Maximum Power Point Tracking Design Based on Fuzzy Logic Algorithm Under Uncertain Weather Condition

Happy Aprillia, Asy-Syifa Ainina Amalia, A. Giyantara
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Abstract

Electricity is one of the main sources of energy that is very important in everyday life, both for household needs, government agencies, and industry. To strengthen the implementation sustainable development goal by reducing the use of fossil fuel, the utilization of solar energy has great potential, though the efficiency of solar panels or solar energy technology is still relatively low, especially in Indonesia. Located in tropical region, the solar panel module receives solar irradiation that varies due to changes in weather or local environmental conditions, partial shading will occur, making the solar panels partially covered by shadows. This situation will result in a decrease in the output power of solar panels To overcome this issue, a battery is used to store the generated energy. To maximize the potential, the battery needs to be charged optimally which need a control algorithm to provide energy gathered from the solar panel, most of the time. Therefore, a maximum power point tracking (MPPT) is necessary to be associated with an algorithm to optimally control the performance of the solar energy harvesting scheme. In this study, both Mamdani and Sugeno Fuzzy Logic Algorithm are used in the MPPT with a buck converter at a solar panel with a battery. Buck converter is chosen to give safety charging margin to the battery since the converter's output voltage is lower than the input voltage. As for the fuzzy logic algorithm, Mamdani's Fuzzy Logic has the advantage of producing more accurate decision results than Sugeno's type. While, Sugeno's Fuzzy Logic has the advantage of using simple mathematical calculations in its design. In addition, a buck converter was also used to match the voltage generated by the solar panel to match the battery specifications. The system design and testing are carried out using Matlab R2018b Simulink. From the simulation, the Mamdani Fuzzy Logic-based MPPT has the same maximum power point tracking computation time as Sugeno's Fuzzy Logic. In the partial shading test conditions, MPPT based on Fuzzy Logic has a higher efficiency value of 94.50% when compared to MPPT without control which is only 89.56%. Under various conditions of irradiation and temperature, MPPT based on Fuzzy Logic has a higher efficiency value of 94.88% than MPPT without control which is only efficiency of 91.53%.
不确定天气条件下基于模糊逻辑算法的最大功率点跟踪设计
电力是日常生活中非常重要的主要能源之一,对家庭、政府机构和工业都很重要。通过减少化石燃料的使用来加强可持续发展目标的实施,太阳能的利用具有巨大的潜力,尽管太阳能电池板或太阳能技术的效率仍然相对较低,特别是在印度尼西亚。太阳能电池板组件位于热带地区,受到的太阳辐射因天气或当地环境条件的变化而变化,会发生部分遮阳,使太阳能电池板部分被阴影覆盖。这种情况将导致太阳能电池板的输出功率下降,为了克服这个问题,使用电池来存储产生的能量。为了最大限度地发挥潜力,电池需要最佳充电,这需要一个控制算法来提供大部分时间从太阳能电池板收集的能量。因此,有必要将最大功率点跟踪(MPPT)与一种算法相结合,以最佳地控制太阳能收集方案的性能。在本研究中,Mamdani和Sugeno模糊逻辑算法都被用于带电池的太阳能电池板的降压变换器的MPPT中。由于Buck变换器的输出电压低于输入电压,因此选择Buck变换器是为了给电池提供安全充电余量。在模糊逻辑算法方面,Mamdani模糊逻辑算法的优势在于比Sugeno模糊逻辑算法产生更准确的决策结果。而Sugeno的模糊逻辑的优势在于在设计中使用了简单的数学计算。此外,还使用降压转换器来匹配太阳能电池板产生的电压,以匹配电池规格。使用Matlab R2018b Simulink进行系统设计和测试。仿真结果表明,基于Mamdani模糊逻辑的MPPT与Sugeno模糊逻辑的MPPT具有相同的最大功率点跟踪计算时间。在部分遮阳测试条件下,基于模糊逻辑的MPPT的效率值为94.50%,而没有控制的MPPT的效率值仅为89.56%。在不同的辐照和温度条件下,基于模糊逻辑的MPPT效率值为94.88%,高于无控制的MPPT效率值91.53%。
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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