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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 530 Documents
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Enhancing solar power generation through AC power prediction optimization in solar plants Krishnan, G. Hari; Thrinath, B. V. Sai; Reddy, M. Ramprasad; Sudhakar, Thukkaram
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.pp645-652

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.
Weighted sum method based multi-objective optimal power flow considering various objectives: an application of whale optimization algorithm Naidu, Tentu Papi; Balasubramanian, Ganapathy; Bathina, Venkateswara Rao
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i4.pp963-972

Abstract

Nowadays, multi-objective optimization plays a vital role in solving optimal power flow problems. Multi-objective optimal power flow (MOOPF) is a nonlinear optimization problem aimed at optimizing control variables while balancing multiple objective functions and satisfying both equality and inequality constraints and addresses this by integrating two more objectives into a single objective using a weighting factor. In this paper this weighted sum type multi-objective technique has been used to formulate the objective function. The whale optimization algorithm (WOA) has been used to reduce the cost, emission, losses, and voltage stability by considering various multi objectives like fuel cost along with emission, fuel cost with losses, fuel cost with voltage stability, fuel cost with voltage deviation and finally fuel cost with emission, losses, voltage deviation. In this paper, the IEEE 30 bus structure has been used to analyze the effect of WOA on the improvement of system performance. Obtained results with WOA have been compared with other optimization techniques like ensemble constraint handling technique with differential evolution (ECHT-DE), the superiority of feasible differential evolution (SF-DE), moth swarm algorithm (MSA), and moth-flame optimization (MFO), available in the literature.
Time-series trendline and curve-fitting-based approach to short-term electricity demand forecasting Anichebe, Ifeanyi Benitus; Ekwue, Arthur Obiora; Obe, Emeka Simon
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i1.pp81-90

Abstract

Electricity load demand forecasting and its accuracy is an important process for utility planning, maintenance, scheduling, operation, and control in power systems. Historical data are also very vital in demand forecasting processes. This study examined weekly electricity demand forecasting model using trendline methods which include linear trendline, moving average, exponential smoothing, quadratic, and logarithmic trends. The calculations and analysis were carried out using Microsoft Excel. The results were compared using known performance evaluation metrics such as mean absolute percentage error (MAPE) and root mean square error (RMSE). Cubic root mean error (CRME) was introduced as a performance evaluation metric. The hybrid (quadratic-logarithmic) method was found to outperform the other individual trendline methods. This method produced the lowest value of MAPE, RMSE, and CRME representing 14.41%, 14.68%, and 14.65% respectively which indicated that hybrid model performs better than individual models operating separately when used in forecasting.
Reliability analysis of an automated radial distribution feeder for different configurations and considering the effect of forecasted electrical vehicle charging stations Rekha, V. Swarna; Vidyasagar, E.
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i1.pp178-185

Abstract

In the future, the expansion of electrical vehicles is becoming more prevalent, which requires electric vehicle charging stations (EVCS), and at the same time, distribution automation and smart grid technology will be implemented as part of the reforms in the distribution system. This paper reviews the effect of the increased EVCS, which causes an increase in the magnitude of current and moderates the average failure rate of feeder sections. The implementation of distribution automation and a smart grid reduces the average restoration time, thereby increasing the reliability of the distribution system. The number of electrical vehicles (EVs) for the years 2025 and 2030 is forecasted using Holt's model, and the corresponding average failure rate of feeder sections is calculated. The average switching time for adopting distribution automation and smart grid technology is taken as 5 seconds and 20 milliseconds, respectively. The voltages, power losses, and reliability indices are calculated assuming the EV charging points are located with equal capacity at all load buses for different configurations of radial feeders. The results are compared with the reliability indices of the feeder of all the configurations in the absence of EV charging station loads, automation, and smart grid technology. This work is validated on a standard IEEE 33 test bus system.
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.
Low cost pulsed electric field generator using DC-DC boost converter and capacitor diode voltage multiplier Thulasidas, Jeya Shree; Purushothaman, Srinivasan; Ravishanker, Srivatsen; Mourougaiyan, Thejaswaroopan; Anilkumar, Arruthra
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i4.pp874-885

Abstract

Traditional high-voltage pulse generators, like Marx generators often face challenges related to efficiency and complexity. In this paper, a solid-state multi-module high-voltage pulse generator that integrates capacitor-diode voltage multipliers (CDVM) with DC-DC boost converters and closed-loop voltage control is proposed to overcome these challenges. The system achieves high output voltage by coupling the pulsed output voltages of individual low-voltage DC sources in series across each module. The proposed design was modeled using MATLAB, and experimental testing was conducted on a single stage. Comparative analyses between timedomain parameters, proportional-integral (PI), and fractional order proportional integral derivative (FOPID) controllers were performed. Both MATLAB simulations and experimental validations demonstrate the effectiveness of this approach. The rise time, peak time, settling time, and steady-state error are all improved using an FOPID controller, decreasing from 0.32 to 0.31 seconds, 0.42 to 0.35 seconds, and 3.15 to 2.20 seconds, respectively. These findings indicate that a closed-loop FOPID controller enhances time-domain performance parameters more effectively than a PI controller for a two-stage DC-DC voltage multiplier.
Fuzzy logic-based approach for optimal allocation of distributed generation in a restructured power system Lindsay, Mahiban; Emimal, M.
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i1.pp123-129

Abstract

Fuzzy logic emerges as a powerful tool for optimizing power flow solutions, particularly in the context of deregulated power systems. By employing fuzzy logic controls, the ideal placement of distribution generators (DGs) can be determined, ensuring the reliability indices are identified through optimal power flow solutions and fuzzy logic controllers to maintain system feasibility. In a deregulated power system, strategic placement of distribution generator units plays a crucial role in minimizing power loss and enhancing overall system performance by mitigating fluctuations. To identify areas of weakness, especially within transmission companies, accessing optimal power flow algorithms becomes essential in a deregulated power system. Both transmission and distribution networks should be appropriately adjusted to alleviate congestion within the respective companies. The aggregator must assess system performance, utilizing data obtained from distribution and transmission companies within the deregulated power system.
A regulatory power split strategy for energy management with battery and ultracapacitor Mohanan, Sreekala Vazhakkuzhackal; Vijayan, Abhilash Theckevalel
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i2.pp442-452

Abstract

Electric vehicle batteries face fast degradation due to the high frequency of charging/discharging cycles and great peak power demands. Lifetime, continuity of supply and power density of these batteries affect the performance of electric vehicles (EVs). Hybrid energy storage systems (HESS) offers a feasible solution by incorporating other energy storage elements like ultra-capacitor (UC) along with battery. Their combination provides higher efficiency and better performance in terms energy/power density. UC can behave like a power buffer when the EV is accelerating and regenerating. The HESS needs a controller that can split the available power between different sub systems as per demand. This paper presents a regulatory control strategy useful in HESS with battery and UC for the speed regulation of a brushless DC (BLDC) motor using a 3-port bidirectional DC-DC converter. The regulatory control strategy monitors the state of charge (SOC) of UC and a fuzzy logic controller regulates the power flow between HESS and the motor. Simulation in MATLAB validates the efficacy of the strategy. Simulation results and hardware evaluation confirm that the regulatory control scheme is effective in splitting the available power according to the load demand and achieves better energy efficiency.
Optimized control strategy for a three-phase grid connected inverter using PI controller and DQ frame Arise, Nagasridhar; Saiteja, Madde; Siddu, V.; Kavya, Vadluri; Vijay, Mada
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i4.pp790-797

Abstract

This paper provides a proportional-integral (PI) controller and direct-quadrature (DQ) frame transformation-based optimum control method for a three-phase grid-connected inverter. In terms of grid synchronization, voltage regulation, and harmonic abatement, the proposed control technique attempts to improve the inverter's performance. By separating the control of active and reactive power, the control structure is made simpler and independent regulation of these parameters is possible. This improves the inverter's capacity to quickly react to grid disruptions and track reference values accurately. In order to lower carbon emissions and improve grid dependability, it has become vital to integrate renewable energy sources into the current power grid. Grid-connected inverters are essential in this situation because they transform DC electricity from renewable sources into grid-safe AC power. This abstract outline a proportional-integral (PI) controller and direct-quadrature (DQ) frame-based optimal control method for a three-phase grid-connected inverter using a MATLAB simulation.
Contribution to the comparison of conventional concentric magnetic gear and double stage concentric magnetic gear for high power offshore wind applications Philippe, d’Almeida Renaud; Gilles, Agbokpanzo Richard; Macaire, Agbomahena Bienvenu
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i1.pp30-44

Abstract

Nowadays, the replacement of mechanical technologies by magnetic technologies has several advantages. Therefore, in this paper, we compare in an indirect drive chain the conventional concentric magnetic gear (CCMG) and the double-stage concentric magnetic gear (DSCMG) used as a speed multiplier for a high-power offshore wind turbine. This comparison is performed for the same gear ratio and the same torque at the input of both magnetic gears to obtain the same torque values at the output of each gear. The goal is to determine which one has the smaller amount of magnet and the higher volumetric torque density. After the calculation of the gear ratio, a first choice of geometrical parameters is adopted. Several simulations carried out by the finite element method (FEM) allowed to obtain the desired torques and to fix the final geometrical parameters of each magnetic gear. The results obtained show that the DSCMG has both the smallest magnet volume and the highest volumetric torque density compared to the CCMG.

Page 41 of 53 | Total Record : 530

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