Adapting Perturbation Voltage For Variable Speed Micro-Hydro Using Particle Swarm Optimization (PSO)

Kit Guan Lim, Mohd Izzat Fikri Md Zainal, M. K. Tan, A. Haron, C. Chai, K. Teo
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Abstract

The aim of this research is to explore a technique that can be implemented to the Variable Speed Micro-hydro Power Generation (VS-MHPG) system to search the optimum operating point for the maximum power extraction. Micro-Hydro that operates in variable speed mode are sensitive to the changes of flow rate and proved to have wide operating point. The Perturb and Observe (P&O) based maximum power point tracking (MPPT) was applied to the VS-MH and based on simulation. However, oscillation occur at maximum point due to the large perturbation speed. The existing Micro-hydro Power Generation (MHPG) system commonly suffers from the non-optimal input control as the controller estimate the changes of flow rate without anticipating the global maximum power curve. Hence the implementation of P&O based MPPT is expected to improve the efficiency of MHPG system while reducing the fluctuation of output power. Results show that the value of perturbation speed affects the performance of MPPT algorithm to search the maximum operating point. Low perturbation signal requires many numbers of iteration before it reaches the steady state. Meanwhile, high perturbation signal will cause the fluctuation that led to unstable power production. Thus, new method was introduced which is Particle Swarm Optimization (PSO) that is expected to improve the performance of conventional MPPT. Simulation result shows that PSO based MPPT was able to track the global maximum point under extreme condition with no power fluctuation compared to P&O MPPT. Also, PSO based MPPT provides adaptive perturbation speed that show improvement in maximum power tracking by 20.88%.
基于粒子群优化(PSO)的变速微水电扰动电压自适应
本研究的目的是探索一种可应用于变速微型水力发电(VS-MHPG)系统的技术,以寻找最大功率的最佳工作点。以变速方式运行的微型水电站对流量变化敏感,工作点宽。将基于扰动和观测(P&O)的最大功率点跟踪(MPPT)应用于VS-MH并进行了仿真。但由于扰动速度大,在最大值处出现振荡。现有的微水电发电系统存在输入控制非最优的问题,即控制器在不预测全局最大功率曲线的情况下估计流量变化。因此,基于P&O的MPPT的实现有望提高MHPG系统的效率,同时减少输出功率的波动。结果表明,微扰速度的大小会影响MPPT算法搜索最大工作点的性能。低扰动信号需要多次迭代才能达到稳态。同时,高扰动信号会引起波动,导致发电不稳定。为此,提出了一种新的方法——粒子群优化算法(PSO),有望提高传统MPPT的性能。仿真结果表明,与P&O MPPT相比,基于PSO的MPPT能够在极端条件下跟踪全局最大值,且无功率波动。此外,基于粒子群的MPPT提供了自适应扰动速度,最大功率跟踪性能提高了20.88%。
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