Muhammed Abduljaleel Ibrahim

The study aims to optimize wind farm efficiency in low wind speed regions using the HOMER Pro tool to examine the impact of wind turbine ratings on overall efficiency of wind farms. boosting wind farm efficiency is essential for improving economic viability and grid integration. We propose the establishment of three wind farms, each possessing equal capacities but different in individual turbine capacities 1.5 kW, 3.4 kW and 5.1 kW, then optimize their performance in simulation environment. Through employing HOMER Pro optimization algorithm, we assess all wind farms over the period of one year, taking into account wind speed, temperature and geospatial coordinates. Although all wind farms have equal total capacities, simulation results revealed disparities in their generation abilities, reaching up to 22%, favouring the farm with smaller turbines. Furthermore, the results demonstrated that as wind speed decreases, the disparity in power generation between wind farms increases, reaching 51.9% in November, the month with the lowest wind speeds. These findings provide a comprehensive understanding of wind farm behaviour, particularly regarding turbine sizes, and contribute to the research community's efforts to enhance wind farm power production in low wind speed regions. They also help find solutions to enable the embrace of wind energy and decrease fossil fuel consumption in such regions, fulfilling their international sustainability commitments.

This paper discusses the implementation of a Proportional-Integral-Derivative (PID) controller for regulating the speed of a closed loop four quadrant chopper fed DC motor. The PID controller is combined with a Dual Fuzzy Logic Controller to form a DFPID controller for enhancing the performance of speed control of the DC motor. The DFLC is optimized using a metaheuristic algorithm known as Harmony Search Algorithm (HSA). The major aim of this research is to gain an effective control over the speed of the motor in the closed loop environment. For achieving this, the parameters for the DFPID are selected through time domain analysis which aims to satisfy the requisites such as settling time and peak overshoot. Initially, the fuzzy logic controller in the DFPID controls the coefficients of the PID achievement gain an effective control over the system error and rate of error change. Further, the DFPID is improved by the HAS for obtaining a precise correction. The solutions obtained by tuning the DFPID controller are evaluated from simulation analysis conducted on a MATLAB/SIMULINK platform. The closed loop performance is analyzed in both time and frequency domain analysis and the performance of DFPID is optimized using the HSA algorithm to obtain precise value of the control process. As observed from the Simulation analysis, the DFPID-HSA generates optimized control signals to the DC motor for controlling the speed. The performance of the intended speed control approach is analyzed in terms of different evaluation metrics such as motor speed, torque and armature current. Experimental outcomes show that the proposed approach achieves better control performance and faster speed of DC motor compared to conventional PID controllers and SMC controllers

Brushless DC (BLDC) motor is commonly employed for many industrial applications due to their high torque and efficiency. This article produces an optimal designed controller of Brushless DC motor speed control depending on the genetic algorithm (GA). The optimization method is used for searching of the ideal Proportional–Integral-Derivative (PID) factors. The controller design methods of brushless DC motor includes three kinds: trial and error PID design, auto-tuning PID design and genetic algorithm based controller design. A PID controller is utilizing by conducted Integral absolute error criterion (IAE) and integral squared error (ISE) error criterion for BLDC motor control system. A GA-PID controller is designed to enhance the system performance by means of genetic algorithm. PID controller coefficients are calculated by GA to produce optimal PID as hybrid PID with GA controller .The closed loop speed response of PID controller is experimented for IAE and ISE error criteria. The suggested controller GA_PID is planned, modeled and simulated by MATLAB/ software program. A comparison output system performance monitored for every controller schemes. The results display that the time characteristics performance of GA-PID controller based on ISE objective function has the optimal performance (rise time, settling time, percentage overshoot) with other techniques.