Browsing by Author "Ademola Abdulkareem"

Now showing 1 - 7 of 7
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    Determination of Power System Losses in Nigerian Electricity Distribution Networks
    (IJET Publications UK, 2016-09-01) Adesina, L. M.; Ademola Abdulkareem
    Nigerian Electric Power Utilities face epileptic power supply due to poor generation level. The available power is characterised with high losses of Aggregate Technical and Commercial (ATC) or Total network losses. These losses have serious effects on the quality of power delivered to customers and adverse effect in meeting the expected revenue targets. Technical losses are caused by network impedance due to current flowing in the network and auxiliary supplies. Whereas non-technical losses are caused by several factors which include, energy theft, unbilled accounts, non-payment of customers, estimated customer accounts etc. This paper presents analysis of some selected power system network for estimation of total network or ATC losses and determination of network technical losses (TL) using power flow analysis. From the results of ATC losses and TL calculations, a total network non-technical loss (NTL) is determined.
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    Effects of Ground Resistivity and Tower Structural Design on Transmission line Symmetrical Components
    (Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences, 2020-05-01) Lambe Mutalub Adesina; Ademola Abdulkareem; Olalekan Ogunbiyi
    Electric power transmission towers are line support that exists in different structural configurations depending on the design. Parameters in consideration for the design include proposed voltage and current ratings to be carried by the tower, weights of the Aluminum conductor, and the weight of the Concrete foundation on which the tower would be erected. It is often reported that ground resistivity of the ground on which an electric power transmission tower is erected has significant effects on earth faults and transmission losses on the line. This paper presents an investigation of the effects of ground resistivity and tower structural design on transmission line symmetrical components. Symmetrical component parameters’ evaluation of the transmission lines approach is considered the best option. Ten differently structured transmission towers were selected for the case study. The effects of installing these ten towers on each of the available ground resistivity types were examined. Modern computer software was developed to carry out this investigation. The results are presented and discussed. It was observed that at each location of a tower, ground resistivity plays a vital role in measuring the performance of the tower in an electric power supply stability and reliability.
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    Evaluating Reliability Compliance of the Power Utility Distribution Networks
    (International Research Publication House, 2020-08-01) Lambe Mutalub Adesina; Kamaldeen Sa’adu; Ademola Abdulkareem
    Distribution network planners carry out analyses of the power distribution network that may include studies like faults, sensitivity analysis and reliability assessment to enhance the robustness of the network. System reliability is the ability of the power system to provide an adequate supply of electrical power at a desired time without interruption. This paper focuses on reliability assessment of distribution network. It involves the determination of the reliability indices which explain the dependability of the system. Fifteen 11kV feeders are considered and the required data of the feeders to be used in this study were sourced from the chosen power utility company in Nigeria. A power system software called ETAP was used in computational process. The reliability indices of the chosen network were computed, and the results obtained are presented. From the results, the performance of these Fifteen 11kV feeders are classified into three; Best, averagely and poorly performing feeders, and they are highlighted using tables and charts. The results are discussed and analyzed. The findings from the study indicate that some feeders have very good reliability indices while some are having average values and others are with poor reliability indices. The most critical feeders that need improvement were identified.
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    Experimental Analysis of Intrusion Detection Systems Using Machine Learning Algorithms and Artificial Neural Networks
    (The Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU), 2024-02-01) Ademola Abdulkareem; Tobiloba Emmanuel Somefun; Adesina Lambe Mutalub; Adewale Adeyinka
    Since the invention of the internet for military and academic research purposes, it has evolved to meet the demands of the increasing number of users on the network, who have their scope beyond military and academics. As the scope of the network expanded maintaining its security became a matter of increasing importance. With various users and interconnections of more diversified networks, the internet needs to be maintained as securely as possible for the transmission of sensitive information to be one hundred percent safe; several anomalies may intrude on private networks. Several research works have been released around network security and this research seeks to add to the already existing body of knowledge by expounding on these attacks, proffering efficient measures to detect network intrusions, and introducing an ensemble classifier: a combination of 3 different machine learning algorithms. An ensemble classifier is used for detecting remote to local (R2L) attacks, which showed the lowest level of accuracy when the network dataset is tested using single machine learning models but the ensemble classifier gives an overall efficiency of 99.8%.
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    On-Load Measurement Methods for Distribution Transformers Operational Performance
    (Elsevier Ltd., 2020-10-24) Lambe Mutalub Adesina; Ademola Abdulkareem; Olalekan Ogunbiyi; Oladimeji Ibrahim
    Transformers are the most important equipment used in power systems. It ensures network stability and reliability. Transformer fails over time due to several factors such as overload, poor insulation, cellulose deterioration, poor dielectric strength of the oil, etc. However, transformer owners are finding it difficult to monitor the performance of distribution transformers (DT) in their place of application which results into system failure. Analyses of this distribution transformer performance required that a distribution transformer be put on-load and the secondary terminals link to Power Quality and Energy Analyzer equipment (Fluke 435 Series II). This paper presents a methodology of carrying out an experimental set-up of on-load reliability measurements of the two distribution transformers, 500 kVA and 300 kVA, 11/0.415 kV as a case study. Recommendations for the operations and maintenance engineers in charge to comply are discussed. This approach using the prescribed power quality equipment gives a reliable experimental method of evaluating the performance of distribution transformers. • Maintaining the selected distribution transformer on – load prior to and during the experiment. • The setting of an experimental circuit to determine the operational parameters involving DT connection to Power Quality and Energy Analyzer (PQEA) equipment. • It utilizes a personal computer to download the measured parameters for graphical and statistics analysis.
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    Predicting Extrusion Process Parameters in Nigeria Cable Manufacturing Industry Using Artificial Neural Network
    (Elsevier Ltd, 2020-07-01) Ayokunle Adesanya; Ademola Abdulkareem; Lambe Mutalub Adesina
    The extrusion process is a very complex process due to the number of process parameters that are associated with it which are prone to high fluctuations. The main purpose of this work is to determine the realistic extrusion process parameters in the thermoplastic extrusion process in Nigeria cable manufacturing industries with the use of an artificial neural network. Conventionally, the use of trial-and-error technique which involves full-size experiments is generally used to determine the process parameters in the thermoplastic extrusion process. This conventional technique is expensive and it is also time-consuming. The use of an artificial neural network to predict extrusion process parameters before plant execution will make extrusion process operations more efficient. This technique also bridges the gap that exists between theoretical analysis and real manufacturing systems because real manufacturers' data was used. The neural network was developed in a MATLAB environment and was trained with a supervised learning method based on Levenberg Marquardt Algorithm and the developed ANN model is capable of predicting manufacturing process parameters for different grades of PVC thermoplastic material.
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    The Electricity Security in Nigeria: Design and Analysis of 750-kV Mega Grid
    (International Research Publication House, 2020-09-01) Ademola Abdulkareem; Victoria Oguntosin; Oluwatimileyin Dare; Adesina Lambe Mutalub
    Nowadays, due to the ever-increasing global energy demand and the complex option for an individual to install renewable power generation at his/her residence, it has become imperative to operate power plants that deliver energy to transmission and distribution systems at a reduced power loss and at the same time maximize efficiency. Therefore, the need arises to construct cost-effective high transmission lines considered at Extra High Voltage (EHV) levels. In this study, the mechanical structures and electrical line parameters of a 750-kV single-circuit 4 conductors per bundle based on existing standards were designed. These EHV levels are then analyzed and the results obtained are compared with the 330kV lower voltage levels in order to extract the benefits. The implementation of the designed 750-kV grid in the Nigeria transmission system results in a significant reduction in the systems’ power losses in comparison to the existing 330-kV system.