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Abstract:In this study, design, implementation, and power performance analyses of a micro wind turbine (MWT) system are presented. An original permanent magnet synchronous generator (PMSG) that reduced cogging torque was employed as a generator in the MWT. A novel blade form offering better performance at low wind speeds was also utilized for the MWT blades. Power performance analyses of the MWT were carried out for different wind regimes by truck testing. Performance coefficient, cut-in, and cut-out of the MWT were determined as 27.7%, 2.7 m/s, and 20 m/s at the end of the truck testing, respectively. Moreover, a new supervisory control and data acquisition (SCADA) program based on a programmable logic controller was written to measure the electrical power of the MWT, and hence the analyses of the MWT were easily fulfilled through the SCADA.

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Output powers of wind turbines (WTs) with variable blade pitch over nominal wind speeds are controlled by means of blade pitch adjustment. While tuning the blade pitch, conventional proportional–integral–derivative (PID) controllers and some intelligent genetic algorithms (IGAs) are widely used in hot systems. Since IGAs are community‐based optimisation methods, they have an ability to look for multi‐point solutions. However, the PID parameter setting optimisation of the IGA controllers is important and quite difficult a step in WTs. To solve this problem, while the optimisation is carried out by regulating mutation rates in some IGA controllers, the optimisation is conducted by altering crossover point numbers in others. In this study, a new IGA algorithm approach has been suggested for the PID parameter setting optimisation of the blade pitch controller. The algorithm rearranging both the mutation rate and the crossover point number together according to the algorithm progress has been firstly used. The new IGA approach has also been tested and validated by using MATLAB/Simulink software. Then, its superiority has been proved by comparing the other genetic algorithm (GAs). Consequently, the new IGA approach has more successfully adjusted the blade pitch of a WT running at higher wind speeds than other GA methods.

Abstract:The use of renewable energy resources has created some problems for power systems. One of the most important of these is load frequency control (LFC). In this study, in order to solve the LFC problem, modern control methods were applied to a two area multi source interconnected power system. A photovoltaic solar power plant (PV-SPP) was also connected, in order to identify the harmful effects on the frequency of the system. A new Genetic-based Fuzzy Logic (GA-FL) controller was designed to control the frequency of the system. For comparison, conventional proportional-integral-derivative (PID), fuzzy logic (FL), and Genetic Algorithm (GA)-PID controllers were also designed. The new control method exhibited a better performance than the conventional and other modern control methods, because of the low overshoot and short settling time. All simulations were realized with the Matlab-Simulink program.

In this study, the design and implementation of a new portable thermoelectric generator of 100 W for low geothermal temperatures has been carried out. For this system, a new SCADA-based testing and measuring system equipped with special software has been developed and employed for the first time. Thus, effects of the hot-cold water flow rates, the temperature differences between the surfaces and the load resistance affecting output power and efficiency of the thermoelectric generator have been investigated by a single testing and measuring system device. In the established SCADA-based testing and measuring system, the hot-cold water flows passed throughout the surfaces of the thermoelectric generator were increased by up to 3.7 and 12.8 l/min, respectively. Then, the temperature difference between the surfaces of the thermoelectric generator was measured as 67°C. When the load resistance of the thermoelectric generator was about 15 Ω, the maximum power of the thermoelectric generator was obtained as 41.6 W and the conversion efficiency was calculated as 3.9%. Also, the SCADAbased testing and measuring system will open up a new stage in examination of various thermoelectric generators.