Articles

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51 articles
31
Research Article DOI: 10.67203/zjeet.2025.oujsl7gb

Derived Specific Rain Attenuation at Stand-Alone Milimeter Wave Bands for Samaru Zaria, Nigeria

I. Abdullahi*, A. Abdulkarim, U. Musa, I. A. Shehu, A. Aliyu

This work studies rain–induced effect on some envisaged 5G links located at Samaru Zaria, Kaduna State, Nigeria, operating at 26 GHz, 38 GHz and 42 GHz in a MATLAB environment; using 3–year rain data obtained from Em60G™ datalogger–powered metrological setup of the Nigerian Metrological Agency (NiMet) located at Ahmadu Bello University, Zaria. Lavergnat and Gole (LG) model was used to derive the 1...

Sep, 2025 pp. 65-70 8 views 1 downloads
32
Research Article DOI: 10.67203/zjeet.2024.4617wkxl

Load Frequency Control of a Two Area Network using Fractional PID Controller

Abdulazeez Abbas*, A.S. Abubakar, Zaharadeen Musa

This paper simulates load frequency control (LFC) problem in a two-area power system using a traditional PID controller and a Fractional Proportional-Integral-Derivative (FPID) controller. The study aims to enhance the stability and performance of the power system by minimizing frequency deviations and maintaining the desired power exchange between the interconnected areas. The FPID controller is ...

Sep, 2024 pp. 67-78 4 views
33
Research Article DOI: 10.67203/zjeet.2020.jxydba8j

NUMERICAL COMPARISON OF AERODYNAMIC PERFORMANCE OF NACA 4415 FISH TAIL AIRFOIL BLADE WITH CONVENTIONAL NACA 4415 AIRFOIL BLADE

S. I. Sa’id*, A.B. Aliyu, A.A. Adam

The numerical values of the lift coefficient and drag coefficient of NACA 4415 fish tailairfoil blade and conventional NACA 4415 airfoil blade were obtained using CFD programANSYS-FLUENT at angle of attack from -6° to 42°. The values of the stall angle and anglecorresponding to the maximum lift-to-drag ratio for both blades were determined andcompared. The result indicated that Lift and drag coeff...

Sep, 2020 pp. 67-72 5 views
34
Research Article DOI: 10.67203/zjeet.2019.qes7j7nt

COMPUTATIONAL COMPLEXITY ANALYSES OF ADAPTIVE EQUALIZATION ALGORITHMS IN LINEARLY DISPERSED CHANNEL SYSTEMS

O.E. Ochia*, E. Obi

This paper presents a framework for assessing the complexity of adaptive equalizationalgorithms in a linearly dispersive channel that produces unknown distortion. Threealgorithms are investigated including the Least Mean Squares (LMS), Recursive LeastSquares (RLS), and Recursive Least Squares Lattice (RLSL) algorithms with respect to themean square error (MSE) and the sample convergence speed. The...

Sep, 2019 pp. 67-73 4 views
35
Research Article DOI: 10.67203/zjeet.2025.80f2lqzh

Development of Deep Learning Model Based Resnet with SSD for Fault Detection in Distribution Network

A. Ango*, O. Ajayi, Z. Haruna, M. B. Mu’azu

This research proposes the development of deep learning model based residual network with single short multi box detector (resnet-SSD) for fault detection in distribution network. Power infrastructures are components used in the power system to generate, transmit or distribute power for the benefit of the consumers. These components include conductors, insulators, transformer, cross arm and many m...

Sep, 2025 pp. 71-79 6 views
36
Research Article DOI: 10.67203/zjeet.2023.pp4714m0

Voltage stability enhancement Scheme using PV-reinforced Dynamic Voltage Restorer

J. A. Joseph*, G. A. Olarinoye, A.S. Abubakar

Among the promising solutions proposed for the mitigation of the voltage instabilities is a series compensator known as Dynamic Voltage Restorers (DVR) due to its flexibility and cost effectiveness. Dynamic Voltage Restorer (DVR) also known as Static Synchronous Series Compensator (SSSC) is a series compensation technique used in the distribution and transmission system. The power flow through the...

Sep, 2023 pp. 73-86 7 views
37
Research Article DOI: 10.67203/zjeet.2019.00meni9c

MULTIPLE MONTE CARLO SIMULATED HIDDEN MARKOV MODEL FOR FUZZY TIME SERIES FORECASTING

A. T. Salawudeen*, A. Nurudeen, S. Garba, S. U. Hussein, M. L. Imam, I. F. Egbujo, B. Yahaya

This paper presents a Monte Carlo based Hidden Markov Model (HMM) for fuzzy timeseries forecasting. To make the nature of conjecture and randomness of forecasting morerealistic, the Monte Carlo method with different simulation size is adopted to estimate theforecasting outcome. To address the insufficiency in data associated with the HMM model,we adopted a method called smoothing. A number of simu...

Sep, 2019 pp. 74-86 4 views 1 downloads
38
Research Article DOI: 10.67203/zjeet.2024.5ikb3ah6

Design of Static Var Compensator for Voltage Stability Improvement in 30 bus network

A. Markus*, A.S. Abubakar, I. Seidu, Zaharadeen Musa

This paper presents a comprehensive study on the application of Static Var Compensator (SVC) devices for voltage stability and load flow optimization in the IEEE 30-bus power system. As modern power networks face increasing demand and complexity, maintaining voltage levels and minimizing power losses are critical challenges. This research investigates the impact of SVC compensation on bus voltage ...

Sep, 2024 pp. 79-80 6 views
39
Research Article DOI: 10.67203/zjeet.2025.b6olr5jj

Integrated Economic and Emission Dispatch of Hybrid Thermal-Photovoltaic Generation

I. Abdullahi*, U. Musa, B. Musa, A. Aliyu, Abdullahi Bala Kunya, S.A. Alkali, S. Awaisu

Due to the increasing demand for qualitative electric energy at a competitive price and reduced environmental deterioration, electric power generation systems should be optimally dispatched. In this paper, the Integrated Economic and Emission Dispatch (IEED) of hybrid thermal-photovoltaic power plants using Bat (Chiroptera) Inspired Algorithm (BIA) is presented. The IEED technique entails determin...

Sep, 2025 pp. 80-91 6 views
40
Research Article DOI: 10.67203/zjeet.2020.igrnn2ln

DECOMPOSITION APPROACH TO THE NEWTON- RAPHSON BASED HYDRO-THERMAL OPTIMAL POWER FLOW SOLUTION

Muyideen Olalekan Lawal*, OlusolaAderibigbe Komolafe

This paper presents a decomposition approach to the hydro-thermal optimal power flow problem to address the mathematical difficulty due to large number of variables and constraints associated with the problem. The decomposition of the problem is achieved by dividing the optimization period under consideration into hourly time intervals. The optimization problem for each time interval is first solv...

Sep, 2020 pp. 82-94 4 views