas Instruments TMS320F240 digital signal processor (DSP) with composed C codes for generating the required references. The results obtained from simulation and experiments confirmed the feasibility of the proposed strategy compared to the conventional one.