Performance analysis of drone sqadron optimisation based MPPT controller for grid implemented PV battery system under partially shaded conditions

IF 4.2 Q2 ENERGY & FUELS
Debabrata Mazumdar , Pabitra Kumar Biswas , Chiranjit Sain , Furkan Ahmad , Taha Selim Ustun , Akhtar Kalam
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引用次数: 0

Abstract

In recent years, growing consumer demand for sustainable energy is driving down costs and paving the way for more clean energy in the future. Since these energies are sporadic, and the load pattern does not correlate to their generation pattern, a battery storage system is required. Operating dispersed alternative energy sources, connected to the grid in this situation makes energy control an unavoidable task. The difficulty is brought on by things like intermittent sources, daytime costs, solar panel and battery size restrictions, and limitations in battery charging and discharging rates. Moreover, integrating energy storage devices into the power system network is one of the recommendations made in this work to increase the performance and dependability of these systems. Compared to the existing works reported in the literature, this study offers enhanced control techniques for hybrid Photovoltaic and Battery Energy Storage System under fluctuating atmospheric scenario. Here, an innovative approach called Drone Squadron Optimisation, which tracks the Global Maximum Power Point, is used get maximum power. Further, suggested approach is tested with various partial shading instances and the uniform irradiance condition to validate it. This research also investigates photovoltaic models and the status of the battery storage device for improved energy management in the system. Finally, the proposed algorithm assists in quickly identifying the potential benefits of a grid-connected, battery-powered rooftop solar system.

基于无人机方阵优化的 MPPT 控制器性能分析,适用于部分遮阳条件下并网的光伏电池系统
近年来,消费者对可持续能源的需求不断增长,推动了成本的下降,并为未来更多的清洁能源铺平了道路。由于这些能源是零星的,负载模式与其发电模式并不相关,因此需要一个电池存储系统。在这种情况下,将分散的替代能源与电网连接起来,使能源控制成为一项不可避免的任务。间歇性能源、日间成本、太阳能电池板和电池尺寸限制以及电池充放电速率限制等因素都会带来困难。此外,为了提高这些系统的性能和可靠性,将储能设备集成到电力系统网络中也是本研究提出的建议之一。与文献报道的现有作品相比,本研究为波动大气场景下的光伏和电池混合储能系统提供了增强型控制技术。在这里,一种名为 "无人机中队优化 "的创新方法可跟踪全球最大功率点,从而获得最大功率。此外,还对所建议的方法进行了各种部分遮挡实例和均匀辐照度条件的测试,以验证其有效性。这项研究还调查了光伏模型和电池存储设备的状态,以改进系统中的能源管理。最后,所建议的算法有助于快速识别并网、电池供电的屋顶太阳能系统的潜在优势。
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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来源期刊
Renewable Energy Focus
Renewable Energy Focus Renewable Energy, Sustainability and the Environment
CiteScore
7.10
自引率
8.30%
发文量
0
审稿时长
48 days
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