Authors:Elipilli Anil Kumar, Gopichand Naik Mudavath, Tamminana Narasimhulu Pages: 521 - 529 Abstract: The bat algorithm (BA) has emerged as a promising meta-heuristic approach, demonstrating its efficiency in tackling diverse optimization problems across the areas such as engineering design, issues with economic load dispatch, power and energy systems, image processing, and medicinal applications. Due to its potential to increase grid resilience, decrease greenhouse gas emissions, and increase energy efficiency, the incorporation of distributed generation (DG) into contemporary power systems has drawn a lot of interest. This paper presents technique for the optimal allocation of DG units, aiming to address existing challenges and improve the overall performance of the power system. The proposed BA technique combines advanced optimization algorithms with comprehensive power system modelling to identify the optimal locations and capacities for DG installation. Key factors are taken into account to formulate a multi-objective optimization problem that includes minimizing power losses, enhancing voltage stability, and minimizing the environmental impact while considering economic feasibility. The algorithm is applied on standard IEEE 33 and 69 bus systems as test cases and a result has been discussed. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp521-529 Issue No:Vol. 13, No. 3 (2024)
Authors:Surender Singh Tanwar, Ganesh Prasad Prajapat, Ravindra Rathod, Sanjay Kumar Bansal, Sukhlal Sisodia Pages: 530 - 538 Abstract: This manuscript considers multi-criteria based multi-objective approach with technical, economic and environmental indices (TEE) for optimal placement and sizing of distributed generation (DG) units in the distribution network. Technical criteria include indices of active energy losses, voltage deviation; whereas economic criteria include the index of cost of DG installation, and environmental index considers the various greenhouse gas (GHG) emissions from generating unit’s and biomass DG. Combined sensitivity analysis is applied for sorting the candidate nodes for DG placement and reducing the search space. Multi-criteria decision-making among TEE factors are addressed using a scientific approach named Analytic Hierarchy process (AHP) approach. The impact of prioritized solutions is analyzed in terms of three scenarios formed using AHP in the form of TEE criterion. The developed formulation is tested on IEEE 33-bus bus radial distribution system and is solved using hybrid optimization approach (hybrid GA-PSO) and AHP based scenarios performed better than base case scenario (non-prioritized scenario). PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp530-538 Issue No:Vol. 13, No. 3 (2024)
Authors:Achala Khandelwal, Namra Joshi Pages: 539 - 545 Abstract: Incorporating photovoltaic (PV) systems to grids have developed into an obvious alternative for many countries, those results in harmonics issues for the utility operators. Harmonics arises due to extensive utilization of power-electronic components during incorporation of PV to grid. Harmonic deformation has traditionally been taken care of by the relevance of passive filter. Active filters have come up as an alternative choice over passive ones for reduction of harmonic due to existence of several advantages in comparison to previous filter. The application of controllers is the most significant aspect of using an active filter. Various investigations are beneath development to progress performance of the filters. Control of capacitor voltage is among the major regulation requirement for the filter. Here, regulation of voltage is carried on by fuzzy-controller. The article represents compensation of harmonic currents of a grid integrated PV-system by application of fuzzy-controller placed active filter. One of the important control requirements of filter is the regulation of DC link up capacitor voltage. Here the voltage supervision of capacitor is being done using PI controller. The paper shows current harmonics compensation of PV grid connected system using PI controller based active filter. Simulating results are revealed that shows the harmonics are contained inside IEEE limits. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp539-545 Issue No:Vol. 13, No. 3 (2024)
Authors:Jayanta Kumar Sahu, Babita Panda, Sudhakar Sahu Pages: 546 - 553 Abstract: The low operating and maintenance expenses of photovoltaic (PV) power generation make it a popular choice for rural power generation systems. Solar radiation, temperature, and load impedance are the major factors influencing the final output of solar PV. Consequently, the solar PV system experiences oscillations in its operation. These oscillations in the operating point pose a difficulty in transferring maximum power from the source to the load in an efficient way. A method called as “maximum power point tracking” is used to address this problem. This technique eliminates oscillations ensure that stability of operating point at the maximum power point. PV has several maximum power points (MPP) under partial shade situations, which is characterized by its non-linear features. As a result, it is challenging to find actual MPP. While tracking and collecting the maximum power from PV, the cuckoo search optimization (CSO) technique developed by biological intelligence is used in this article. The cuckoo search (CS) has several advantages, including a short tuning process that is efficient as well as fast convergence. The step-up converter steps up the voltage. In order to steady the converter, the counter variable is employed to provide delay. Resistive load is present. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp546-553 Issue No:Vol. 13, No. 3 (2024)
Authors:A. Clement Raj, Ramaiyan Bensraj Pages: 554 - 570 Abstract: This study presents a novel topology for a high-gain Cuk converter without isolation, leveraging switched-inductor (SL) and switched-capacitor (SC) networks tailored for renewable energy sources. Unlike traditional Cuk converters that perform negative-to-positive boost DC-DC voltage conversion, this innovative design offers a significantly enhanced voltage-boosting capacity. They evolve from the conventional Cuk converter by integrating an SL instead of the singular inductor and substituting the energy-transferring capacitor with an SC. The standout benefits of the modified Cuk converters include a remarkable voltage conversion ratio and minimized voltage stress on the primary switch, allowing a low-voltage-rated switch for greater efficiency. Comparatively, the proposed designs surpass the classical Cuk and a few modified Cuk converters in voltage gain and reduced switch voltage stress. The converter also avoids the need for transformers or coupled inductors, resulting in minimized volume, loss, and expense. The converters' operation in continuous conduction mode is rigorously analyzed in this study. After deriving all the relevant equations, they are validated against outcomes. The proposed Cuk converter topology was simulated using the MATLAB/Simulink tool, and the findings are deliberated. The performance of the proposed converter is compared with the other converters, and the proposed converter's superiority is proved through the obtained results. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp554-570 Issue No:Vol. 13, No. 3 (2024)
Authors:Sivaprasad Kollati, Satish Kumar Gudey Pages: 571 - 582 Abstract: For use in solar-assisted hybrid electric vehicle applications, a multiport bidirectional switched reluctance motor (SRM) drive is suggested in this research. Since the photovoltaic (PV) system's output voltage is low and insufficient to reach the necessary voltage level, a high gain KY converter is used to increase the PV output. The 8/6 SRM receives the steady converter output via the (n+1) diode (n+1) converter architecture with the help of the proportional integral (PI) controller. A PI controller regulates the SRM's speed. A bidirectional battery converter connects the battery, which is attached to the DC bus, to the extra power from the PV. A PI controller manages the bidirectional battery converter's operations. When necessary, the battery transfers the excess energy from the PV to the SRM drive. The outcomes demonstrate that, when examined using MATLAB simulation, the recommended methodology functions well. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp571-582 Issue No:Vol. 13, No. 3 (2024)
Authors:Khairul Eahsun Fahim, Md. Rakibul Islam, Nahid Ahmed Shihab, Maria Rahman Olvi, Khondaker Labib Al Jonayed, Adri Shankar Das Pages: 583 - 593 Abstract: A smart grid is a cutting-edge energy system designed to take over old-fashioned energy infrastructure in the twenty-first century. With comprehensive communication and computation capabilities, its primary objective is to increase energy distribution's dependability and efficiency while minimizing unfavorable effects. A number of approaches are needed for effective analysis and well-informed decision-making due to the massive infrastructure and integrated network of communications of the smart grid. In this study, we examine the architectural elements of the smart grid as well as the uses and methods using machine learning (ML) and deep learning (DL) with regard to the smart grid. We also clarify present research limitations and propose future directions for machine learning-driven data analytics. In order to improve the stability, reliability, security, efficiency, and responsiveness of the smart grid, this paper examines the implementation of several machine learning methodologies. This paper also covers some of the difficulties in putting machine learning solutions for smart grids into practice. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp583-593 Issue No:Vol. 13, No. 3 (2024)
Authors:Zakaria M'barki, Ali Ait Salih, Youssef Mejdoub, Kaoutar Senhaji Rhazi Pages: 594 - 602 Abstract: Pseudo-random position pulse modulation (RPPM) technique can be implemented either analogically using pseudo-random binary sequences (PRBS) to generate a pulse-width modulation (PWM) control signal or digitally through an Arduino Uno board. It plays a critical role in mitigating conducted electromagnetic emissions (EMI) in boost converters dedicated to electric vehicle systems (EVS) applications. The digital implementation offers a significant advantage by enabling a substantial widening of the frequency spectrum of the control signal. This expanded spectral range results in a noticeable reduction in emitted electromagnetic interference (EMI), making the digital method the preferred choice. The increased spectral bandwidth effectively mitigates EMI, which is particularly advantageous for EMI-sensitive EVS systems. In conclusion, the digital pseudo-random modulation approach, facilitated by Arduino Uno, proves to be more effective in reducing EMI in EVS boost converters. Its capability to broaden the control signal's frequency spectrum leads to a favorable reduction in emitted EMI, ultimately enhancing electromagnetic compatibility and overall system performance.
Authors:P. Annapandi, D. Lakshmi, B. Kavya Santhoshi, P. Annapoorani Pages: 603 - 615 Abstract: The wide deployment of grid-connected renewable energy system has piqued immense attention recently, in response to rising electricity consumption, diminishing fossil fuel reserves in addition to the need for reducing carbon emissions. Among the available sources of renewable energy, photovoltaic (PV) power generation is the most promising technology with enormous potential and easy access. This paper presents an optimum control technique for grid connected PV systems. The improved single ended primary inductor converter (SEPIC) controls and regulates PV output power to the optimum voltage level. The working of the improved SEPIC is controlled by a proportional-integral (PI) controller optimized by meta-heuristic technique of lion swarm optimization (LSO). The constant output from the converter is then supplied to the power grid through a single-phase voltage source inverter (1𜙠VSI). The effectiveness of the proposed control strategy is ascertained using hardware validation with DSPIC3050FPGA controller and MATLAB simulation generating a reduced total harmonic distortion (THD) of 3.9% and 2.9%, respectively. Furthermore, the proposed system generates an enhanced voltage gain of 1:10 and an efficiency of 96%. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp603-615 Issue No:Vol. 13, No. 3 (2024)
Authors:K. S. Kavin, P. Subha Karuvelam, Naresh Kumar, Siddheswar Kar, Riyaz A. Rahiman, Sharda Patwa Pages: 616 - 627 Abstract: An efficient machine learning approach for accomplishing the maximum power point tracking (MPPT) system for photovoltaic (PV) systems is proposed in this work. PV system is one of the most suitable renewable energy sources (RES) for electric vehicles (EV) based operations due to its ubiquitous availability and speed of installation. The deployment of PV-powered EVs reduces the quantity of carbon dioxide emitted into the atmosphere substantially. The primary objective of this research is to integrate a PV system with an EV load and to provide a constant power supply to the EV load with no distortions. A coupled inductor interleaved boost converter is used to raise voltage level of the PV because it has a wide conversions range with low leakage reaction times. Furthermore, the converter produces a consistent output with no fluctuations and high voltage gain. With the application of artificial neural network (ANN) based MPPT and recurrent neural network (RNN) based MPPT, the converter operational performance enhanced with steady dc link voltage is obtained. Consequently, it is stated that the employment of ANN and RNN-based MPPT controllers in PV-based systems offers improved DC link voltage regulation and lower power losses, thereby boosting system effectiveness. The MATLAB platform is used to test every component of the system's performance, and the findings show that the proposed system is more efficient than alternative approaches. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp616-627 Issue No:Vol. 13, No. 3 (2024)
Authors:Munther Mohamed-Abdulhussein, Rosmiwati Mohd-Mokhtar Pages: 628 - 636 Abstract: In this paper, a model was designed to estimate the amount of solar energy based on solar radiation angles. The model was applied to five Iraqi cities (Baghdad, Basrah, Nineveh, Dyala, and Anbar). The amount of solar energy reaching the globe's surface is analyzed through its application. Data from NASA was relied upon for implementation and comparison. The main objective of the research is to find a reliable and low-cost method by which to know the amount of solar energy in the study area to promote sustainable energy. The results were compared with the data available from NASA, and a satisfactory agreement was found based on some statistical processes that prove the validity of the proposed model. Through the results, it is possible to rely on the proposed model to predict the amount of solar energy reaching the study area and to implement solar energy projects. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp628-636 Issue No:Vol. 13, No. 3 (2024)
Authors:Josiah Teyah Maroko, David K. Murage, Peterson Kinyua Hinga Pages: 637 - 644 Abstract: The primary goal of any power microgrid is to provide consumers with reliable power. This becomes a challenge with the continued growth of population which necessitates a corresponding rise in power supply. However, this continued rise in power consumption with a limited power supply can result in voltage collapse and ultimately power outage. In times of severe disturbances in an islanded microgrid (IMG), load-shedding (LS) helps to avert the occurrence of a blackout. The IMG is usually supplied by distributed generations (DGs) which have low inertia or inertia less. Thus, when in islanded mode power imbalance is usually solved by performing optimal LS to prevent the system from plunging into a total blackout. This paper presents a hybrid method which is a combination of fuzzy and linear programming algorithm for optimal LS in IMG. The developed method is centered on power generation, load demand and power prioritization. The fuzzy linear programming (FLP) algorithm is tested on the IEEE 14 bus system. The simulation results show that the proposed algorithm is effective in shedding optimal loads to ensure equilibrium is restored and frequency is within set values of 50 Hz. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp637-644 Issue No:Vol. 13, No. 3 (2024)
Authors:G. Hari Krishnan, B. V. Sai Thrinath, M. Ramprasad Reddy, Thukkaram Sudhakar Pages: 645 - 652 Abstract: As the world embraces sustainable energy solutions, the accurate prediction of AC power generation in solar power plants becomes imperative for efficient energy management. This research endeavors to address this critical need through a meticulous exploration of five distinctive predictive algorithms: linear regression, gradient boosting, neural networks, support vector regression (SVR), and ensemble techniques. Leveraging a merged dataset comprising environmental parameters like ambient and module temperatures, irradiation, and historical yield, our study embarks on a comprehensive evaluation journey. The essence of this endeavor lies in the recognition that renewable energy sources, particularly solar power, are instrumental in mitigating environmental concerns associated with traditional energy generation. To unleash the full potential of solar power, a nuanced understanding of predictive methodologies is indispensable. Linear regression serves as a cornerstone, validating its foundational role. However, the crux of innovation lies in the advanced algorithms – gradient boosting, neural networks, SVR, and ensemble methods – each striving to optimize prediction accuracy. A novelty of this research stems from its holistic approach to predictive modelling. By meticulously comparing the performance of multiple algorithms, we uncover insights that transcend mere theoretical applications. Our findings assume significance in the context of renewable energy's societal impact. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp645-652 Issue No:Vol. 13, No. 3 (2024)
Authors:Debani Prasad Mishra, Somya Siddharth Padhy, Partha Sarathi Pradhan, Shubh Gupta, Asutosh Senapati, Surender Reddy Salkuti Pages: 653 - 660 Abstract: Electric vehicle (EV) performance is greatly influenced by the motor drive system's stability, efficiency, and safety. With the increased usage of electric vehicles, fault detection and diagnostics (FDD) of the motor drive system has become an important topic of research. In recent years, there has been a lot of interest in artificial intelligence (AI) approaches employed in FDD. This paper provides an overview of the application of AI in defect detection for electric vehicles. The FDD method is divided into two steps: feature extraction and fault classification. Feature extraction involves identifying relevant parameters or characteristics from the EV's sensors and signals, enabling the AI system to capture meaningful patterns. Subsequently, fault classification employs AI algorithms to categorize and identify specific faults based on the extracted features, facilitating efficient diagnosis and maintenance of EVs. In the realm of EVs, the combination of AI techniques and FDD has the potential to improve performance, reliability, and safety while enabling proactive maintenance and reducing downtime. Using machine learning and deep learning, we can detect the fault in the system before it starts damaging our EV. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp653-660 Issue No:Vol. 13, No. 3 (2024)
Authors:Thangavel Jothi, Manoharan Arun, Murugesan Varadarajan Pages: 661 - 669 Abstract: Hybrid smart grids which depend on renewable energy have substantial challenges to their reliability and efficiency due to power quality issues. However, the performance and dependability of the system might be impacted by power quality concerns caused by the intermittent nature of renewable energy sources and the presence of nonlinear and unbalanced loads. This study suggests that a hybrid renewable energy-based smart grid can improve power quality by using a dynamic voltage restorer (DVR), a flexible alternating current transmission system device. The goal is to improve voltage stability, reduce voltage spikes and harmonic distortion, and provide a clean power supply. This study's primary contributions are the design and execution of the cascaded H-bridge DVR topology, the development of a modified synchronous reference frame-based controller and a thorough examination of the performance of the integrated DVR system. Total harmonic distortion and voltage regulation are two power quality metrics used to evaluate the effectiveness of the suggested technique in MATLAB simulations. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp661-669 Issue No:Vol. 13, No. 3 (2024)
Authors:Leonardus Heru Pratomo, Sushil Paudel, Bagus Kusuma Cahyadi Pages: 670 - 678 Abstract: Over the past decade, much research and development has gone into the use of electric power converters, and the trend is upward. Inverters are employed when converting DC voltage to AC voltage. Typically, inverters perform functions such as voltage boost (to compensate for voltage decrease) or both voltage buck and boost. Other issues to consider include the structure of the inverter topology and the control method. Based on the problem, a study was conducted on a buck-boost inverter that integrates an H-bridge inverter and a single ended primary inductor converter (SEPIC). The H-bridge inverter is widely recognized for its simplicity of operation and always runs in buck mode. The SEPIC converter always runs in buck-boost mode. Since it is unipolar, it can operate as a buck or boost when combined with SEPIC AC-AC. The output voltage is significantly improved because it has several filters to enhance the signal. This hybrid topology is controlled by sinusoidal pulse width modulation, resulting in a straightforward control technique with outstanding performance. The H-bridge inverter operates in index modulation 0-100%, and the SEPIC converter more than 50%. In the lab, a computational and implementation procedure is used to test the effectiveness of the hybrid topology and control method under consideration. The test results show that the hybrid architecture can function within the desired parameters. The proposed inverter has 4.531% THD_V, 4.531% THD_I, and 97.85% efficiency under simulation. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp670-678 Issue No:Vol. 13, No. 3 (2024)
Authors:Mugachintala Dilip Kumar, D. Himabindu, Yarrem Narasimhulu Vijaya Kumar, Thota Mohana, Ramagiri Shashank, Bodapati Venkata Rajanna Pages: 679 - 686 Abstract: Accessing the unelectrified rural population is currently not possible through grid expansion, as connectivity is neither economically viable nor encouraged by large companies. Additionally, conventional energy options, such as broom-based systems, are being gradually phased out of rural development programs because to growing oil prices and the unbearable effects of this energy source on consumers and the environment. A hybrid generator using solar and wind can solve this issue. Proven hybrid systems are the best choice for delivering high-quality power. Nowadays, hybrid renewable energy systems are becoming popular. The power system provides electricity to remote and isolated areas. Villages and residents in the forest area had their electricity cut off due to the forest environment. While creating a renewable energy source near the load. Solar power and wind power are renewable sources, solar power works in the morning and wind can make morning and night time to synchronize both output voltage and frequency to provide provides the ability to charge continuously, without interruption. The main objective of the project is to provide mixed renewable energy without interruption. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp679-686 Issue No:Vol. 13, No. 3 (2024)
Authors:Tole Sutikno Pages: 687 - 694 Abstract: Smart charging is a technology that allows electric vehicles (EVs) to communicate with charging devices. This paper presents an overview of smart EV charging. Smart charging is a future solution for businesses, allowing them to remotely monitor EV charging events, manage charging stations, and concentrate on their core operations. It also simplifies payments, regulates electricity consumption, and makes charging stations easy to manage. Smart charging solutions assist utility companies in developing their own EV charging networks by stabilizing the grid, adapting to changing demands, and easily managing multiple charging stations. Furthermore, the visibility of all actions at charging stations facilitates keeping track of business activities. Smart charging is a critical component of electric vehicles (EVs) because it provides future-proof features such as cloud connectivity, standardized socket types, and backend compatibility. Smart EV charging includes an admin panel for managing multiple charging points, automatic payments and billing, end-user mobile and web apps, charging station roaming, dynamic load management (DLM), and energy management. These features enable charging stations to better manage their resources, attract more users, and protect the local grid against peak loads. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp687-694 Issue No:Vol. 13, No. 3 (2024)
Authors:Khammampati R. Sreejyothi, Kalagotla Chenchireddy, Abbagoni Srujana, Dharavath Nagaraju, Golluri Ramcharan, Dhunnapothula Raghu Pages: 695 - 702 Abstract: This paper presents a stepper motor drive using the hybrid two-phase model. The stepper motor changes the pulse signals into angular displacement with some angles. Stepper motors are used to control the speed and are also more reliable for smooth operations. The stepper motor provides constant holding torque with controlled speed ranges from 0 to 6000 range. The closed-loop control technique with park transformation is used to control the speed torque variables in a design range. The simulation and hardware results were discussed in MATLAB\Simulink software. The verified simulation results are motor source voltage, motor source current, motor speed, and torque. The hardware results are also implemented in this paper, the implemented circuit by using Arduino microcontroller. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp695-702 Issue No:Vol. 13, No. 3 (2024)
Authors:Abhilash T. Vijayan, Jothish V. Dev, Healsa Henry Pages: 703 - 714 Abstract: The demand for electric vehicles (EVs) is rising due to the environmental impact of zero emission, high efficiency, and a deterioration in the levels of conventional fuels. Initial expense, the range, the time for charging and the availability of charging stations narrows their popularity. Alternately, smart approaches like vehicle-to-home (V2H), vehicle-to-vehicle (V2V), and vehicle-to-grid (V2G) charging schemes can modify this situation and shape the grid-side load curves. Vehicles in need can utilize V2V, where the transfer of charge between electric vehicles ensures the transit up to the nearby charging stations. There are wired and wireless modes in V2V topology. When equipped with the required switchgear, wireless power transfer (WPT) between electric vehicles offers great possibilities in charge sharing. A wireless charging system gives EV owner’s freedom of easy charging without waiting in a queue. This paper compares the performance and utilities of wired scheme and wireless scheme for power transfer between vehicles. Both the strategies check the state of charge (SoC) of the batteries and facilitate the power transfer. Simulations in MATLAB/Simulink and experimental results validate the proposed schemes. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp703-714 Issue No:Vol. 13, No. 3 (2024)
Authors:Gokulananda Sahu, Rakhee Panigrahi, Rajesh Kumar Patjoshi, Venkata Ratnam Kolluru Pages: 715 - 726 Abstract: This paper represents a least mean square (LMS) built Adaline current estimator in conjunction with model predictive control (MPC) approach (Adaline-MPC) employed for distribution-static-compensator (DSTATCOM) to enrich power quality within power distribution network. The real fundamental frequency components of load currents are estimated via LMS-built Adaline adopting instantaneous weight computation and reference currents are further formed by means of multiplying these weights with unit vector templates. A proportional-integral (PI) controller is engaged in support of continual maintenance of DC-capacitor voltage. Moreover, the switching signals of voltage source converter (VSC) are created via applying MPC wherein source currents should track the reference currents, which is derived from Adaline current estimator. Both MATLAB based simulation and Opal-RT based real-time experimental outcomes are demonstrated and the effectiveness of the proposed Adaline-MPC based DSTATCOM towards power quality improvement has been verified. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp715-726 Issue No:Vol. 13, No. 3 (2024)
Authors:Chava Sunil Kumar, Sujatha Banka, Shaik Chandini, Jakkoju Vaishnavi, Gorla Himabindu, Gudibandi Meghana Pages: 727 - 736 Abstract: The focus of the work is on optimizing the wind power system to generate high-quality power from renewable energy sources. This article describes how to control a stand-alone PMSG wind turbine system using perturb and observe (P&O) maximum power point tracking (MPPT) controller. This aids in the regulation of output voltage levels and the maximum power provided to the load. The present study employs P&O MPPT control algorithm to optimize energy extraction from the wind resource, while simultaneously ensuring a stable voltage throughout the load. The goal of MPPT approaches is to establish a reference speed so that the wind energy conversion system (WECS) control system can follow the MPPT trajectory. The MPPT controllers can keep the system running smoothly irrespective of the wind speed fluctuations. There is a significant power output improvement over conventional controllers when using the proposed MPPT controller, according to the comparison results. The DC-DC boost converter was implemented for enhancing the low AC voltage given by the permanent magnet synchronous generator (PMSG). PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp727-736 Issue No:Vol. 13, No. 3 (2024)
Authors:Boaz Wadawa, Joseph Yves Effa Pages: 737 - 754 Abstract: This work offers two significant contributions. The first concerns the proposal of a new formula for evaluating solar radiation on a horizontal plane in the sense of Joseph Fourrier's thermal equation. From which we deduce the characterization of solar radiation under overcast and almost overcast conditions. The second approach is dedicated to the calculation of solar irradiation captured on a fixed inclined surface. This consists of adding the expression of solar radiation coming from the horizontal plane with the overall balance of losses along the path of solar radiation. It appears that, contrary to the results of the models resulting from the Angstrom Prescott formula, the coefficients R= 0.9972, R2= 0.9952, and MAPE= 0.061 for the Garoua data and R= 0.8849, R2= 0.9407, and MAPE= 0.05, for the El Jadida data show that the results of the first proposed formula are well correlated with the measured values. Furthermore, using the optimal tilt angles, the second formula we proposed presents well-correlated results, such that: R= 0.9997, R2= 0.9978, and MAE= 4.1470 for Garoua data and R= 0.9994, R2= 0.9959, and MAE= 7.7742 for El Jadida data. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp737-754 Issue No:Vol. 13, No. 3 (2024)
Authors:Kamal Anoune, Anas El Maliki, Merouan Belkasmi Pages: 755 - 767 Abstract: This paper delves into the critical aspect of managing energy consumption in drone operations to achieve the utmost range and ensure accurate state of charge (SoC) estimation. Effective energy management is pivotal in determining the operational range of drones, allowing for longer distances and heavier payloads. The integration of precise energy estimation algorithms into operational planning extends the range of drones, facilitating swift, environmentally-conscious missions for sustainable and efficient logistics solutions. The paper introduces a mathematical model to understand energy consumption and battery behavior in drones, utilizing the hybrid pulse power characterization test and recursive least square with forgetting factor for parameter identification. To overcome the limitations of linear filters, the paper employs the accurate extended Kalman filter (EKF) in the nonlinear filter section. The EKF significantly enhances the battery management system by furnishing precise SoC data. The study evaluates two SoC estimation techniques: SoC-AH (ampere-hours) and SoC_EKF, using root mean square error for comparison. The SoC_EKF technique demonstrates higher accuracy, boasting a lower errors value of 0.78%, thus making it superior for precise drone battery SoC estimation. These findings contribute to the improved performance, reliability, and overall safety of drones. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp755-767 Issue No:Vol. 13, No. 3 (2024)
Authors:S. Prakash, K. Boopathy Pages: 768 - 782 Abstract: The rapid adoption of electric vehicle (EV) motors has recently raised numerous issues including high expensive, complex maintenance, and resonance problems. Some of the most effective and most thoroughly investigated EV motors are 3ф induction motors and DC motors. Brushless DC (BLDC) motors for EVs are a more advanced version of the solution used in developing nations. Rising time, steady state, transient, overshoot, settling time and other characteristics of the EV based BLDC motor are difficult to control. A loss of control leads to system instability and reduces the components' lifespan. Thereby, in this work, a grid incorporated PV fed EV based BLDC motor is proposed using DC-DC converter along with hybrid optimized PI controller. An innovative high gain Luo converter has been developed with the goal to deal with the fluctuating behavior of PV systems and it provides the impressive advantages of a high conversion range, reduced voltage stress and outstanding efficiency. To considerably improve the performance of the suggested converter, the reliable hybrid particle swarm-spotted hyena optimized (PS-SHO) proportional integral (PI) controller is invented for controlling the BLDC motor's speed. The grid supplies electricity to the BLDC motor when the PV-based power source isn't accessible. The simulation used to determine the efficacy of the proposed BLDC motor system in MATLAB has confirmed that the methodology provides increased efficacy with a highest efficiency of 97.3% and a lower total harmonic distortion (THD) of 2.02%. PubDate: 2024-09-01 DOI: 10.11591/ijape.v13.i3.pp768-782 Issue No:Vol. 13, No. 3 (2024)
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