Nowaday, the power control technique for a large wind turbine is mainly controlled through pitch angle control. The necessity for control of pitch angle is because of stochastic nature of the speed of wind. In this paper, different strategies for pitch angle controllers are compared for a wind turbine with doubly fed induction generator to achieve the steady output power for above rated wind speed. The control strategy utilized here are the conventional Proportional Integral (PI) and Genetic algorithm (GA) optimized PI controllers, which are developed through MATLAB. Finally, the performances of the control strategies are compared. From the results it is found that the GA optimized PI controller depicts an improved performance in comparison to PI controller. 

Design and simulation of a GA optimized variable speed DFIG based wind turbine using MATLAB

Recent technological advancements and cost reduction drives increasing the penetration of renewable energy sources with grid. Utilisation factor of renewable energy sources is low due to dependency on the environmental conditions. Basically, hybrid energy systems provide constant, high-quality power for the remote communities. The sizing of the hybrid system is significant to meet the load demand of residential buildings. In this paper, A simple optimal sizing algorithm is used to model the Wind turbine and PV system to meet the residential load. Quantitave feedback theory (QFT) based robust controller is implemented for the proposed sub-module integrated PV converter and the PMSG based wind energy conversion system to extract maximum power using simple genetic algorithm. Performance of the QFT controller is analysed through MATLAB simulations under varying irradiance and wind conditions.

Performance analysis of Grid Integrated Hybrid Renewable Energy System configuration application to Residential Buildings

Nowaday, the power control technique for a large wind turbine is mainly controlled through pitch angle control. The necessity for control of pitch angle is because of stochastic nature of the speed of wind. In this paper, different strategies for pitch angle controllers are compared for a wind turbine with doubly fed induction generator to achieve the steady output power for above rated wind speed. The control strategy utilized here are the conventional Proportional Integral (PI) and Genetic algorithm (GA) optimized PI controllers, which are developed through MATLAB. Finally, the performances of the control strategies are compared. From the results it is found that the GA optimized PI controller depicts an improved performance in comparison to PI controller.

A taxonomic review of Dendrophthora brachyclada, D. cupressoides, D. marmeladensis, D. moniliformis, D. picotensis and D. podocarpicola in Cuba was conducted through the direct comparison and measurement of vegetative and reproductive characters, and considering geographical, ecological and altitudinal distributions and host trees. The most important morphological characters found to separate species are discussed, and an identification key for all Cuban squamate species is provided. Besides the taxonomic review, nomenclatural changes are proposed, including the designation of a syntype for D. cupressoides and third-step lectotypes for D. brachyclada, D. picotensis and D. selleana. Results suggest that D. brachyclada, D. cupressoides, D. marmeladensis, D. picotensis and D. podocarpicola are distinct species, while D. moniliformis should be recognized as a synonym of D. marmeladensis.

Taxonomic revision of an Antillean group of mistletoes (Dendrophthora, Viscaceae) present in Cuba

Long-term simulations are significant to understand the real-time operation of grid-tied renewable energy system configurations. Grid-tied photovoltaic system (GPV) is highly non-linear due to the dependency of real-time meteorological conditions. The non-linear behavior of the photovoltaic (PV) system with the power electronic converter makes the long-term simulation inefficient and slow. This paper presents an efficient and simple modelling approach for GPV modelling suitable for long-term simulations. The recent advancements in control strategies and system configurations, sub-module level controller operation gained much interest but the simulation of such systems can be very challenging due to a large number of power electronic components and their control, non-linear behavior of PV system. This paper proposed a genetic algorithm based robust controller design in the quantitative feedback theory (QFT) framework to extract the maximum power from GPV at the sub-module level to extradict the power losses due to partial shading conditions. The performance of the proposed controller at the PV sub-module level is evaluated through comparison with the Q-parameterization based controller. The proposed QFT methodology based robust controller is shown to have advantages over Q-parameterization approach to simulate long-term GPV operation.

Performance analysis of automated QFT robust controller for long-term grid tied PV simulations

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Performance analysis of Grid Integrated Hybrid Renewable Energy System configuration application to Residential Buildings

Performance analysis of automated QFT robust controller for long-term grid tied PV simulations