Balanced Performance Merit on Wind and Solar Energy Contact With Clean Environment Enrichment

IF 2.4 3区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Journal of the Electron Devices Society Pub Date : 2024-01-24 DOI:10.1109/JEDS.2024.3358087
Priyan Malarvizhi Kumar;M. M. Kamruzzaman;Badria Sulaiman Alfurhood;Bakri Hossain;Harikumar Nagarajan;Surendar Rama Sitaraman
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Abstract

1. Introduction: The wind is used for solar energy, and solar energy is used for wind energy. Without each other, electricity cannot be made. Then based on the components, the generator, and the inverter-related electricity can be saved later. Problem formulation: One of the main problems with solar and wind energy is that they make non-concentrated and dilute energy from vast lands. Also, generating the variability and the cost factors is the problem in wind and solar power. To solve this, the installation of solar panels has been enabled for the energy done. The production of the batteries in some of the solutions can be stimulated for the analysis is done. One technique used in this paper is the Artificial neural networks-based expert system and the crop production system. Techniques: Artificial Neural Network-Based Expert Systems are used to predict the plant response in the environment, which is the response to the humidity, light radiation, and temperature. The crop production system is used for performing the plant performance, and the fertilizer follows the resources of the plants and other arrangements related to the plants. Result: The results from the working of the wind and solar energy are equally proportional to the analysis’s 50% -the 50s. Then, the suggested model explains 96.9% of the variation in the dependent variable (plant growth and development) based on the input variables (temperature, CO2, humidity, and light radiation), according to the Coefficient of Determination of 0.969. Overall, the suggested ANN-ES model anticipates plant growth and development based on the input variables and is regarded as dependable for this purpose.
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风能和太阳能与清洁环境的平衡功绩
1.导言:风能用于太阳能,太阳能用于风能。二者缺一不可,缺一不可就无法发电。那么基于组件、发电机和逆变器相关的电能就可以节省下来。问题的提出:太阳能和风能的一个主要问题是,它们从广袤的土地上获取的能源不集中,而且稀释。此外,发电的可变性和成本因素也是风能和太阳能发电的问题。为了解决这个问题,人们安装了太阳能电池板来提供能源。一些解决方案中的电池生产可以促进分析的完成。本文使用的一种技术是基于人工神经网络的专家系统和作物生产系统。技术:基于人工神经网络的专家系统用于预测植物在环境中的反应,即对湿度、光辐射和温度的反应。农作物生产系统用于检测植物的表现,肥料则根据植物的资源以及与植物相关的其他安排进行施用。结果:风能和太阳能的工作结果与分析结果的 50%-50%成正比。然后,根据输入变量(温度、二氧化碳、湿度和光辐射),建议的模型解释了因变量(植物生长和发育)变化的 96.9%,决定系数为 0.969。总体而言,所建议的 ANN-ES 模型可根据输入变量预测植物的生长和发育情况,在这方面是可靠的。
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来源期刊
IEEE Journal of the Electron Devices Society
IEEE Journal of the Electron Devices Society Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
5.20
自引率
4.30%
发文量
124
审稿时长
9 weeks
期刊介绍: The IEEE Journal of the Electron Devices Society (J-EDS) is an open-access, fully electronic scientific journal publishing papers ranging from fundamental to applied research that are scientifically rigorous and relevant to electron devices. The J-EDS publishes original and significant contributions relating to the theory, modelling, design, performance, and reliability of electron and ion integrated circuit devices and interconnects, involving insulators, metals, organic materials, micro-plasmas, semiconductors, quantum-effect structures, vacuum devices, and emerging materials with applications in bioelectronics, biomedical electronics, computation, communications, displays, microelectromechanics, imaging, micro-actuators, nanodevices, optoelectronics, photovoltaics, power IC''s, and micro-sensors. Tutorial and review papers on these subjects are, also, published. And, occasionally special issues with a collection of papers on particular areas in more depth and breadth are, also, published. J-EDS publishes all papers that are judged to be technically valid and original.
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