International Journal of Applied Power Engineering (IJAPE)
Not a member yet
508 research outputs found
Sort by
Mitigating mismatch power losses in photovoltaic systems under partial shading: a comparative study of series-parallel and alternative configurations
Get PDFUtilizing the photovoltaic effect, photovoltaic (PV) systems are a popular technique for capturing solar energy and turning sunlight into electricity. However, environmental factors, especially shade, significantly impact photovoltaic system efficiency. Shadows cast on PV panels by surrounding structures, trees, accumulated dirt, clouds, and debris can seriously impair their performance. The purpose of this study was to investigate how shade affects photovoltaic systems utilized in residential settings. Series-parallel (SP) topology for PV system have been investigated. Additionally, in this work, a PV system of 5 kW of the residence home has been proposed and multi cases of shading examined. Through the results obtained when partial shading was applied, it was found that the highest efficiency of the system was when partial shading irradiance (Ir = 500 W/m2) was applied to one column (5 modules) as 82.84%, while the worst and least equipped case was when the shading was applied to the corners and random shading at (8 modules), where the efficiency decreased to approximately 39.24% and 40.64% respectively
Transmission line fault detection using empirical mode decomposition in presence of wind intermittency
Get PDFThe regular fault detection approaches are failed to detect the faults in wind integrated transmission networks due to intermittency nature of the wind energy. More reliable schemes are required to accomplish the detection of faults in presence wind. This article proposed empirical mode decomposition (EMD) based fault detection scheme to detect various faults in wind integrated transmission lines during the normal and stressed conditions of the system. The instantaneous current measurements available at either sending or receiving end are processed through EMD to decompose it into a series of intrinsic mode functions (IMFs) and IMF2 is identified as a dominated IMF with numerous case wise investigations. 1/4th cycle moving window is used to calculate the absolute sum of the IMF2 coefficients to detect the faults with the support of a predefined threshold. The efficacy of the method is tested on different types of faults during the normal condition in presence of wind and later extended to stressed conditions such as power swing. The method is reliable during the typical cases and includes remote end and high resistance faults. All the experiments are carried out in Simulink to generate the measurement data and programs are executed in MATLAB
Power smoothing in electrical distribution system using covariance matrix adaptation evolution strategy of aquila optimization
Get PDFThis study introduces a novel hybrid optimization approach covariance matrix adaptation evolution strategy of aquila optimization (CMAESAO) to enhance power smoothing and minimize power losses in electrical distribution systems through the optimal allocation of D-STATCOMs. The method is tested on standard 33-bus and 69-bus systems. The CMAESAO algorithm efficiently identifies optimal locations and sizes of D-STATCOMs to achieve system performance improvements under constant power (CP), constant current (CC), and constant impedance (CI) load models. The results show that, for the 69-bus system, installing two D-STATCOMs yields optimal performance, reducing real power loss from the base value to 149.6368 kW, while three D-STATCOMs yield a slightly better voltage profile and VSI but only marginal additional power loss reduction (147.8951 kW), making two units more cost-effective. For the 33-bus system, three D-STATCOMs provide the best improvement in power quality and loss minimization. Voltage and current profiles confirmed improvement in voltage stability and reduced branch currents with optimized placements. Compared to other optimization techniques, CMAESAO demonstrates faster convergence and superior accuracy in minimizing losses, establishing its effectiveness for such multi-objective optimization problems. The study's novelty lies in integrating CMA-ES with aquila optimization to combine strong global search with adaptive exploration, resulting in robust and efficient power system enhancement. The proposed methodology contributes to smarter, more reliable distribution systems, supporting grid resilience and energy efficiency
Optimization and management of solar and wind production for standalone microgrid: a Moroccan case study
Get PDFThe increasing demand for sustainable and efficient energy solutions has prompted extensive research into optimizing renewable energy sources in microgrid systems. This paper focuses on optimizing renewable energy sources within a standalone microgrid using particle swarm optimization (PSO) as the sole algorithm. The microgrid model proposed integrates photovoltaic (PV), wind, battery storage, and serves a load represented by an agricultural firm. Real-world data from Agdz in Ouarzazate, Morocco, is utilized for analysis. The primary objective is to minimize excess production from PV and wind sources when the battery reaches full charge. This research addresses the increasing demand for sustainable energy solutions by emphasizing a single optimization technique, PSO, for achieving a balanced and efficient energy generation system. The study aims to closely align energy production with load demand to reduce wastage and ensure a reliable energy supply within the microgrid. The evaluation is conducted based on the ability of the PSO algorithm to diminish the gap between total energy production and load demand. The use of the PSO algorithm resulted in a 30% reduction in excess energy, effectively mitigating unnecessary energy wastage when the battery is fully charged. This outcome highlights the algorithm's capacity to adapt and optimize energy production from primary sources to precisely align with the specific requirements of the loa
Hysteresis current control for single-phase transformerless inverter
Get PDFThe total harmonic distortion (THD) of grid current and leakage current are significant for transformerless inverters, as they impact power quality, efficiency, and compliance with grid codes. Monitoring and minimizing these currents ensure safe and reliable grid integration of photovoltaic (PV) systems while reducing electromagnetic interference. Therefore, in this paper, the analysis THD of grid current and leakage current is described. The bipolar pulse width modulation (BPWM) technology provides a stable common-mode voltage (200 V), fewer leakage currents (< 30 mA), and better system efficiency, compared to the unipolar pulse width modulation (UPWM) technique. To ensure the inverter complies with the IEC 61000-3-2 class C (THDi < 5%), the current control strategy should be considered during the design of the transformerless inverter. Therefore, this paper presents an implementation and evaluation of the bipolar hysteresis current control (BHCC) technique. In comparison to the BPWM technique, the BHCC technique delivers lower leakage current (0.007274 A), reduced grid current harmonic distortion (1.81%), and increased efficiency
Optimizing microgrid designs towards net-zero emissions for smart cities: addressing energy disparities and access issues in Northern and North-eastern India
Get PDFProviding affordable and clean energy is a significant sub-sector of the Smart Cities Mission proposed by India. This research investigates the development of optimal microgrid designs for smart cities in northern and north-eastern India to address regional energy disparities and access issues. In the northern zone, characterized by uneven urban-rural infrastructure and high-power demand, microgrids offer localized, reliable solutions that reduce dependency on centralized systems and enhance energy efficiency. In the north-eastern zone, where geographical isolation and underdeveloped infrastructure hinder energy access, microgrids provide decentralized power generation and distribution, improving access in remote areas. The proposed microgrid designs aim to enhance energy reliability, efficiency, and accessibility by integrating renewable energy sources. The proposed system is analyzed for technical and economic feasibility based on critical factors such as cost of energy (COE), loss of power supply probability (LPSP), and the renewable fraction (RF). The renowned particle swarm optimization (PSO) algorithm is used to optimize the system size to achieve better performance in terms of technical and economic aspects. A proper energy management technique ensures the energy balance between the demand side and the distributed energy sources. A typical 24-hour household load profile is used for the optimization
Analysis of the soft switching modes for energy loss measurement of high frequency closed-loop boost converter
Get PDFThis manuscript explains the analysis of the soft switching technology to measure the energy loss of high-frequency closed loop boost converter with zero-current switching (ZCS) and zero-voltage switching (ZVS) techniques. To get these attributes, the use of soft power converters that utilize soft switching techniques is essential. This paper examines the ZCS/ZVS AC/DC converter design, used in high-power systems for renewable energy and battery charging. This converter architecture ensures semiconductor switches turn on and off at zero voltage and current. It smooths rectifier diodes, reducing switching and reverse recovery losses. It has better power quality, efficiency, and input power factor. Practical study has been done to verify the converter's theoretical analysis. Empirical research shows gentle switching enhances system efficiency. Energy losses are reduced by 26% while turning on and 20% when turning off compared to the ZVS and ZCS. The prototype converter is built to corroborate simulation results. Compared to ZVS and ZCS, switching losses are lower and efficiency decline is modest across the operating range. This shows that the simulation and experimental results are consistent
Grid connected solar water pumping system
Get PDFA grid-connected solar water pumping system (SWPS) uses solar power to pump water while simultaneously drawing power from the grid when necessary. These systems can benefit farmers in a variety of ways, including reliable power, lower electric bills, increased income, and improved economic viability. This study explores a solar photovoltaic (SPV) water pumping system designed to function with a single-phase distribution network. It utilizes an induction motor drive (IMD) and incorporates an advanced power-sharing technique for optimal performance. In addition to transferring power from SPV to IMD, a DC-DC boost converter functions as a grid interface and power factor adjustment device. Maximizing the power extracted from the SPV array is critical for optimizing its utilization. To do this, a control mechanism based on incremental conductance is implemented to track maximum power points. Simultaneously, the IMD connected to the power source inverter is regulated using a simple volt/frequency approach. The suggested system, which includes standalone, grid-interfaced, and mixed-mode situations, is developed and validated in a lab
Comparative analysis of MPPT techniques for photovoltaic systems: classical, fuzzy logic, and sliding mode approaches
Get PDFThis study presents a comprehensive comparative analysis of maximum power point tracking (MPPT) strategies for photovoltaic systems, focusing on the classical perturb and observe (P&O) method, an artificial intelligence based fuzzy logic controller (FLC), and a robust sliding mode control (SMC) technique. These methods aim to maximize power output by dynamically adapting to rapid and unpredictable environmental variations, such as changes in solar irradiance. Simulations performed the MATLAB/Simulink environment under diverse real-world scenarios demonstrate that SMC and FLC outperform the conventional P&O approach, particularly under conditions of sudden and severe environmental in fluctuations. The findings highlight the advanced controllers’ ability to sustain optimal power extraction, minimize energy losses, and maintain system stability across varying operating conditions. These results underscore the potential of SMC-based MPPT systems to enhance the efficiency and resilience of renewable energy applications, making them highly viable for deployment in real-world scenarios characterized by volatile environmental conditions
AI-driven solutions for Li-ion battery performance and prediction
Get PDFBatteries serve as crucial power sources for essential portable devices like electric vehicles, smartphones, and laptops. The widespread adoption of Li-ion batteries, while beneficial, has unfortunately led to a surge in adverse incidents. The sudden failure of batteries in both industrial and lightweight applications poses significant economic risks across various industries. Consequently, researchers are intensifying their focus on enhancing battery state estimation, management systems, and predicting remaining useful life (RUL). This paper is structured into three main sections. Firstly, it delves into the acquisition of battery data, encompassing both commercially available and freely accessible Li-ion battery datasets. Secondly, the exploration extends to techniques for estimating battery states through advanced battery management systems. The paper investigates battery RUL estimation, categorizing and evaluating diverse prognostic methods applied to Li-ion batteries based on crucial performance parameters. The review includes scrutiny of commercially and publicly available datasets for various battery models and conditions, considering different battery states and the role of advanced battery management system (BMS). In the final section, the paper concludes with a comparative analysis of Li-ion battery RUL prediction, incorporating exploration into various RUL prediction algorithms, and mathematical models, and introducing an AI-based cloud monitoring system