cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
International Journal of Applied Power Engineering (IJAPE)
Published by Institute of Advanced Engineering and Science
ISSN : 22528792     EISSN : 27222624     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
International Journal of Applied Power Engineering (IJAPE) focuses on the applied works in the areas of power generation, transmission and distribution, sustainable energy, applications of power control in large power systems, etc. The main objective of IJAPE is to bring out the latest practices in research in the above mentioned areas for efficient and cost effective operations of power systems. The journal covers, but not limited to, the following scope: electric power generation, transmission and distribution, energy conversion, electrical machinery, sustainable energy, insulation, solar energy, high-power semiconductors, power quality, power economic, FACTS, renewable energy, electromagnetic compatibility, electrical engineering materials, high voltage insulation technologies, high voltage apparatuses, lightning, protection system, power system analysis, SCADA, and electrical measurements.
Arjuna Subject : -
Articles 25 Documents
 1   2   3 
Search results for , issue "Vol 13, No 3: September 2024" : 25 Documents clear
Study of cuckoo search MPPT algorithm for standalone photovoltaic system Sahu, Jayanta Kumar; Panda, Babita; Sahu, Sudhakar
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i3.pp546-553

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.
An overview of the future smart charging infrastructure for electric vehicles Sutikno, Tole
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i3.pp687-694

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.
Lion swarm optimization for grid connected PV system with improved SEPIC Annapandi, P.; Lakshmi, D.; Santhoshi, B. Kavya; Annapoorani, P.
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i3.pp603-615

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%.
New formulas generalized to the evaluations of solar irradiations captured on horizontal surfaces and optimal inclinations Wadawa, Boaz; Effa, Joseph Yves
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i3.pp737-754

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.
Fault detection and diagnosis of electric vehicles using artificial intelligence Mishra, Debani Prasad; Padhy, Somya Siddharth; Pradhan, Partha Sarathi; Gupta, Shubh; Senapati, Asutosh; Salkuti, Surender Reddy
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i3.pp653-660

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.

Page 3 of 3 | Total Record : 25

 1   2   3 

Filter by Year

2024 2024


Reset
Filter By Issues
All Issue Vol 14, No 4: December 2025 Vol 14, No 3: September 2025 Vol 14, No 2: June 2025 Vol 14, No 1: March 2025 Vol 13, No 4: December 2024 Vol 13, No 3: September 2024 Vol 13, No 2: June 2024 Vol 13, No 1: March 2024 Vol 12, No 4: December 2023 Vol 12, No 3: September 2023 Vol 12, No 2: June 2023 Vol 12, No 1: March 2023 Vol 11, No 4: December 2022 Vol 11, No 3: September 2022 Vol 11, No 2: June 2022 Vol 11, No 1: March 2022 Vol 10, No 4: December 2021 Vol 10, No 3: September 2021 Vol 10, No 2: June 2021 Vol 10, No 1: March 2021 Vol 9, No 3: December 2020 Vol 9, No 2: August 2020 Vol 9, No 1: April 2020 Vol 8, No 3: December 2019 Vol 8, No 2: August 2019 Vol 8, No 1: April 2019 Vol 7, No 3: December 2018 Vol 7, No 2: August 2018 Vol 7, No 1: April 2018 Vol 6, No 3: December 2017 Vol 6, No 2: August 2017 Vol 6, No 1: April 2017 Vol 5, No 3: December 2016 Vol 5, No 2: August 2016 Vol 5, No 1: April 2016 Vol 4, No 3: December 2015 Vol 4, No 2: August 2015 Vol 4, No 1: April 2015 Vol 3, No 3: December 2014 Vol 3, No 2: August 2014 Vol 3, No 1: April 2014 Vol 2, No 3: December 2013 Vol 2, No 2: August 2013 Vol 2, No 1: April 2013 Vol 1, No 3: December 2012 Vol 1, No 2: August 2012 Vol 1, No 1: April 2012 Vol 10 More Issue