獨立型太陽能發電系統於遮蔽效應下之最大功率點追蹤演算法

Maximum Power Point Tracking for Stand-alone Photovoltaic Power Generation Under Partial Shading Conditions

張庭愷(Ting-Kai Chang)

指導教授 ： 邱謙松

中原大學/電機資訊學院/電機工程研究所/碩士(2020年)

https://doi.org/10.6840/cycu202000757

摘要

太陽能電池受日照與溫度的變化，輸出功率呈現非線性的變化，因此需要最大功率點追蹤技術，提高太陽能發電系統的光電轉換效率。本文主要探討當太陽能電池因環境的因素發生遮蔽效應時，會產生多個功率峰值，而傳統型最大功率點追蹤演算法可能會陷入局部最大功率點，而無法找出全域最大功率點，造成轉換效率的降低。故本文提出灰狼演算法結合增量電導法之混合法來尋找全域最大功率點的工作電壓，其架構為獨立型太陽能發電系統，太陽能電池的電力經由升壓直流轉換器轉換後供給直流負載所使用，並利用PI進行電壓控制。本論文使用Matlab軟體模擬混合法可以在遮蔽效應下找出全域最大功率點。

關鍵字

太陽能電池 ； 遮蔽效應 ； 大功率點追蹤 ； 灰狼演算法 ； 升壓轉換器

並列摘要

The Photovoltaics are changed by illuminance and temperature, where power shows nonlinear change. The maximum power point tracking technology is needed to improve the energy conversion efficiency. In this thesis, we discuess the traditional maximum power point tracking method may fall into local maximum power point when the photovoltaic generates a number of local maximum power points under partial shading conditions. This implies that the global maximum power point cannot be found and the conversion efficiency is reduced. Thus, this thesis proposes a hybrid method, which combines Grey Wolf Algorithm (GWA) and Incremental Conductance method (INC) to find the global maximum power point. For a stand-alone photovoltaic power generation, the power of the photovoltaic energy is converted to a specific load through the boost converter, and the voltage is controlled by a PI controller. This thesis uses Matlab software to simulate the hybrid method and to find the global maximum power point under partial shading conditions.

並列關鍵字

Photovoltaic ； partial shading effect ； MPPT ； Grey Wolf Algorithm

參考文獻

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