Charge Controller Research Articles

Performance Investigation of Wind/Photovoltaic/Fuel cell Hybrid Energy System for Stand-alone Power Supply

Large numbers of households in isolated areas in Nigeria were reported to have lacking access to national grid. Their basic electricity demand is served through fossil fuel generators which are costly and environmentally unfriendly. The fact that extension of national grid lines to those areas becomes difficult, renewable energy resources exploitation is the best alternatives. Wind and solar energy as clean abundantly available resources could be harnessed in a hybrids form with long-term storage devices for enhancing energy optimization and power stability. This paper investigated the performance of Wind-PV-Fuel cell Hybrid Energy Systems for stand-alone application. The performances of Wind-Battery-Fuel cell and PV-Battery-Fuel cell Hybrid Energy Systems were investigated by using Hybrid Optimization Models for Energy Renewable (HOMER), through cycle charging controls. The techno-economic Figure of merits for the optimal configurations from these systems was compared. The results revealed that Wind-Battery-Fuel cell Hybrid had been the best system for serving4.37kWh/day (1595kWh/yr) residential load demand. The system was reported with 321 kWh/yr excess electricity, 8.59 kWh/y unmet load and 10.5 kWh/yr capacity shortage. While, the Net Present Cost (NPC), Operation and Maintenance Cost (O&MC) and Cost of Energy (COE) were $25,951, $185 /yr and $1.229/kWh respectively. The result of sensitivity analysis, predicted the unmet load and capacity shortage to be declined by 0.0% each, with system autonomy of 7.9 days. Meanwhile, the NPC, O&MC and COE have decreased by 24.6 %, 8.1 % and 25.06 % respectively. This analysis confirmed that Wind-Battery-Fuel cell-Hybrid Energy System could be an economically viable and technically feasible for stand-alone power supply for isolated areas.

Impacts of Electric Vehicle Charging Station with Photovoltaic System and Battery Energy Storage System on Power Quality in Microgrid

The expected increase in electric vehicles necessitates an expansion in charging stations. However, this increase could introduce issues to the power grid, such as the deterioration of voltage stability and an increase in microgrid loading. To address these issues, innovative solutions are imperative. One potential solution is the implementation of charging control mechanisms. This paper analyzes the impact of a residential charging station on a low voltage microgrid from the power quality point of view using a one-year operation simulation. Thirty-seven charging station scenarios with different locations within the network were examined, including instances with no charging control and various combinations involving charging control, photovoltaic power plant, and battery energy storage system. The simulation results of the charging station without charging control show a decrease in some power quality indicators, such as exceeding voltage change thresholds after charging station connection and increasing power losses. On the contrary, the scenarios implementing charging control and local resources effectively mitigate the adverse effects of charging stations on the microgrid.

Stand-alone solar lighting system with Programmable Logic Controller

The circuitry modelling of the standalone photovoltaic (PV) maximum power point tracking (MPPT) lithium-ion battery charge controller is presented in this study using the MATLAB/Simulink environment. For the charge controller implementation, a DC-DC converter called a buck topology is used. The Perturb and Observe (P&O) MPPT algorithm monitors the solar panel’s peak power. The lithium-ion battery is charged in three stages by the battery charge controller. The model’s performance is analysed in terms of MPPT tracking performance, battery charging performance, and overall charge controller efficiency performance. With an MPPT efficiency of up to 99.9%, the performance result demonstrates that the MPPT is capable of tracking to the PV panel maximum point at any variation in solar irradiation. For small and medium standalone PV systems, this verified model aids in improved sizing of PV panels and battery energy storage. Techno-economic analysis refers to the assessment of the economic viability and profitability of using this type of lighting compared to other forms of lighting. The maintenance costs and efficiency of these systems can be improved even more by adding a programmable logic controller (PLC).

Artificial Intelligence Integration Driven Smart Grid Alternative Transforming the Future With Renewable, and Non-renewable Energy Sources

The evolving energy landscape necessitates a paradigm shift towards more sustainable, efficient, and resilient systems. This article explores integrating renewable and non-renewable energy sources within Smart Grid alternatives, highlighting the transformative role of Artificial Intelligence (AI). Renewable sources, like solar and wind, are essential for reducing carbon emissions but present challenges due to their intermittent nature. Non-renewable sources provide stability, ensuring a consistent power supply. AI's capabilities in predictive maintenance, demand response, energy forecasting, and grid optimization enhance grid efficiency and adaptability, facilitating the seamless integration of diverse energy inputs. Essential components of standalone systems, including batteries, charge controllers, and power conditioning equipment, are also examined for their contributions to system robustness and reliability. The Smart Grid, supported by AI and advanced technologies, represents a reimagined energy infrastructure poised to meet modern demands while promoting sustainability and resilience. This holistic approach promises a secure energy future, balancing efficiency with environmental stewardship.

Performance evaluation of a novel ev charging topology for standalone pv systems with charge controller

Performance evaluation of a novel ev charging topology for standalone pv systems with charge controller

Stability-Centric Design of a Droop-Mounted Adaptive Nonlinear Control for EV Charging in DC Microgrid

Stability-Centric Design of a Droop-Mounted Adaptive Nonlinear Control for EV Charging in DC Microgrid

Nonlinear Model Inversion-Based Output Tracking Control for Battery Fast Charging

Nonlinear Model Inversion-Based Output Tracking Control for Battery Fast Charging

Design Development and Construction of Solar Powered Fresh Juice Extracting Machine

One of the greatest problems of fruit farmers in Nigeria is their inability to process and add value to their produce. This results from the paucity of processing and preservation facilities or the prohibitive cost of imported ones, especially for low-income farmers who produce the bulk of the commodity. It therefore becomes imperative to design, develop and construct low-cost, durable, efficient and environmentally friendly machines to meet the needs of both the urban and, more importantly, the rural farmers with a view to improving their income and also making their produce available and affordable all year round. The machine components include feeding hoppers, a top cover, an auger conveyor housed in a cylindrical barrel, a juice sieve, a juice collector, a waste outlet, a transmission belt, a main frame, pulleys, bearings, 3hp DC motor, a control panel, a solar panel, 20Ah charger controller 100Ah Solar battery, breaker and control switch.

SIMULATION MODELING OF MULTI-PORT DC-DC CONVERTER IN MPPT SOLAR BATTERY CONTROLLERS UNDER NEURAL NETWORK CONTROL

Photovoltaic generation system - energy system, designed to convert useful solar energy through photovoltaic systems. It can consist of several components, including a solar array, DC/DC and DC/AC semiconductor converter, battery, filter or transformer, control system (CS). Depending on the application, photovoltaic systems can be operated as part of a self-contained power plant or operate on a network. Thus, it is possible to distinguish several basic configurations of photovoltaic generation systems. The standalone generation system is the most common configuration of photovoltaic generation systems, which contains rechargeable batteries (AB). This system is completely independent of the centralized power supply networks and is suitable for comfortable energy supply to consumers. The use of AB makes it possible to increase the reliability of the photovoltaic system and to extend the possibilities of using e.g. battery power is used during insufficient light or when the load exceeds the generation of solar cells. The scope of such configurations are lighting systems of residential and non-residential objects, power supply of houses and buildings, security systems and emergency power supply, power supply of remote residential and non-residential objects, Power supply to spacecraft, etc. Autonomous generation systems typically contain two transducers. The DC/DC converter acts as a battery charge controller. The control system for such a transducer may include the function of tracking the maximum power point for the maximum use of solar energy. The excess energy will be stored in AB. The DC/AC converter converts the DC current energy into the AC energy of the required frequency and voltage. The advantage of such a system is the possibility of using solar energy, both during the day and at night, due to the power of AB and the possibility of using the system at remote sites where there is no grid power supply. The disadvantage of such a system is the loss of double conversion of solar energy and the high cost of batteries. Artificial Neural Network (ANN) provides an alternative way to solve complex problems. A neural network, with the right structure, can compute the values of any continuous function with some predetermined accuracy. The neural network requires no knowledge of the internal parameters of the solar module, learns quickly, has the ability to optimize and approximate. Therefore, the use of INS to track the maximum power point is relevant and of practical and scientific importance. Keywords: multi-port DC converter, artificial neural network (ANN), rechargeable batteries (AB), pulse width modulation (PWM), solar panels (SP), MOSFET power keys

Soft-switching dual Active Bridge Converter-based Bidirectional On-Board Charger for Electric Vehicles under Vehicle-to-Grid and Grid-to-Vehicle Control Optimization

Electric Vehicles (EVs) are rapidly replacing conventional fuel vehicles, offering powerful, emission-free performance. This paper introduces an innovative three-phase bidirectional charger for Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) applications, strengthening the connection between EVs and the power grid. The charger employs a two-stage power conversion approach with advanced converters and a simplified dq-based charging control strategy. An efficient AC-DC converter facilitates smooth transitions between modes, responding to grid directives for active and reactive power. A Soft Switching Dual Active Bridge (SS-DAB) DC-DC converter optimally interfaces with the EV battery pack, while dual active LCL filters suppress harmonics, enhancing system performance. Simulated results confirm the charger’s effectiveness in a 3.5kW prototype using MATLAB/Simulink.

A Proportional and Weight Based Decentralized Charge Controller of Electric Vehicles for the Improvement of Local Voltage Profile

A Proportional and Weight Based Decentralized Charge Controller of Electric Vehicles for the Improvement of Local Voltage Profile

Photovoltaics Efficiency on Automatic Fish Feeding Distributors Device Using Internet of Things

Renewable energy is crucial for facilitating the shift towards a more sustainable society. It plays a significant role in establishing a clean energy system, mitigating greenhouse gas emissions, and enhancing the well-being of both current and future generations. The study included field observation and data analysis approaches. The study utilized IoT-based automatic fish feed spreaders, photovoltaic units, batteries, SCC (solar charge controller), Android phones, thermometers, multimeter tester, LCDs, ultrasonic sensors, and a microcontroller circuit. This study aims to acquire power, electrical energy, and efficiency measurements from solar systems employed in an Internet of Things (IoT) enabled automatic fish feeder apparatus. The results show that the power consumption needed to operate the IoT-based automatic fish feeder gadget is 48.75 watts. The peak of solar irradiance was recorded at 12.00 WIT, averaging 900.27 W/m2. The lowest intensity was at 09.00 WIT, averaging 422.78 W/m2. Photovoltaics can produce electrical power at 22.75 watts per hour, leading to a daily electrical energy output of 159.25 Wh. The highest photovoltaics efficiency was 16.37% with 465.3 W/m2 of solar irradiance, 30.7°C of temperature and 2.144 m/s of wind speed. The temperature and wind speed has significantly affected on photovoltaics efficiency.

AI enabled fast charging of lithium-ion batteries of electric vehicles during their life cycle: review, challenges and perspectives

This review presents a thorough investigation of factors affecting fast charging, battery modeling, key state estimation and fast charging control strategies and provides a forward-looking perspective on AI enabled fast charging technology of LIBs.

Developing a Transactive Charging Control Framework for EV Parking Lots Equipped With Battery and Photovoltaic Panels: A MILP Approach

Developing a Transactive Charging Control Framework for EV Parking Lots Equipped With Battery and Photovoltaic Panels: A MILP Approach

Design, Construction and Performance Evaluation of Solar Charge Controller for Street Lighting Application

Solar powered equipment and applications are gradually making their ways into various sector of our day to day life. We need a storage or battery to store the solar energy harnessed during day. A Solar Charge Controller (SCC) which is a part of a solar power system has been designed using Proteus Software, to maintain batteries used in solar power harvesting and utilization in a charged state, without risk of over-charging or over-discharging, ensuring battery durability. The charge controller has battery management system in built, responsible for executing the desired charging algorithm based on the battery chemistry characteristics. After the circuit design and construction, tests like Power Supply test, Accuracy test, charging test and discharging test were conducted. From the results of the tests, the power supply met its requirement to out-put a constant voltage of 5Vfor the microcontroller and LCD circuit. The charging test result shows the charging characteristics of the charge controller. The discharging test result is a negative linear graph showing that the battery is discharging from 14.4 V to about 9.5 V where the microcontroller disconnected the battery from the load. The results showed that the charge controller was able to control and regulate the charging process well. Calculated Mean percentage error was 0.04.

Design and Feasibility Study of a Standalone Photovoltaic System for Electrifying a Healthcare Centre in a Rural Area of Malaysia: A Case Study

le="Abstract"] <p style="text-align: justify;">Malaysia is strategically located at the sunbelt viability, where it receives a large amount of sunshine every day. This makes the solar photovoltaic technology popularly utilized particularly in rural areas that are isolated from the main grid. These areas have the potential to use photovoltaic technology to meet load requirements. Compared to grid connected photovoltaic systems, standalone photovoltaic systems offer several benefits to system owners including low maintenance, low upkeep cost, no waste or by-products, and easy expansion through the use of multiple solar panels and batteries. This article presents a design phase of the Standalone Photovoltaic System (SAPVS) to electrify the healthcare centre in Kampung Tewowoh, Kluang, Johor. The design steps for SAPVS are discussed to obtain the required parameter for each component in the SAPVS. The results indicate that 16 panels, 1219.52Ah/day, 1437.5A and 350 (A) are needed for the PV panels, battery capacity, inverter, and charge controller, respectively. It is proven that SAPVs are technically viable and feasible for electrifying the healthcare centre in the specified area.

Sistem Otomatis Pengendalian Pakan Ikan dengan Sumber Energi Matahari Menggunakan Mikrokontroller Arduino

Humans have made many discoveries in the modern era that make work easier, including advances in technology, healthcare, agriculture, and cultivation. Automated methods and equipment are among thedevelopments that make human work easier. As a result, a device for feeding fish that can functionautomatically according to the feeding plan and time is designed using a servo motor controller for the fishfeeder powered by solar energy and an Arduino microcontroller module as the controller program. Solarpanels are power plants that receive power from sunlight and are equipped with a charge controller. Theinverter acts as a DC to AC voltage converter, while the battery stores and distributes the voltage. Thescheduling system used by this tool is determined by Arduino software that has been programmed in astructured manner. It will operate on a pre-set schedule, which requires it to be used between 8 am and 5pm, and its output capacity of 10 feed container valve openings is set consistently and pre-programmed.During the test, the average power consumption was 142.75 watts during the day and 125.72 watts at night,with a total consumption of 108.93 watts at night.

Vehicle-to-grid bidding for regulation and spinning reserve markets: A robust optimal coordinated charging approach

This paper handles the problem of optimal charging control for electric vehicle (EV) aggregators in energy and ancillary service markets under uncertainties. We propose a robust optimal coordinated charging (OCC) model that formulates a robust linear programming (RLP) for the EV aggregator formed on unidirectional vehicle-to-grid (V2G) and coordinates the provision of regulation and spinning reserves. Our model considers many uncertainties in the electricity markets, like ancillary service prices and the placement signals, as well as accurate parameters associated with EV behavior, like EV availability, time of trips, and trip duration. The objective of the optimization is to maximize the aggregator's income from V2G by contributing to the ancillary services markets. The proposed robust OCC model, a robust linear problem (RLP) model, is simulated using the CPLEX solver in GAMS software. We compare our model with the existing deterministic models and show that our model increases the aggregator's revenues and then reduces the deviation between predicted and realized revenues. We propose a new and effective method for EV aggregators to bid into energy and ancillary service markets under uncertainties. Our model shifts the charging time of EVs from peak to off-peak hours, resulting in an improved final state of charge.

Analysis of Battery Testing Protocols in the Transition from the Lab to the Field: A Test Case Using Advanced Zn-MnO2 Batteries in Off-Grid Solar Microgrids

Understanding cycling performance of batteries under varying conditions is crucial for continued development of emerging chemistries. Currently much of this work is focused on cycling single cells in well-controlled lab experiments. There are few module cycling studies in the open literature. Studies of full-sized fielded systems are even rarer. As a result of this data gap, there is limited understanding of how single cell cycling can be used to predict performance of fielded systems prior to their deployment.Sandia National Laboratories (SNL) recently deployed an advanced Zn-MnO2 secondary battery energy storage system in an off-grid solar plus storage system. Using this deployment as a test case, we will detail how performance and degradation for batteries can vary between the lab and the field. We will also discuss ways that single cell and module lab cycling can be improved to better predict operation in fielded systems.In preparation for this deployment, SNL conducted single cell cycling experiments in the lab to simulate operation in the field and determine the expected life of the systems. The first test program utilized elements of the IEC 61427-1 standard for photovoltaic off-grid application to simulate the temperature and predicted state of charge (SOC) range the cells will be cycled during field operation. The simulated field cycling targeted SOC ranges of 10 to 40% and 80-100% over 150 cycles with temperature varied between -4 and 35oC to match the ambient conditions in the field during each season. The second type of cycling test was a temperature dependence study to determine how temperature impacted cell degradation. Cells were cycled at C/10 at their full SOC range and at a single temperature until they reached 40% capacity retention. Both cycling studies predicted that low temperature operation would increase the rate of degradation.The system was deployed in May of 2022, and since that time the SNL team has collected a significant amount of performance data to help analyze system level behaviors as compared to observations from cell level testing. These include battery interactions with the solar charge controller, limitations on power inverter settings, and variance between the average system level state of charge and the test protocol. Additionally, the team is analyzing conditions found in the field, with regards to ambient temperature, solar insolation and battery charging rates, and customer usage patterns for comparison with cell-level testing protocol.Observations of the deployed system’s performance indicate there is a need for more nuanced testing protocols for lab testing that can better approximate field conditions. These may include dynamic temperature ranges that vary throughout a charge/discharge cycle, and solar charging assumptions that account for reduced insolation due to cloud cover. This can help further inform the development of charge control algorithms, system hardware and software that can help improve the overall performance of solar microgrid energy storage systems.Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2023-02502A

Modeling of a Hybrid Controller for Electric Vehicle Battery Charging Using Photovoltaic Panels

Modeling of a Hybrid Controller for Electric Vehicle Battery Charging Using Photovoltaic Panels