This project involved designing and developing a 1.5 KVA solar power system as an alternative power source for teaching and learning. It was initiated to address the major challenge of inadequate and unreliable power supply at the Federal College of Education Technical Asaba. The study employed a design and development approach following standard engineering stages, including problem identification, system specification, design analysis, component selection, construction, and performance testing. Materials used included four 250W solar panels, 60 Amps, MPPT charge controller, a 240 Ah deep-cycle battery, and a 1.5 KVA inverter. These components were assembled into the system. The inverter's performance was evaluated through various tests: a no-load test to verify output voltage and frequency, a load test using instructional equipment to assess stability, and a battery discharge test to determine backup duration. Additional tests on mobility and safety assessed ease of movement and compliance with electrical safety standards. Test results were compared with the design specifications to evaluate effectiveness for educational purposes. During the no-load test, the inverter produced approximately 230 V AC at 50 Hz, meeting standard utility requirements. At an estimated load of 484 W, about 80% of the inverter’s rated capacity, the output remained stable without shutdown or overheating, indicating suitability for continuous use in classrooms and labs. The battery discharge test showed an average backup of 3.5 to 4.1 hours under full instructional load, closely matching the estimated backup time during design.

Development of a Solar-Powered EV Charging Station using MPPT Charge Controller and Boost Converter

The design, installation, and performance assessment of a hybrid renewable energy water pumping system that incorporates solar photovoltaic panels, wind turbines, and an energy storage unit are presented in this study. By integrating solar and wind energy sources with a charge controller and battery storage, the system is designed to solve the intermittency and variability issues that these sources provide. This ensures a consistent and dependable water supply that is appropriate for remote and off-grid settings. A vertical-axis wind turbine and solar panels are used in the proposed water pumping system to capture natural energy, which is then stored in a 12V battery under the supervision of a specially made charge controller. A DC water pump designed for domestic water supply and irrigation is powered by the stored energy. The system's ability to provide steady water flow and effective energy management is demonstrated by experimental prototype testing conducted in a variety of weather conditions. By lowering reliance on traditional power grids and fossil fuels, the hybrid system exhibits better operational efficiency, increased dependability, and environmental sustainability as compared to single-source renewable pumping alternatives. In addition to lowering greenhouse gas emissions and fostering energy independence, this work emphasizes the potential of combining several renewable energy sources with energy storage for sustainable water resource management in rural and developing regions.

Although electric vehicles offer increased user comfort, the range limitation remains one of their most significant challenges, primarily due to battery capacity. Moreover, for electric vehicles—classified as zero-emission—it is crucial that the electricity used originates from renewable energy sources. In this study, electricity was generated using wind energy while the vehicle was in motion, enabling the batteries to be charged during operation. This approach aims to reduce charging time and extend the vehicle's range. A wind turbine was mounted on the front bumper of a sedan-type vehicle used for the experiments, without altering the total frontal projection area. The tests were conducted along the same route, in both directions, under windy conditions with wind speeds of 1 m/s. It was observed that energy production was more efficient when the wind blew against the direction of the vehicle's motion compared to when it came from behind. As the vehicle speed increased, the rotational speed of the wind turbine also increased, resulting in greater energy generation. The AC voltage generated by the wind turbine, which varied due to changes in load and vehicle speed, was rectified and stabilized at approximately 18V DC by the battery charging control unit, allowing the batteries to be charged at all vehicle speeds.

Aims: The aim of this study was to develop and evaluate a solar-powered, sensor-based hydroponic maize fodder production system capable of providing a sustainable, energy-efficient and year-round solution for green fodder cultivation. Study Design: Engineering development followed by system evaluation under controlled hydroponic growing conditions. Place and Duration of Study: Department of Farm Machinery and Power Engineering and Department of Renewable Energy Engineering, University of Agricultural Sciences, Raichur, Karnataka, India. Methodology: A sensor-integrated hydroponic fodder unit was developed using AHT10, AHT25 and DHT11 sensors connected to an Arduino Uno for automated monitoring of temperature and humidity. Solar PV panels with a charge controller and battery storage powered the system. The structure consisted of multi-tier trays with micro-sprinklers to ensure uniform irrigation. Sensors were evaluated based on mean absolute error and accuracy. Hydroponic maize was grown under different seed rates, temperatures and harvest periods, and green fodder yield was recorded in kg m⁻². Results: Among the sensors tested, AHT10 demonstrated the highest accuracy and lowest mean absolute error for both temperature and humidity, making it the most suitable for automated hydroponic control. Maximum green fodder yield of 19.78 kg m⁻² was achieved at an optimum temperature of 29–32 °C, 11-day harvest period, and 600 g seed rate. The solar-powered system ensured uninterrupted operation while reducing dependence on external electricity. Conclusion: The developed solar-powered, sensor-based hydroponic maize fodder unit proved efficient, cost-effective and highly suitable for rural farming systems. It offers a sustainable solution for year-round green fodder production, overcoming limitations of traditional cultivation such as high labour, water requirement and seasonal dependence.

The maximum power extraction (MPE) from a solar PV panel depends on the maximum power point tracking (MPPT) algorithm and the connected PV power optimizer. For the effective MPE, precise MPPT algorithm and power optimizer needs to be designed. To facilitate this design, a detailed mathematical model of the solar PV power optimizer system is needed for understanding the effect of various power electronic components on stability and their behaviour in dynamic operating conditions. This paper presents a detailed small-signal modelling and stability analysis of buck converter–based solar PV power optimizer in continuous and discontinuous conduction modes for low-voltage DC (LVDC) applications. The small-signal modelling is developed by considering the PV power optimizer’s input filter capacitance and equivalent series resistance (ESR) of the power electronic components. A lucid analysis on the effect of input filter capacitance on PV power optimizer’s stability is presented. From the theoretical analysis and experimental validation, it has been observed that the MPPT in buck converter–based PV power optimizer is open-loop stable. A pole-zero cancellation in the transfer function of PV current to the duty cycle (I PV ) under both continuous and discontinuous conduction modes is observed, which leads to resiliency in the PV system’s stability for any variations in input capacitance.

The increasing need for sustainable and decentralized power generation has accelerated the development of microgrid technologies capable of integrating renewable resources. This study presents the design and implementation of a solar energy–based microgrid monitoring and control system using an Arduino Uno platform. The proposed system utilizes photovoltaic (PV) modules as the primary power source and incorporates sensors for real-time measurement of voltage, current, temperature, and battery state-of-charge (SOC). An MPPT-enabled charge controller ensures efficient energy harvesting, while the Arduino Uno performs data acquisition, energy management, and load-switching operations. The system communicates key operational parameters through an LCD interface and optional IoT connectivity for remote supervision. Prototype results demonstrate stable power delivery, improved energy utilization, and effective load management for small-scale microgrid environments. This cost-effective and modular architecture provides a scalable solution for rural electrification, smart energy distribution, and renewable-integrated microgrid applications, highlighting its potential for wider deployment in sustainable energy systems

Stand-Alone Photovoltaic (SAPV) systems play a vital role in providing clean and reliable electricity for remote and off-grid communities where grid expansion is economically or technically unfeasible. Their economic feasibility and technical reliability, however, depend strongly on accurate component sizing and system configuration, which require advanced optimization techniques. In this study, the Meerkat Optimization Algorithm (MOA) is applied to optimize two SAPV configurations. System 1 integrates a photovoltaic array, battery storage, and a hybrid inverter, while System 2 consists of a photovoltaic array, battery storage, a solar inverter, and a charge controller. The optimization focuses on minimizing Life Cycle Cost (LCC) and Levelized Cost of Energy (LCOE), which are widely recognized as reliable indicators of long-term cost-effectiveness and financial viability. To validate the performance of MOA, its results are benchmarked against three well-established metaheuristic algorithms: Particle Swarm Optimization (PSO), Firefly Algorithm (FA), and Slime Mould Algorithm (SMA). Simulation results show that System 1 consistently achieves lower LCC and LCOE compared to System 2, primarily due to its reduced component count and simplified integration. Moreover, MOA demonstrates enhanced optimization performance by converging more rapidly and delivering more stable solutions across multiple independent runs. In contrast, PSO, FA, and SMA exhibit slower convergence and greater variability in outcomes. Importantly, the performance differences are statistically meaningful, as MOA achieved consistently lower mean values and smaller standard deviations. These findings highlight MOA as an effective and reliable optimization tool for SAPV systems and provide practical insights to support sustainable rural electrification planning.

Abstract - The SolarSwift project proposes a stand-alone, solar-powered USB charging multinode station intended for public use in areas such as bus stops, railway stations, college campuses, marketplaces, and rural locations. In recent years, mobile phones have become essential for communication, digital transactions, navigation, and emergency services. However, the availability of convenient and reliable charging facilities remains limited, particularly in regions affected by irregular grid power supply. To overcome this limitation, the SolarSwift system utilizes a 12 V photovoltaic panel combined with a charge controller, a rechargeable battery, and a high-efficiency DC–DC buck converter to provide a stable and regulated 5 V output suitable for multiple USB charging ports. In addition to device charging, the system integrates an automatic LED streetlight controlled using a light-dependent resistor (LDR), allowing illumination during nighttime conditions without reliance on external electricity. The design approach emphasizes efficient energy management, compact structure, voltage stability, and battery protection to ensure reliable operation under varying environmental conditions. Performance evaluation through practical observations and simulation indicates consistent charging performance, sufficient energy storage, and dependable operation throughout day and night cycles. The SolarSwift system highlights the potential of decentralized solar solutions to improve public convenience, reduce dependence on conventional power sources, and promote sustainable and inclusive energy infrastructure in both urban and rural settings. Keywords: solar-powered charging, renewable energy, USB charging station, buck converter, automatic streetlight, public infrastructure.

Indonesia’s vast horticultural land faces serious threats from Bactrocera fruit fly infestations, a type of fruit fly in the Tephritidae family that causes rotting plants, reducing the quality of plantation and agricultural products, and even crop failure. The purpose of this study was to design a fruit fly (Bactrocera) trap ApelB version 1.1, using the Cockcroft-Walten Circuit, Methyl Eugenol, PIR HC-SR501 sensor, Arduino Uno ATmega328P, powered by electricity from a Solar Power Plant/System (PLTS) with a panel capacity of 10 Wp, Solar Charge Controller 10 A and a 14.8 V 2.5 Ah battery. The ApelB version 1.1 test method on agricultural land for 24 hours used methyl eugenol to attract fruit flies to enter the trap. Electricity from the PLTS functions to eradicate fruit flies that land on the electric net trap. The findings of ApelB version 1.1 successfully attracted, detected through sensors, and eradicated fruit flies with electric shocks. The capture rate was 80% in lab tests, while corn and chili field trials caught an average of 148–150 fruit flies. ApelB version 1.1 can suppress attacks and fruit fly populations, with a PLTS system and energy storage battery. This tool is guaranteed to operate 24 hours automatically.

Traditional fishermen in coastal communities often rely on ice blocks to preserve their catch, a method that is costly, inefficient, and unable to maintain stable temperatures during long fishing trips. This study presents the development and implementation of a hybrid freezer palka system that integrates solar panels and engine-driven alternator power to provide a continuous and energy-efficient cooling source for small fishing vessels. The research aimed to design a reliable cooling system capable of maintaining low temperatures during extended operations at sea while reducing operational costs for fishermen.The methodology involved system design, component integration, and field testing with partner fishermen in Kampung Mandar, Banyuwangi. The hybrid system consists of a 100 Wp solar panel, MPPT charge controller, 65 Ah battery, alternator, inverter, and a 125-Watt freezer installed inside an insulated palka box. Field testing was conducted over 21 consecutive days to evaluate temperature stability, operating duration, and energy performance.Results show that the system successfully reached temperatures between –2 °C and 5 °C within approximately 80 minutes and maintained stable cooling for more than 8 hours per trip using combined solar and engine power. The hybrid configuration significantly reduced dependence on ice blocks, decreased operational costs, and improved fish quality upon landing. The findings indicate that this hybrid freezer palka system is an effective, sustainable, and practical technological solution to support fishermen’s productivity, especially in small-scale traditional fisheries..

ABSTRACT This paper presents a full‐range adaptive charging control strategy for PT‐symmetric wireless power transfer (WPT) systems, specifically designed to address the challenges of fluctuating mutual inductance, variable loads, and extended transmission distances in dynamic applications such as drone in‐flight charging. The proposed method achieves seamless constant‐current (CC) and constant‐voltage (CV) charging across a wide range of mutual inductance and load variations. Leveraging the frequency‐splitting phenomenon inherent in PT‐symmetric circuits, the system identifies secondary‐side resonant characteristics that traditional methods often fail to detect. Mutual inductance and load variations are dynamically estimated through primary‐side voltage and current measurements, eliminating the need for direct communication with the secondary side. A hybrid control strategy is adopted: Phase‐shift control is applied in the strong coupling region to ensure CC/CV operation, while pulse‐width modulation (PWM) control maintains output voltage regulation under weak coupling. The system adaptively adjusts the operating frequency and compensates for mutual inductance variations in real time, ensuring stable energy transfer across coupling region transitions. Experimental validation confirms the method's effectiveness, demonstrating a rapid control strategy switching time of 287 ms and a 56.7% expansion in the CV charging range compared to conventional approaches. This work introduces a robust, scalable, and adaptive control framework for PT‐symmetric WPT systems, significantly improving energy delivery stability and operational flexibility under dynamic wireless charging conditions.

Predictive control of eV charging for wide-area reduction in grid congestion

Super twisting sliding mode control for high-efficiency and fast charging of electric vehicles using current-fed resonant converter: 400 V and 800 V validation

Abstract This study explores the development and performance evaluation of a pilot-scale sustainable oxyhydrogen production system, aiming to address the urgent need for clean and renewable energy solutions in the Philippines. The system utilizes microhydropower as a renewable source to drive electrolysis for hydrogen and oxygen generation. A 220-liter elevated tank supplies water to a Pelton turbine, which powers a permanent magnet generator connected to a charge controller and battery bank. The stored energy runs a 17-plate wet cell electrolyzer, producing consistent hydrogen output. The study assessed temperature, flow rate, gas output, and electrical parameters under various test conditions. Results show a stable 1 Liter per Minute (LPM) hydrogen production rate at 12V and 5A, with higher Potassium Hydroxide (KOH) concentrations enhancing output. This research validates the feasibility of oxyhydrogen systems powered by off-grid renewable sources, with implications for energy independence, environmental sustainability, and rural electrification. The findings support the national goals of integrating hydrogen into the energy mix, providing a clean and scalable solution suitable for communities with abundant water and renewable energy resources.

Artificial intelligence prediction of maximum power point tracking voltage and current based on battery for sensor reduction and complexity minimization for photovoltaic charge controller

This paper presents an adaptive charging system for lithium-ion batteries using an Elman backpropagation neural network (EBNN) integrated with a PID controller and a ZETA converter. The system dynamically identifies the battery type and adjusts the charging voltage accordingly. The EBNN model was trained using 1441 samples of initial current and voltage data, achieving a mean squared error (MSE) of 7.64×10⁻¹⁴. A ZETA converter enables both step-up and step-down voltage regulation, while the PID controller ensures stability toward the predicted setpoint. Simulations in Simulink were conducted on four lithium-ion battery types with setpoints of 4.4 V, 8.8 V, 14.4 V, and 21.6 V. The results show that the PID-regulated output voltage closely matches the target with a maximum deviation of ±0.05V and an average voltage error of 0.1725%. The system achieves fast response times between 0.015 and 0.033 seconds. Extended testing through 24 randomized trials confirmed consistent identification and regulation across varying battery types. These findings validate the proposed EBNN-PID-based charging system as a highly accurate, flexible, and efficient solution for managing lithium-ion battery charging in real-time embedded applications.

This paper reviews the growing importance of solar energy in electricity generation and its potential to help resolve the global energy crisis. As traditional fossil fuels decline and environmental challenges become more urgent, solar power stands out as a renewable, clean, and abundant energy source. The review explores two main solar technologies— Photovoltaic (PV) systems and Concentrated Solar Power (CSP) explaining how they work, their efficiency levels, and patterns of global adoption. It also highlights the rapid progress in solar technology, particularly the falling cost of solar panels and the increasing installation capacity around the world. The discussion includes how solar energy is integrated into existing power grids, its role in enhancing grid reliability, and how well it works with current infrastructure. Essential system components such as solar cells, inverters, and charge controllers are examined for their roles in system performance and design. Furthermore, the paper outlines various advantages of solar power, such as its environmental friendliness, suitability for remote regions, scalability, and potential to boost energy independence and support economic development. The review concludes by emphasizing the need for ongoing innovation in solar technology to support a more sustainable energy future.

This paper addresses an effective, reliable and fast charging method for maximizing lithium-ion battery performance, longevity, and safety. The proposed multi-stage current charging mechanism utilizes a modified multi-stepped constant current-constant voltage based on the particle swarm optimization (MMSCC-CV-PSO) algorithm. The proposed MMSCC-CV-PSO charging strategy demonstrates a significantly faster charging performance compared to traditional charging techniques, including the widely used constant-current constant-voltage (CC-CV) method and the conventional multistage constant current (MSCC) approach. This enhanced efficiency highlights the superiority of the proposed method over existing solutions discussed in the literature. The simulation results confirm the practicality and superior performance of the proposed design strategy. Compared to the conventional MSCC method, the proposed approach achieved a considerable reduction in battery charging time, indicating a more efficient energy transfer process. Additionally, it led to a noticeable decrease in heat generation within the battery during the charging cycle, reflecting improved thermal management. These outcomes collectively demonstrate the effectiveness of the proposed method in enhancing both the speed and safety of the charging process, making it a promising solution for advanced battery management systems. The simulation model was developed and successfully implemented using the MATLAB/Simulink environment, providing a flexible platform for testing and evaluating the proposed charging strategy.

This research work titled ‘design and implementation of solar powered automatic street light control using embedded image and motion sensor’, is aimed at building a device that will control street light automatically. The system is powered by photovoltaic panels which charges the battery during the day, and provides energy for the LED lamp during the night. An Automatic Street Light Control System is a simple but powerful concept, which uses transistor as a switch to trigger ON and OFF the street light automatically. The system was developed using embedded system design methodology and the key components includes PIR sensor, LDR sensor, Atmega8A microcontroller and solar powered battery pack. The circuit design commenced with the introduction of the circuit block diagram, which is the block representation of the operational mark of the operational units of the system. The passive infra-red (PIR) sensor which consists of pyroelectric element and lens, has the ability to detect motion of object or human at a reasonable distance and send command of about 0-10v dimming signal to the microcontroller. The implementation process was done using bread-board and later transferred to the vero board, before incorporating into the lighting device. The solar module that will convert solar energy into electrical energy was also designed to provide energy for the street lighting device. The work reduced attack on people especially at night by providing light for residents of the streets. The streetlight turns ON in full brightness when motion is detected, otherwise the lights will be switched to dim brightness. The automatic street light control system produced an overwhelming result when put to test as the controls uses sensors to adjust brightness from dusk to down, thereby reducing unnecessary power consumption to save energy and extend their life span. It is suggested that this design could save up to 45% or more energy compared to conventional streetlight through features like automatic on/off, dynamic dimming and battery charge controller. This marks the success of this work since it was intended to provide security and save energy.