用人工蜂群算法实现光伏系统最大功率点跟踪

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2020-12-10 DOI:10.1109/ISRITI51436.2020.9315527

Muhammad Rizal Fanani, I. Sudiharto, I. Ferdiansyah

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引用次数: 3

摘要

目前正在开发太阳能热能作为可再生电力的一种来源。光伏系统的主要问题是电力效率低。最大功率点跟踪(MPPT)方法可以提高光伏输出功率的效率。本研究将采用基于人工蜂群(ABC)算法的MPPT方法。MPPT设计将使用Power Simulation (PSIM)软件进行仿真。仿真结果将与无MPPT和MPPT人类心理优化(HPO)算法进行比较。结果表明，MPPT ABC在无MPPT的平均准确率和MPPT HPO的平均准确率中获得了最好的平均准确率，为99.95%。在辐照800w /m2、900w /m2、1000w /m2时，MPPT ABC的MPP跟踪响应时间比MPPT HPO快。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Implementation of Maximum Power Point Tracking on PV System using Artificial Bee Colony Algorithm

Implementation of Solar thermal energy as a source of renewable electricity is currently being developed. The main problem with photovoltaic systems is the result of power efficiency is low. The maximum power point tracking (MPPT) method can increase the efficiency of photovoltaic output power. This research will use the MPPT method with an artificial bee colony (ABC) algorithm. MPPT design will be simulated using Power Simulation (PSIM) software. Simulation results will be compared with no MPPT and MPPT human psychology optimization (HPO) algorithm. The results show MPPT ABC gets the best average accuracy from the average accuracy without MPPT and MPPT HPO, which is 99.95%. And the MPPT ABC has a response time of MPP tracking faster than MPPT HPO, during irradiation 800 W/m2, 900 W/m2, 1000 W/m2.

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来源期刊

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

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