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首页> 外文会议>2015 International Conference on Energy Systems and Applications >Maximum power point tracking of SPV at varying atmospheric condition using Genetic Algorithm
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Maximum power point tracking of SPV at varying atmospheric condition using Genetic Algorithm

机译：遗传算法在变化大气条件下对SPV的最大功率点跟踪

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The output power of the PV panel depends on the amount of irradiation, temperature and the connected load. This controls the operating point i.e. voltage and current of the panel. The maximum power from the PV panel can be extracted if the impedances of both source (PV panel) and load are matching. The internal resistance of the panel depends upon the irradiation i.e. the intensity of the sunlight falling on it. The change in the atmospheric conditions results in the mismatch between the load and source impedance. Due to this mismatch, panel is not operated at its maximum power point (MPP) resulting in lower generation of power thereby decreasing the overall efficiency of the system. This paper presents a simulation study on enhancing the efficiency of a solar photovoltaic panel by finding the optimum operating parameters under varying atmospheric conditions using Genetic Algorithm. The said technique finds the optimum voltage and current corresponding to the given atmospheric condition. The proposed algorithm is tested at different temperature and irradiation. Results show that the Genetic Algorithm can track the maximum power point accurately with high conversion performance.
机译：光伏面板的输出功率取决于辐照量，温度和所连接的负载。这可以控制工作点，即面板的电压和电流。如果电源（PV面板）和负载的阻抗都匹配，则可以从PV面板提取最大功率。面板的内阻取决于辐射，即，落在其上的阳光的强度。大气条件的变化导致负载和源阻抗之间的失配。由于这种失配，面板无法在其最大功率点（MPP）下运行，从而导致发电量降低，从而降低了系统的整体效率。本文提出了通过使用遗传算法找到变化的大气条件下的最佳运行参数来提高太阳能光伏板效率的模拟研究。所述技术找到对应于给定大气条件的最佳电压和电流。所提出的算法在不同温度和辐射下进行了测试。结果表明，遗传算法能够以较高的转换性能准确地跟踪最大功率点。

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