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All Journal International Journal of Renewable Energy Development International Journal of Renewable Energy Development
Rasool, Akhtar
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Chemistry Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering

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Modeling and Analysis of the Dynamic Response of an Off-Grid Synchronous Generator Driven Micro Hydro Power System Ali, Waqas; Farooq, Haroon; Rasool, Akhtar; Sajjad, Intisar Ali; Zhenhua, Cui; Ning, Lin
International Journal of Renewable Energy Development Vol 10, No 2 (2021): May 2021
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2021.33567

Abstract

This paper models and analyses the dynamic response of a synchronous generator driven off-grid micro hydro power system using Simulink tool of MATLAB software. The results are assessed from various perspectives including regulation through no load to full load and overload scenarios under normal and abnormal operating conditions. The investigation under the normal conditions of no load, linearly changing load and full load divulges that the system operates in a satisfactory manner as generator voltage and frequency remain approximately constant at 1 pu. However, at full load generator voltage and frequency drop 3% and 0.5% respectively from its nominal values but remain within prescribed standard IEC limits. The results also expose that the abnormal conditions produced by abrupt changes in load, system faults and severe overload, cause the unwonted variations in the magnitude of generator parameters. Moreover, the study reveals that the system stability significantly enhances when the system is run at full load because the regulation time to fix the variations in the generator parameters; except input mechanical power; decreases, e.g. from 4.1 sec to 0.8 sec for generator voltage, with the increase in the loading from quarter to full load respectively at unity power factor. Further, it is also observed that the regulation time rises, e.g. from 0.8 sec to 1.3 sec for generator voltage, with the reduction in load power factor from unity to 0.8, respectively. Thus, proper protection, to cater for increased fault current at full load and power factor correction must be provided to improve the system stability and protection. Furthermore, it is also concluded that the over loading in any case should be strongly avoided in this type of system and it should never be allowed to exceed 20% of the full load value to avoid system failure 
AI-optimization operation of biomass-based distributed generator for efficient radial distribution system Ali, Muhammad Abid; Bhatti, Abdul Rauf; Farhan, Muhammad; Rasool, Akhtar; Ali, Ahmed
International Journal of Renewable Energy Development Vol 13, No 6 (2024): November 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60224

Abstract

This research aims to optimize the size and location of biomass-based distributed generator (BMDG) units to enhance the voltage profile, reduce electrical losses, maximize cost savings, and decrease emissions from power distribution systems. Biomass-based distributed generator (BMDG) systems offer numerous advantages to enhance the efficiency of power distribution systems. However, achieving these benefits relies on determining the optimal size and position of the BMDGs. To achieve these objectives, the metaheuristic technique called particle swarm optimization (PSO) is employed to find the optimal placement and size of BMDGs. The proposed model was validated on MATLAB's IEEE-33 bus radial distribution system (RDS), confirming the aforementioned benefits. Comparative analysis between the PSO-based technique and other algorithms from previous research revealed better results with the proposed method. The results indicate that optimal placement and sizing of BMDG units have led to a reduction of more than 67.68% in active power losses and 65.90% in reactive power losses compared to the base case. Additionally, the reduction in active power loss was 40.44%, 11.39%, 42.85%, 1.81%, 0.85%, 29.83%, 5.82% and 28.38% more than artificial bee colony, backtracking search optimization algorithm, moth-flame optimization, Coordinate control, artificial Hummingbird algorithm, variable constants PSO (VCPSO), artificial gorilla troops optimizer (AGTO), and a jellyfish search optimizer respectively. Furthermore, the reactive power losses were reduced by 38.33% and 15.68% compared to VCPSO and AGTO respectively. Furthermore, this study revealed a cost reduction of 6.38% when compared to the AGTO and 1.30% when compared to the AHA. Moreover, the voltage profile of the power distribution system was improved by 7.28%. The presented methodology has demonstrated promising results for BMDGs in RDS across various applications.
Co-Authors Ali, Ahmed Ali, Muhammad Abid Ali, Waqas Bhatti, Abdul Rauf Farooq, Haroon Muhammad Farhan Ning, Lin Sajjad, Intisar Ali Zhenhua, Cui