本研究提出了兩種新型的太陽能追蹤演算法，分別為太陽與地平線角度最大功率點追蹤演算法，與基於趨勢線轉換技術最大功率點追蹤演算法。首先，傳統的爬山法在低日照量(<150W/m2)下不易執行最大功率追蹤，且作動點會陷入局部低點無法脫離，引起功率損失，所提第一種演算法利用了太陽與地平線之間角度關係，可將最大功率追蹤範圍延伸到100W/m2，進一步與爬山法在日照量分別為1000 W/m2、800 W/m2、500 W/m2、250 W/m2與100 W/m2進行模擬與實測結果比較，證實了所提第一種演算法優於傳統的爬山法。
再者，第二種演算法在均勻的日照環境與部分遮蔭環境，皆可完成全局最大功率點追蹤控制。所提系統以微控制器根據太陽能模組輸出的電流、功率與實際溫度趨勢線之斜率，計算出太陽能模組的全局最大功率點之電流，以準確執行全局最大功率點追蹤，並快速地判斷太陽能模組是否遭受部分遮蔭的影響，可立即執行部分遮蔭模式控制策略，再重新計算出太陽能模組的全局最大功率點電壓，以精準地追蹤全局最大功率點。
所提演算法二與粒子群優化法，及傳統的爬山法、擾動觀察法分別使用MATLAB模擬日照量由1,000 W/m2下降至500 W/m2的動態響應。然後，分別在日照量1,000 W/m2的均勻日照環境，與日照量1,000 W/m2和500 W/m2部分遮蔭下進行實測。最後，所有的模擬與實驗結果驗證所提演算法之全局最大功率點追蹤效能與收斂時間，均優於粒子群優化法，以及傳統的爬山法、擾動觀察法。

This research proposes two novel types of solar tracking algorithms, namely the maximum power point tracking (MPPT) algorithm for the angle between the sun and the horizon and the MPPT algorithm based on the trend line transformation technique. The traditional hill climbing (HC) algorithm is not easy to perform MPPT under low irradiance level (<150W/m2), and the actuating point will trap a local minimum without escape, resulting in power loss. The first proposed algorithm uses the angle between the sun and the horizon to extend the MPPT range to 100W/m2. The proposed algorithm and HC algorithm are compared with the simulated and measured results under 1000 W/m2, 800 W/m2, 500 W/m2, 250 W/m2, and 100 W/m2, respectively, which confirmed the performance of the first proposed algorithm is better than the traditional HC algorithm.
Furthermore, the second proposed algorithm can complete the global maximum power point tracking (GMPPT) control under uniform irradiation and partial shading conditions (UIC and PSC, respectively). The microcontroller unit of the proposed system calculates the IGMPP of the photovoltaic (PV) module to accurately execute GMPPT on the basis of the PV module current (Ipv), power (Ppv) and temperature trend line slope (dIpv/dPpv), and can rapidly confirm whether the PV module suffers from shading according to the slope (dIpv/dPpv) and immediately executes the PSC mode control strategy to recalculate the VGMPP of the PV module, thereby accurately tracking the GMPP.
The second proposed algorithm is compared with the particle swarm optimization (PSO) method, traditional HC, and perturbation and observation (P&Q) algorithms for MATLAB simulation and actual measurement. These four algorithms firstly use MATLAB to simulate the dynamic response of the solar irradiance level from 1000 W/m2 to 500 W/m2. Then the measured separately under UIC of 1000 W/m2, and measured under PSC of 500 W/m2 and 1000 W/m2, respectively. Finally, all the simulations and experimental results confirm that the proposed algorithm has better GMPPT performance and convergence time than the PSO, the traditional HC, and P&O techniques.

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