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Optimization of the Dynamic Performance of the Photo-Voltaic and Wind-Turbine Hybrid-Energy System by the Particle-Swarm Optimization Technique

机译:通过粒子 - 群优化技术优化光伏和风力涡轮混合能系统的动态性能

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In order to overcome the intermittence of renewable energy sources, such sources are connected in parallel forming hybrid systems. One of these hybrid systems is presented in this paper aiming to investigate and improve its dynamic performance. The hybrid energy system is composed of photovoltaic (PV) arrays and wind turbine (WT) that drives a doubly-fed induction generator (DFIG). Both the PV and WT are linked together through a DC-capacitor link. In order to improve the dynamic performance, a Particle-Swarm Optimization algorithm is implemented to tune the gains of the applied controllers. The obtained optimum gains are then implemented in a simulation model using the simulink program (MATLAB). Results in the case of optimized gains are compared with initial design results in the relevant literature. Results show that the dynamic performance of the hybrid energy system with PSO is improved in terms of speed and steady-state error.
机译:为了克服可再生能源的间歇性,这种源并联形成混合系统。本文提出了其中一种混合系统,旨在调查和改善其动态性能。混合能量系统由光伏(PV)阵列和风力涡轮机(WT)组成,其驱动双馈感应发生器(DFIG)。 PV和WT都通过DC电容链路连接在一起。为了提高动态性能,实现了一种粒子 - 群优化算法来调整所应用的控制器的增益。然后使用Simulink程序(MATLAB)在仿真模型中实现所获得的最佳增益。结果在优化的收益的情况下与相关文献中的初始设计进行了比较。结果表明,在速度和稳态误差方面,具有PSO的混合能量系统的动态性能。

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