Improving Frequency Stability of the Nigerian 330kv Transmission Network Using Fuzzy Controller

Ngang, Ngang Bassey; Kazeem, Bakare

doi:10.11648/j.epes.20211003.12

Cited by 2 publications

References 3 publications

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Vocational Education-Based Acquisition of Skills to Curb Youth Restiveness: The Internet of Skills Approach

Ecoma,

Iheoma,

Ngang

2022

IJRER

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Lack of pertinent skills has been linked to youth unrest brought on by rising unemployment rates. This work offered a method for students to learn without the assistance of a subject-matter expert (SME). The paper is a source of information that focuses on using the internet to develop entrepreneurial skills to address the issue of youth unemployment in developing countries. It is a fact that entrepreneurial skills are essential to job creation; active use of the internet to acquire pertinent knowledge could lead to self-actualization. Youth unemployment in developing nations is on the rise. This paper used real-world examples to demonstrate how internet resources can be helpful for performing tasks both at home and in the workplace. For example, studying saponification in chemistry can be taught similarly to how it is used in the soap manufacturing industry. Information on troubleshooting guides for electrical machines (electric motors and synchronous generators) was also provided from secondary sources. Finally, the "Internet of Skills" could be used to design a microgrid system. The Internet of Skills strategy was employed as the technique to accomplish this. With this strategy, it is possible to reduce youth unrest and improve security.

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Vocational Education-Based Acquisition of Skills to Curb Youth Restiveness: The Internet of Skills Approach

Ecoma,

Iheoma,

Ngang

2022

IJRER

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Optimized Energy Efficiency in a Telecommunication Company: Machine Learning Approach

Ngang¹

2022

Alternative Energies and Efficiency Evaluation

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Energy efficiency is the use of technology that requires less energy to perform the same task. It was considered to introduce optimized energy efficiency by using machine learning to reduce power consumption at communication base station (BTS) sites. This process involves reviewing relevant work to identify defects, characterizing and determining the power consumption of the cell site under investigation, developing a SIMULINK model for the cell site under investigation, and identifying the module. It also includes optimizing high power consumption; design a machine learning rule base to monitor the power consumption of the module. Train artificial neural network (ANN) on machine learning rules designed to reduce cell power consumption, thereby improving network performance. The next step is developing an algorithm to implement it, and finally, to design a power consumption model for the network under investigation. The results obtained after a large simulation show that the traditional maximum power consumed at the cell site is 5746 kW, while the power when machine learning is injected into the system is 4733 kW. Integrating machine learning into the system resulted in 4731 kW, an 8.9% performance improvement.

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Improving Frequency Stability of the Nigerian 330kv Transmission Network Using Fuzzy Controller

Cited by 2 publications

References 3 publications

Vocational Education-Based Acquisition of Skills to Curb Youth Restiveness: The Internet of Skills Approach

Vocational Education-Based Acquisition of Skills to Curb Youth Restiveness: The Internet of Skills Approach

Optimized Energy Efficiency in a Telecommunication Company: Machine Learning Approach

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