DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING

The main purpose of the project was to design a 3.5KVA inverter which makes use of both solar and mains or grid supply for charging the batteries. This is to reduce the frequency of power outages experienced in our homes and businesses. The project was carried out with the use of two 12V batteries connected in series to give a total of 24V DC which would serve as input for the inverter when on inverting mode and give an output of 220V AC for household appliances. Incorporated within the inverter was load control features, such that when the inverter stops charging and starts inverting, at a particular battery level set by the user, the heavy loads would be cut off while supply of power to the light loads continues. But when critical battery level is reached the light loads are also cut off and the inverter shuts down. This was done using Microcontroller in controlling relays which either powers on the load or cuts off the load when the battery is low. The proposed inverter design has two outputs through which load management was achieved. One of the outputs is designated to light loads and the other to heavy loads. The Microcontroller DSPIC30F4012 controls the load stage which can be programmed through the keypad to monitor the output power to the loads in output one and two, to ensure they do not draw power beyond the limits programmed by the user. To achieve this, the Microcontroller cuts off either of the outputs which exceed the set limit. The project was successful and the test results obtained was satisfactory. The inverter's operation was consistent with the design and the desired control of power consumption and power management was achieved.

This study evaluates the economic viability of solar farms as a sustainable energy solution for residential communities in Nigeria. The research aims to determine whether solar farms can provide a cost-effective alternative to the national grid by analyzing key economic factors, including initial investment, operational costs, and long-term financial benefits. The study also explores the environmental impact of solar farms, highlighting their potential to reduce carbon emissions and enhance energy security for households. By assessing various ownership models and financial incentives, the research provides insights into the feasibility of large-scale solar
adoption in residential areas.The methodology involves a detailed load analysis for a 100-household community, calculating daily energy consumption and peak load demand. The study designs a solar farm using 806 monocrystalline solar panels, a 400 kVA inverter, and necessary protection devices. Cost estimation covers component procurement, labor, land acquisition, and annual maintenance. Financial modeling incorporates revenue generation from surplus energy sales to the grid and cost comparisons with traditional electricity tariffs. A sensitivity analysis evaluates the impact
of rising grid electricity prices on the long-term economic benefits of solar farms.

This project focuses on the design and construction of a smart electricity meter using Internet of Things (IoT) technology to enable efficient energy monitoring and management. The system is built around the ESP32 micro\controller, which controls data acquisition, processing, and wireless transmission to the ThingSpeak cloud platform. The PZEM-004T measurement module is employed to accurately measure voltage, current, power, and energy consumption in real time. A DC-DC buck converter provides a regulated power supply, ensuring stable operation of the ESP32 and peripheral components. Data collected by the meter are uploaded to ThingSpeak, where users can visualize live readings, generate graphical trends, and analyze consumption patterns through an interactive dashboard. This allows for remote monitoring, fault detection, and informed decision-making regarding energy usage. The prototype demonstrates reliable performance, high accuracy, and cost-effectiveness compared
to conventional meters. By integrating embedded systems with IoT-based cloud services, the developed smart meter promotes efficient power utilization, user awareness, and modern smartgrid compatibility. Overall, the project highlights a practical approach to advancing energy management through low-cost IoT solutions.

The rapid growth in energy demand and the increasing need for accurate monitoring have made traditional energy meters inadequate for modern applications. This project presents the design and implementation of an IoT-Based Smart Energy Meter capable of measuring, displaying, and transmitting real-time electrical data over the internet. The system uses an Arduino Uno as the main controller, integrated with a PZEM-004T power sensor to measure voltage, current, and power consumption. The readings are displayed locally on a 16×2 LCD screen and simultaneously transmitted to the ThingSpeak IoT platform through an ESP-01S Wi-Fi module, allowing remote monitoring through mobile or web interfaces.
The device also includes an automatic overload protection mechanism, which disconnects the load using a relay and triggers an alarm whenever the current exceeds a set threshold. Supporting components such as transistors (BC548), a 7805 voltage regulator, LED indicators, and a buzzer ensure system stability and safety. The entire circuit is powered by a 12V DC adapter, regulated to 5V for the control units. Testing results show that the system provides accurate readings with less than 3% deviation compared to a standard energy meter. It successfully transmits data to the cloud and reacts promptly to overload conditions. This project demonstrates a low-cost, reliable, and efficient solution for smart home energy management and offers a foundation for future improvements such as mobile app integration and multi-load monitoring

This project presents a comprehensive study on the reverse engineering of a Pulse Width Modulation (PWM) Low-Frequency Hybrid Inverter used in renewable energy applications. The primary objective was to analyze, understand, and document the internal architecture, components, and operational principles of the inverter through a systematic disassembly and evaluation process. The study focused on identifying key functional sections namely, the oscillating stage, power stage, and transformer stage along with their respective roles in energy conversion and control.

The rapid expansion of fifth-generation (5G) wireless networks demands antenna arrays with wide bandwidth, high gain, and efficient beamforming capabilities to facilitate ultra-high-definition video streaming, extensive Internet of Things (IoT) connectivity, and communications with minimal latency. Nevertheless, traditional microstrip patch antennas continue to face fundamental challen0ges, including limited bandwidth, strong mutual coupling in array configurations, and reduced radiation efficiency caused by dielectric and surface wave losses. These challenges hinder their suitability for high-performance 5G applications. This project presents the design and simulation of a 4×4 microstrip patch antenna array optimized for sub-6GHz 5G applications. The Rogers 4350B substrate is utilized because of its low-loss characteristics and stable dielectric properties. To improve performance, U-shaped slots are added to the radiating elements, and a Defected Ground Structure (DGS) is incorporated into the ground plane. The design, analysis, and optimization of the antenna are carried out using ANSYS HFSS, focusing on achieving wide impedance bandwidth, high gain, and improved inter-element isolation without physical fabrication. The selection of materials, substrate parameters, and design dimensions are carefully chosen to facilitate future fabrication and experimental validation. Simulation results show that the proposed antenna achieves a gain of 10.64dB, a bandwidth of 180MHz, radiation efficiency of 72.3%, and a return loss (S11) of –19.96dB at 3.5GHz. In comparison, the conventional 4×4 array of the same dimensions without slots and DGS recorded a gain of 10.31dB, no substantial bandwidth as the return loss at the resonance frequency, 3.5GHz, is above the -10dB line, efficiency of 64.39%. The observed improvements are primarily attributed to the DGS, which effectively suppresses surface waves, minimizes mutual coupling, and enhances current distribution uniformity across the array. Overall, the optimized DGS-based antenna demonstrates superior performance in terms of gain, bandwidth, and element isolation, making it a strong candidate for compact and efficient sub-6GHz 5G base station and user terminal applications. The findings of this study provide a useful framework for further research and practical realization of high-performance antenna arrays for next-generation wireless communication systems.

The rapid expansion of fifth-generation (5G) wireless networks demands antenna arrays with wide bandwidth, high gain, and efficient beamforming capabilities to facilitate ultra-high-definition video streaming, extensive Internet of Things (IoT) connectivity, and communications with minimal latency. Nevertheless, traditional microstrip patch antennas continue to face fundamental challen0ges, including limited bandwidth, strong mutual coupling in array configurations, and reduced radiation efficiency caused by dielectric and surface wave losses. These challenges hinder their suitability for high-performance 5G applications. This project presents the design and simulation of a 4×4 microstrip patch antenna array optimized for sub-6GHz 5G applications. The Rogers 4350B substrate is utilized because of its low-loss characteristics and stable dielectric properties. To improve performance, U-shaped slots are added to the radiating elements, and a Defected Ground Structure (DGS) is incorporated into the ground plane. The design, analysis, and optimization of the antenna are carried out using ANSYS HFSS, focusing on achieving wide impedance bandwidth, high gain, and improved inter-element isolation without physical fabrication. The selection of materials, substrate parameters, and design dimensions are carefully chosen to facilitate future fabrication and experimental validation. Simulation results show that the proposed antenna achieves a gain of 10.64dB, a bandwidth of 180MHz, radiation efficiency of 72.3%, and a return loss (S11) of –19.96dB at 3.5GHz. In comparison, the conventional 4×4 array of the same dimensions without slots and DGS recorded a gain of 10.31dB, no substantial bandwidth as the return loss at the resonance frequency, 3.5GHz, is above the -10dB line, efficiency of 64.39%. The observed improvements are primarily attributed to the DGS, which effectively suppresses surface waves, minimizes mutual coupling, and enhances current distribution uniformity across the array. Overall, the optimized DGS-based antenna demonstrates superior performance in terms of gain, bandwidth, and element isolation, making it a strong candidate for compact and efficient sub-6GHz 5G base station and user terminal applications. The findings of this study provide a useful framework for further research and practical realization of high-performance antenna arrays for next-generation wireless communication systems.

Solar photovoltaic (PV) technology is a critical low-carbon solution, but its performance is severely compromised by shading. This study addresses the persistent problem of partial shading, which causes disproportionate power losses and creates thermal stress risks like hot spots.This research aims to quantify the effect of shading on PV panel voltage, current, and power output under controlled laboratory conditions.The methodology employed an experimental approach using an SES TPS-3720 Solar Energy Trainer. Experiments measured performance under 0% (baseline), 50% (partial), and 100% (full) shading.The study also evaluated the impact of shading material optical properties by testing opaque (wood), semi-opaque (paper), and translucent (plastic film) materials. Measurements were recorded across five irradiance levels using both LED lamp and DC motor loads.Key findings demonstrate a highly non-linear performance degradation. Partial shading covering 50% of the panel area resulted in a 65-70% power loss, far exceeding a proportional reduction. Full shading with opaque (wood) or semi-opaque (paper) materials caused a 100% power loss, eliminating all usable current. Translucent plastic film caused the least degradation (approx. 23% power loss).The results confirm that a material's optical transmittance, not its physical density, is the dominant factor determining shading severity.These findings validate established photovoltaic theory and highlight the critical importance of shadow avoidance in system design. The study reinforces the necessity of mitigation strategies such as bypass diodes and module-level power electronics (MLPE) in shade-prone installations.

This project focuses on designing a monitoring system using an Internet of Things (IoT) device that sends data to Thingspeak, a cloud-based platform. Solar system are affected by various factors such as temperature, weather condition and light intensity, on their output performance. These factors can lead to inefficient performance, increased maintenance cost and so on. Therefore, the aim of the project Is to design and implement an intelligent virtual monitoring system that utilizes IoT to monitor PV solar panel array. To achieve this work, the role was centred on light sensor, voltage sensor and temperature sensor. These sensors are connected to on IoT gateway or a local data acquisition unit that acts as a bridge between the sensors and the internet collects the sensors data and prepares it for transmission to the cloud. Testing the monitoring system works satisfactorily. Having humidity of 85g/m3 on average, voltage of 35.78V during the day and 0V at night, temperature as high as 300c and low as 270c and luminance of 4201cd/m2 during the day and 0cd/m2 at night.

This project focuses on designing a monitoring system using an Internet of Things (IoT) device that sends data to Thingspeak, a cloud-based platform. Solar system are affected by various factors such as temperature, weather condition and light intensity, on their output performance. These factors can lead to inefficient performance, increased maintenance cost and so on. Therefore, the aim of the project is to design and implement an intelligent virtual monitoring system that utilizes IoT to monitor PV solar panel array. To achieve this work, the role was centred on light sensor, voltage sensor and temperature sensor. These sensors are connected to on IoT gateway or a local data acquisition unit that acts as a bridge between the sensors and the internet collects the sensors data and prepares it for transmission to the cloud. Testing the monitoring system works satisfactorily. Having humidity of 85g/m3 on average, voltage of 35.78V during the day and 0V at night, temperature as high as 30 0c and low as 27 0c and luminance of 4201cd/m2 during the day and 0cd/m2 at night