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基于算术优化的最大功率点跟踪算法在非均匀光照条件下光伏系统中的应用

Arithmetic optimization based MPPT for photovoltaic systems operating under nonuniform situations.

作者信息

Adaikkappan Maheshwari, Sathiyamoorthy Nageswari, Ravichandran Durga Devi, Balasubramani Karthikeyan, Karuppannan Sundararaju, Palanisamy Ramasamy, Elbarbary Zakaria M S, Al-Gahtani Saad F, Omar Ahmed I

机构信息

Department of Electronics and Communication Engineering, M. Kumarasamy College of Engineering, Karur, Tamilnadu, India.

Department of Electrical and Electronics Engineering, Alagappa Chettiar Government College of Engineering and Technology, Karaikudi, Taminadu, India.

出版信息

PLoS One. 2024 Dec 30;19(12):e0311177. doi: 10.1371/journal.pone.0311177. eCollection 2024.

DOI:10.1371/journal.pone.0311177
PMID:39774430
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11684703/
Abstract

Photovoltaic (PV) modules may encounter nonuniform situations that reduce their useable power volume, causing ineffective maximum power point tracking (MPPT). Moreover, due to the incorporation of bypass diodes, power-voltage (P-V) graph has multi-peaks when each component of the module receives different solar irradiation. This paper proposes a solution to this problem using an arithmetic optimization algorithm (AOA) for MPPT in PV systems operating in nonuniform situations. The non-operational regions associated with the voltage are excluded using a single-ended primary inductance converter (SEPIC) with voltage step-up and step-down capability. The AOA-MPPT algorithm gets current and voltage as inputs from the PV modules. It computes the converter's duty cycle and regulates the operational point to keep MPP under all working conditions. The proposed AOA-MPPT's efficacy under different insolation patterns has been validated using three nonuniform conditions in terms of convergence, tracking speed, steady state oscillations, and tracking efficiency. In simulations, the proposed AOA-MPPT method and SEPIC converter demonstrated quick response and excellent steady-state performance. The tracking efficiency of the AOA-MPPT is above 99% and settling time is 200 to 300ms for all three non-uniform conditions.

摘要

光伏(PV)模块可能会遇到不均匀的情况,这会降低其可用电量,导致最大功率点跟踪(MPPT)无效。此外,由于并入了旁路二极管,当模块的每个组件接收到不同的太阳辐射时,功率-电压(P-V)图会出现多个峰值。本文针对在不均匀情况下运行的光伏系统中的MPPT问题,提出了一种使用算术优化算法(AOA)的解决方案。通过具有升压和降压能力的单端初级电感变换器(SEPIC)排除与电压相关的非工作区域。AOA-MPPT算法将电流和电压作为光伏模块的输入。它计算变换器的占空比,并调节工作点以在所有工作条件下保持最大功率点。通过在收敛性、跟踪速度、稳态振荡和跟踪效率方面使用三种不均匀条件,验证了所提出的AOA-MPPT在不同日照模式下的有效性。在仿真中,所提出的AOA-MPPT方法和SEPIC变换器表现出快速响应和出色的稳态性能。对于所有三种不均匀条件,AOA-MPPT的跟踪效率均高于99%,稳定时间为200至300毫秒。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cda/11684703/ee4efc6af79f/pone.0311177.g008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cda/11684703/ee4efc6af79f/pone.0311177.g008.jpg

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2
Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems.基于神经网络的独立光伏系统自适应全局滑模 MPPT 控制器设计。
PLoS One. 2022 Jan 20;17(1):e0260480. doi: 10.1371/journal.pone.0260480. eCollection 2022.