Browsing by Author "Cam, E"

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    Use of the Genetic Algorithm-Based Fuzzy Logic Controller for Load-Frequency Control in a Two Area Interconnected Power System
    Cam, E; Gorel, G; Mamur, H
    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.
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    A new fuzzy logic proportional controller approach applied to individual pitch angle for wind turbine load mitigation
    Civelek, Z; Lüy, M; Cam, E; Mamur, H
    In the world, efforts to increase the resource diversity in electric generation have accelerated lately. So, the great improvements have been achieved in wind turbines (WTs). The dimensions of WTs have grown for more electric generation and their energy productions have increased. Depending on these developments, it has become more important to reduce the WT load mitigation. Thus, a tendency to pass an individual pitch angle system control rather than a collective pitch angle system control employed to stable the output power of WTs over nominal wind speeds has whetted in recent studies. However, in literature, a controller proposal relating to how to incorporate the blade moments used for providing the individual pitch angle system into the output power control system has not yet been offered. Therefore, in this study, a new fuzzy logic proportional control (FL-P-C) approach has been recommended to mitigate the moment load on blades and tower to a minimum possible value while keeping the output power of WTs at a constant value. The offered FL-P-C has also been verified by MATLAB/Simulink. Through the first application of the FL-P-C on a WT, a significant improvement of 33-83% has been managed for the blade and tower moment loads. Furthermore, the grid fluctuations have been reduced because of the stabilisation of the output power of the WT. Ultimately, by the offered FL-P-C, not only the WT load mitigations and maintenance costs of WTs could be reduced, but also electric costs could be decreased owing to increasing lifetimes of WTs. (C) 2017 Elsevier Ltd. All rights reserved.