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International Journal of Applied Power Engineering (IJAPE)
ISSN : 22528792     EISSN : 27222624     DOI : -
Core Subject : 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 7 Documents
Search results for , issue "Vol 11, No 2: June 2022" : 7 Documents clear
Contribution to the systemic modeling of a photovoltaic devices Hamza, Wertani; Jamel, Ben Salem; Lakhoua, Mohamed Najeh
International Journal of Applied Power Engineering (IJAPE) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v11.i2.pp%p

Abstract

The modeling of systems using systemic tools has been for a few years, a subject which has attracted the attention of scientists and especially researchers to allow designers to acquire a rigorous approach to problem solving using the capabilities of already existing methods and tools. This document presents a contribution in the field of modeling, where a methodology based on two methods has been proposed. The first concerns the functional analysis to extract the use functions and the constraint parameters from the system. In this methodology, the static functional study is carried out using the SADT method. On the other hand, the dynamic behavioral analysis is carried out by the SA-RT method. Then, we used a behavioral and parametric analysis, the Bond Graph method, to observe the evolution of representative quantities of a photovoltaic system.
Evaluation of brushless DC motor structure design for the electric impact using 3-D finite element analysis M. Senthil Raja; B. Geethalakshmi
International Journal of Applied Power Engineering (IJAPE) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (652.133 KB) | DOI: 10.11591/ijape.v11.i2.pp156-164

Abstract

In this article, an analytical model is deployed to optimize and design an interior permanent magnet brushless DC motor (IPMBLDC motor) when compared to theoretical structure of IPMBLDC. In this motor, assume air-gap of magnet assembly, distribution of flux density coefficient, selection of functional point in the permanent magnet, Torque density, and permanent magnet dimension compares with air-gap were deployed in an ideal design model. An equivalent circuit of magnetic field was improved and compare with the total flux density distribution and the torque density efficiency is based on initial ideal design factors. In finite element of MAXWELL 3D method, an electromagnetic field is investigated and used to verify an advanced equivalent circuit of magnetic field and improve the IPMBLDC motor factors. Finally, simulation results of IPMBLDC motor are verify and compare with ideal factors of IPMBLDC motor.
Assessment of the influence of wind energy incorporated capacity benefit margin in ATC computation Olatunji Obalowu Mohammed; Mohd Wazir Mustafa; Sani Salisu; Ahsanullah Memon; Saddam Hussain; Abdulrahaman Okino Otuoze; Oladimeji Ibrahim
International Journal of Applied Power Engineering (IJAPE) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (614.77 KB) | DOI: 10.11591/ijape.v11.i2.pp145-155

Abstract

Available transfer capability (ATC) is an important metric used to measure the techno-economic viability of the transmission networks. Several methods have been presented in literature for ATC assessment, however, only some few articles incorporate CBM in ATC calculation and those few papers only considered conventional power generation sources in CBM evaluation. CBM is a function of the reliability of generating units. This paper presents the inter-area CBM calculation in the presence of wind energy source using graph theory technique and the results are incorporated in ATC computation using repeated power flow. CBM is incorporated in ATC computation as non-recallable and recallable power transfers. The results with and without CBM incorporation, in the presence of wind power system, are compared. The contribution of the paper is to study the influence of wind power (WP) integrated CBM on ATC evaluation. The results showed that the incorporation of CBM, in the presence of renewable energy, has a significant influence on ATC, without which ATC would be inaccurately estimated. Simulations using IEEE 24-Bus RTS is used to implement the proposed approach. This approach can be employed by transmission operators to assess the technoeconomic viability of the power network for possible power transactions.
Power quality improvement of grid-connected photovoltaic systems using PI-fuzzy controller Marwan Saded Ahmed; Dhari Yousif Mahmood; Ali Hussein Numan
International Journal of Applied Power Engineering (IJAPE) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1549.149 KB) | DOI: 10.11591/ijape.v11.i2.pp120-133

Abstract

To ensure enhanced reliability and availability of electricity to consumers, grid-connected photovoltaic systems need to improve their power quality, this paper uses a three-phase five levels cascaded H-bridge inverter in grid-connected mode to improve the flexibility and efficiency of the photovoltaic system. Each photovoltaic (PV) array in the proposed system has a maximum power point tracker (MPPT) to extract the PV array maximum power point for a particular irradiance and temperature and reduce the mismatch that causes an imbalance in the power sent from the inverter to the main grid. The fuzzy logic controller is used to tune the proportional-integral (PI) controller to regulate the current and voltage of the grid-connected inverter by changing the gain of the PI controller (Kp, Ki) to obtain a fast response and improve the power quality of the system despite different load disturbances and inputs. The system was simulated in MATLAB/Simulink, and the results show the superiority of the proposed control unit, in which a pure and stable sine output voltage and current waveforms. Finally, the total harmonic distortion (THD) is improved to reach 3.81% based on the fuzzy PI controller, while 7.77% is based on the PI controller.
A multi-scale dual-stage model for PV array fault detection, classification, and monitoring technique Siti Nor Azlina Mohd Ghazali; Muhamad Zahim Sujod
International Journal of Applied Power Engineering (IJAPE) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (777.279 KB) | DOI: 10.11591/ijape.v11.i2.pp134-144

Abstract

The output generated by photovoltaic arrays is influenced mainly by the irradiance, which has non-uniform distribution in a day. This has resulted in the current-limiting nature and nonlinear output characteristics, and conventional protection devices cannot detect and clean faults appropriately. This paper proposes a low-cost model for a multi-scale dual-stage photovoltaic fault detection, classification, and monitoring technique developed through MATLAB/Simulink. The main contribution of this paper is that it can detect multiple common faults, be applied on multi-scale photovoltaic arrays regardless of environmental conditions, and be beneficial for photovoltaic system maintenance work. The experimental results show that the developed algorithm using supervised learning algorithms mutual with k-fold cross-validation has produced good performances in identifying six common faults of photovoltaic arrays, achieved 100% accuracy in fault detection, and achieved good accuracy in fault classification. Challenges and suggestions for future research direction are also suggested in this paper. Overall, this study shall provide researchers and policymakers with a valuable reference for developing photovoltaic system fault detection and monitoring techniques for better feasibility, safety, and energy sustainability.
Artificial intelligence for energy fraud detection: a review Sushmita Poudel; Udaya Raj Dhungana
International Journal of Applied Power Engineering (IJAPE) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (616.336 KB) | DOI: 10.11591/ijape.v11.i2.pp109-119

Abstract

Energy fraud in the distribution sector of electric utility includes electricity theft, meter tampering, or billing error. This fraud causing non-technical loss has led to an economic loss of the company. In order to detect and minimize fraud, different technologies have been used. From conventional methods to development in the field of artificial intelligence (AI), effective and reliable fraud detection methods have been proposed. This paper first provides an overview of different proposed methods for non-technical loss detection and evaluate the advantage and limitation of using those methods. Furthermore, several supervised and unsupervised machine learning methods for detecting electricity theft are discussed in summary along with their metrics and attributes used. Finally, these methods are classified based on the overall operation and the parameters used. This paper provides comparisons of several fraud detection methods using AI along with their weak and strong points and this information is very useful for the researchers who are working in the field of AI method for detecting fraud.
A-star algorithm based on admissible searching for strategically placing PMU considering redundancy and cost/benefit analysis Rohit Babu; Biplab Bhattacharyya
International Journal of Applied Power Engineering (IJAPE) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (525.557 KB) | DOI: 10.11591/ijape.v11.i2.pp165-178

Abstract

This research examines an admissible search algorithm-dependent A-star strategy and takes into account redundancy and cost/benefit analysis under normal operating conditions. The goal is to allocate a phasor measurement unit (PMU) for maximal observability of the interconnected power network. To determine the fewest number of PMU required to make the connected power network totally observable using redundancy analysis, the A-star approach is utilized. The redundancy analysis of the power network is carried out in order to determine the appropriate PMU placement, which results in the acquisition of total power network observability and reliability. To put the suggested technique through its paces, it has been tested on IEEE-standard test systems such as IEEE-14 bus, IEEE-30 bus, New England-39 bus, IEEE-57 bus, and IEEE-118 bus. The results obtained using the suggested methodology are compared to those obtained through standard literature research. The experimental findings of the suggested method revealed the resilience and accuracy of the A-star algorithm as well as its effectiveness in achieving maximum observability of the connected power network.

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