由於人類過度開發導致全球氣候暖化與空氣汙染的問題日趨嚴重，為了改善以上問題，許多專家學者均致力於再生能源的研究。再生能源為潔淨、取之不盡、用之不竭的大自然能源，而在所有再生能源之中，太陽能是相當重要的再生能源之一。對於商用之太陽能發電系統，在成本與體積為基本考量之下，轉換效率的改善變得極其重要，造成太陽能發電系統轉換效率低的主要原因是太陽能電池之電壓及電流關係為非線性曲線，其會依據當時的太陽日照量與溫度的不同而改變，並造成太陽能電池之輸出功率有所不同。因此，必須發展一最大功率追蹤(Maximum Power Point Tracking, MPPT) 法則，以在不同氣候因素下依然使得太陽能電池保持最大功率輸出，並具有快速且準確的追蹤響應。
現今針對最大功率追蹤法則已發展出相當多演算法，其在穩定的天氣狀態下多能發揮高效能的表現。然而當太陽能模組受到部分遮蔽情況下，功率-電壓之特性曲線將變得更加複雜，其將呈現多峰值的情況而產生多個區域(Local)最大功率點，由於傳統的最大功率追蹤法則多在追尋到峰值時便會停止搜尋，因此其在搜索全域(Global)最大功率點時會遭遇困難，這會造成太陽能發電系統的追蹤效率下降。由於部分遮蔽的情形對大型太陽能發電系統而言相當常見，因此發展一當發生部分遮蔽狀況時依然能快速且準確地尋找全域最大功率點之新型最大功率追蹤法則是有必要的。
本論文將針對太陽能模組在部分遮蔽情形下，發展以粒子群演算法(Particle Swarm Optimization, PSO)為基礎之最大功率追蹤法則。本論文中功率電路使用升壓式轉換器，韌體部分則是使用Microchip公司所推出的dsPIC微處理器來實現數位控制器。實際測試粒子群演算法是否能成功追蹤到遮蔽情況下之太陽能功率-電壓特性曲線中的最大功率點，並測試在日照變化的情況下程式是否能成功判別日照的變化重新追蹤最大功率點。由實驗結果可知粒子群演算法在電壓-功率特性曲線為多峰值狀況下仍可搜尋到最大功率點位置，其追蹤精確度為99%以上，且可判別日照變化重新追蹤最大功率點。

Studies on renewable energy systems are actively being promoted in order to mitigate environmental issues such as the global warming and air pollution. Photovoltaic (PV) energy is one of the most important renewable energy sources since it is clean, free and inexhaustible. For the commercialization of PV energy, the reduction of cost and size, and
the improvement of conversion efficiency have become important concerns. The main reason for the low conversion efficiency is the non-linear voltage-current (V-I) characteristics, which depends on the solar insolation and panel temperature. Therefore, a maximum power point tracking (MPPT) technique which has quick response and is able to track the peak power generated in any weather condition is required.
There are many MPPT strategies that are effective and time tested under uniform solar insolation. However, under partially shaded conditions when the entire array does not receive uniform insolation, the P –V characteristics become more complex and have multiple peaks. The presence of multiple peaks reduces the effectiveness of most of the existing tracking algorithms, which assume a single peak power point on the P–V characteristic. Since the occurrence of partially shaded conditions is quite common, there is a need to develop a novel MPPT algorithm for PV systems operating under partially shaded conditions.
This thesis focuses on developing a particle swarm optimization (PSO)-based MPPT algorithm for a PV system operating under partially shaded conditions. A boost converter is used as the power stage and the MPPT controller is realized using microcontroller dsPIC33FJ16GS502 from Microchip corp. Experiments are carried out to validate the correctness and effectiveness of the proposed algorithm. According to the experimental results, the proposed algorithm can track global maximum power point in various test conditions and the tracking accuracy is higher than 99%. The proposed algorithm can also restart tracking under irradiation changing conditions.

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