Improved design of advanced controller for a step up converter used in photovoltaic system

Q2 Engineering
N. Ben Si Ali, N. Benalia, N. Zerzouri
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引用次数: 0

Abstract

Abstract The expanding need for electricity has stimulated research and development of novel supply sources for energy production, conversion, and storage. Many studies are being done to increase the effectiveness of conversion systems as renewable energy is integrated into power networks on a larger scale. The global challenge is to minimize manufacturing costs and increase the use of sustainable resources. In this sense, photovoltaics is viewed as a particularly promising source due to the low cost of implementation and the wide range of applications it could be used for. This research focuses on the analysis, modeling, and simulation of a smart controller for a step-up converter that uses an artificial neural network (ANN) as a maximum power point tracking (MPPT) technique to provide maximum power. The proposed ANN-based algorithm is performed in Matlab/Simulink software, and its effectiveness has been demonstrated under varying climatic conditions.
光伏系统升压变换器高级控制器的改进设计
不断扩大的电力需求刺激了对能源生产、转换和储存的新型供应来源的研究和开发。随着可再生能源更大规模地纳入电力网络,正在进行许多研究以提高转换系统的效率。全球面临的挑战是将制造成本降至最低,并增加可持续资源的使用。从这个意义上说,由于低成本的实施和广泛的应用,光伏发电被视为一个特别有前途的来源。本研究着重于升压转换器的智能控制器的分析、建模和仿真,该控制器使用人工神经网络(ANN)作为最大功率点跟踪(MPPT)技术来提供最大功率。基于人工神经网络的算法在Matlab/Simulink软件中执行,并在不同的气候条件下验证了其有效性。
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来源期刊
Energy Harvesting and Systems
Energy Harvesting and Systems Energy-Energy Engineering and Power Technology
CiteScore
2.00
自引率
0.00%
发文量
31
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