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i-manager's Journal on Electrical Engineering (JEE)

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PV-grid Performance improvement through Integrated Intelligent Water Drop Optimization with Neural Network for Maximum Power Point Tracking
A Digital Healthcare Monitoring System with Real-Time Analysis
Advancements in Smart Meter Design and Integration for Enhanced Energy Management and Efficiency
Electric Vehicles in Modern Transportation: Environmental Impacts, Configurations, and Future Trends – A Review
GTO Technique Based Hybrid Power System Controller Design

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Volume 16 Issue 2 October - December 2022

Research Paper

Conveyor Belt Regulator through Silo Operation

Abdullah Mohammed Salim Al-Hakmani* , Ch. Venkateswara Rao, Sampath Kumar B., Mohammed Junaid Mouda, Sayath Birose

*-***** University of Technology and Applied Sciences, Salalah, Sultanate of Oman.

Al-Hakmani, A. M. S., Rao, Ch. V., Kumar, B. S., Mouda, M. J., and Birose, S. (2022). Conveyor Belt Regulator through Silo Operation. i-manager’s Journal on Electrical Engineering, 16(2), 1-11. https://doi.org/10.26634/jee.16.2.19207

Abstract

Conveyor belts are used in industries such as electro-mechanical and mechanical assembly to transfer goods from one position to another or from one procedure to another. In coal mining industries, controlling the speed of a conveyor can be achieved by controlling the speed of its drive unit. The Programmable Logic Controller (PLC's) commonly used programming language has the trapezoidal chart language, Ladder Diagram (LD), the Smooth Functional Diagram (SFC), and the Function Block Language (FBD). The four-level leather belt conveyer control system belongs to the model of sequential control and therefore mainly uses the SFC to program. A Programmable Logic Controller (PLC) is used to implement the control strategy. A PLC is a microprocessor-based control device with the original drive of complementing relay logic. The latest PLCs have progressed past just a robust stage into a new realm of high computational control and processor speediness. These, along with the PLC's extremely elastic arrangement, make it an ideal stage for uses far beyond its conventional ones. The main aim of this paper is to design a PLC conveyor belt control system for silo operation that has three various modes, namely continuous mode, manual mode, and fill by pass mode. The conveyor belt plays a very effective role as it reduces the time required to complete a large amount of work and increases productivity with high efficiency. It also saves money and costs, reduces the required manpower, is characterized by ease of maintenance and handling, and offers many other benefits.

References

[1]. Basile, F., Chiacchio, P., & Gerbasio, D. (2012). On the implementation of industrial automation systems based on PLC. IEEE Transactions on Automation Science and Engineering, 10(4), 990-1003. https://doi.org/10.1109/TASE.2012.2226578

[2]. Bebic, M. Z., & Ristic, L. B. (2018). Speed controlled belt conveyors: drives and mechanical considerations. Advances in Electrical and Computer Engineering, 18(1), 51-60. https://doi.org/10.4316/AECE.2018.01007

[3]. Birmole, P., Kamble, M., Naik, S., Sadamate, A., & Korgaonkar, H. V. (2018, April). Designing and implementation of chemical mixing and filling bottles using PLC. In 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) (pp. 436-439). IEEE. https://doi.org/10.1109/ICICCT.2018.8473096

[4]. Chen, X. H., Rahman, M. L., & Zhang, Y. (2016, May). Notice of violation of IEEE publication Principles: adaptive fuzzy PID speed control of DC belt conveyor system. In 2016 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) (pp. 487-490). IEEE. https://doi.org/10.1109/SNPD.2016.7515945

[5]. Eswar, S., Jaiganesh, L., Hariprasad, N., Mohamedimthiyas, M., & Gopikrishnan, A. (2018, March). Automatic liquid mixing and filling using PLC. In 2018 International Conference on Current Trends towards Converging Technologies (ICCTCT) (pp. 1-6). IEEE. https://doi.org/10.1109/ICCTCT.2018.8551099

[6]. Li, W., Pang, Z., Zhang, H., & Meng, G. (2010a, November). Design of multi-loading control system for belt conveyor. In 2010 International Conference on EProduct E-Service and E-Entertainment (pp. 1-3). IEEE. https://doi.org/10.1109/ICEEE.2010.5661598

[7]. Li, W., Zheng, Y., & Xinfa, D. (2010b, June). The design and research of belt transport system based on PLC. In 2010 International Conference on Advances in Energy Engineering (pp. 120-124). IEEE. https://doi.org/10.1109/ICAEE.2010.5557599

[8]. Lu, Q., Wang, X., & Zhuang, L. (2012, August). Research and design of monitoring system for belt conveyor. In 2012 International Conference on Computer Science and Service System (pp. 1943-1945). IEEE. https://doi.org/10.1109/CSSS.2012.485

[9]. Pannu, J., Kulkarni, R., & Ranjana, M. S. B. (2016, March). On the automated multiple liquid bottle filling system. In 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT) (pp. 1-3). IEEE. https://doi.org/10.1109/ICCPCT.2016.7530183

[10]. Smeu, G. A. (2013, May). Automatic conveyor belt driving and sorting using SIEMENS step 7-200 programmable logic controller. In 2013 8th International Symposium on Advanced Topics in Electrical Engineering (ATEE) (pp. 1-4). IEEE. https://doi.org/10.1109/ATEE.2013.6563408

[11]. Sreejeth, M., & Chouhan, S. (2016, July). PLC based automated liquid mixing and bottle filling system. In 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES) (pp. 1-5). IEEE. https://doi.org/10.1109/ICPEICES.2016.7853685

[12]. Ulices, C., Irma, M., & Carlos, J. (2020, November). Design of an electronic coupling to control speed of motor on a conveyor belt using IoT. In 2020 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE) (pp. 115-121). IEEE. https://doi.org/10.1109/ICMEAE51770.2020.00027

[13]. Vardhan, D. S., & Narayan, Y. S. (2015, December). Development of an automatic monitoring and control system for the objects on the conveyor belt. In 2015 International Conference on Man and Machine Interfacing (MAMI) (pp. 1-6). IEEE. https://doi.org/10.1109/MAMI.2015.7456594

[14]. Yu, Y., Wang, J., Liu, W., Li, C., Zhao, L., & Fu, H. (2017, December). Design of the control system of automatic picking and conveying line based on PLC. In 2017 2nd International Conference on Robotics and Automation Engineering (ICRAE) (pp. 229-233). IEEE. https://doi.org/10.1109/ICRAE.2017.8291385

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Research Paper

Comparison of Dynamic Models of SLIM

M. Nagaraju* , G. Durga Sukumar, M. Ravindrababu*

* Vignan's Lara Instiute of Technology & Science, Vadlamudi, Andhra Pradesh, India.

Vignan Institute of Technology and Science, Deshmuki, Yadadri, Telangana, India.

* University College of Engineering Narasaraopet, JNTUK, Guntur, Andhra Pradesh, India.

Nagaraju, M., Sukumar, G. D., and Ravindrababu, M. (2022). Comparison of Dynamic Models of SLIM. i-manager’s Journal on Electrical Engineering, 16(2), 12-21. https://doi.org/10.26634/jee.16.2.19255

Abstract

The Single Linear Induction Motor (SLIM) is a specialized electrical machine that produces linear motion instead of the rotary motion produced by a traditional rotary induction motor. SLIM's accurate dynamic model is required to analyze the performance of the motor under different operating conditions. Dynamic modelling of SLIM using the traditional DQ- axis equivalent circuits is difficult due to the time-varying parameters such as end effect, air gap flux, saturation, and half-filled slot. The two methods for modelling SLIMs were compared, namely the conventional method and the split method. The results of the comparison showed that both methods provided similar results, but the split method offered a more detailed analysis of the components and provided deeper insight into the behavior of the motor. The choice between the two methods depends on the specific requirements and objectives of the analysis. In this paper, the dynamic model of SLIM is modelled using conventional and split methods in MATLAB/SIMULINK. The results of the two modelling methods are compared with each other, and it is concluded that the splitting method provides better transient performance than traditional D-Q axis methods.

References

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[10]. Seo, H., Lim, J., Choe, G. H., Choi, J. Y., & Jeong, J. H. (2018). Algorithm of linear induction motor control for low normal force of magnetic levitation train propulsion system. IEEE Transactions on Magnetics, 54(11), 1-4. https://doi.org/10.1109/TMAG.2018.2842222

[11]. Xu, D., Huang, J., Su, X., & Shi, P. (2019). Adaptive command-filtered fuzzy backstepping control for linear induction motor with unknown end effect. Information Sciences, 477, 118-131. https://doi.org/10.1016/j.ins.2018.10.032

[12]. Xu, W., Zhu, J. G., Zhang, Y., Li, Z., Li, Y., Wang, Y., & Li, Y. (2010). Equivalent circuits for single-sided linear induction motors. IEEE Transactions on Industry Applications, 46(6), 2410-2423. https://doi.org/10.1109/TIA.2010.2073434

[13]. Xu, W., Zhu, J., Guo, Y., Zhang, Y., Wang, Y., & Shi, Z. (2009, September). Steady and dynamic performance analysis of a single-sided linear induction motor. In 2009 Australasian Universities Power Engineering Conference (pp. 1-6). IEEE.

[14]. Zare-Bazghaleh, A., Naghashan, M. R., & Khodadoost, A. (2015). Derivation of equivalent circuit parameters for single-sided linear induction motors. IEEE Transactions on Plasma Science, 43(10), 3637-3644. https://doi.org/10.1109/TPS.2015.2474746

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Research Paper

Molybdenum-Based Perovskite Solar Cell with Resistance and Layer Thickness Impact on PCE and Fill Factor

Ganesh Ram Ratnakar* , Rahul Baghel**

*-** Department of Electrical and Electronics Engineering, Shri Shankaracharya Technical Campus Bhilai, Chhattisgarh, India.

Ratnakar, G. R., and Baghel, R. (2022). Molybdenum-Based Perovskite Solar Cell with Resistance and Layer Thickness Impact on PCE and Fill Factor. i-manager’s Journal on Electrical Engineering, 16(2), 22-27. https://doi.org/10.26634/jee.16.2.19217

Abstract

The performance of a perovskite photovoltaic cell based on an active layer of molybdenum trioxide and methyl ester was studied, and the results are described in this research. The FTO/MoO3/perovskite layer/PC60bm-Au is a "Fluorinedoped Tin Oxide: Molybdenum Trioxide: Perovskite Layer: PC60bm (a polycarbonate-based material) and Gold" structure that was subjected to electrical simulation using the General-Purpose Photovoltaic Device Model (GPVDM) software. The effect of series resistance and layer thickness on Power Conversion Efficiency (PCE) and Fill Factor (FF) in a Perovskite Solar Cell (PSC) based on an absorbing layer was examined using the GPVDM program. Adjustments were made by varying the values of series resistance and layer thickness. The results demonstrate that changing the value of series resistance and layer thickness can boost Power Conversion Efficiency (PCE). In this case, it resulted in an increase in Power Conversion Efficiency from 17% to 21% and an improvement in Fill Factor from 66% to 72%.

References

[1]. Joshi, P. H., Zhang, L., Hossain, I. M., Abbas, H. A., Kottokkaran, R., Nehra, S. P., & Dalal, V. L. (2016). The physics of photon induced degradation of perovskite solar cells. AIP Advances, 6(11), 115114. https://doi.org/10.1063/1.4967817

[2]. Konstantakou, M., & Stergiopoulos, T. (2017). A critical review on tin halide perovskite solar cells. Journal of Materials Chemistry A, 5(23), 11518-11549. https://doi.org/10.1039/C7TA00929A

[3]. Liao, Y., Liu, H., Zhou, W., Yang, D., Shang, Y., Shi, Z., & Ning, Z. (2017). Highly oriented low-dimensional tin halide perovskites with enhanced stability and photovoltaic performance. Journal of the American Chemical Society, 139(19), 6693-6699. https://doi.org/10.1021/jacs.7b01815

[4]. Liu, D., & Kelly, T. L. (2014). Perovskite solar cells with a planar heterojunction structure prepared using roomtemperature solution processing techniques. Nature Photonics, 8(2), 133-138. https://doi.org/10.1038/nphoton.2013.342

[5]. Miyata, A., Mitioglu, A., Plochocka, P., Portugall, O., Wang, J. T. W., Stranks, S. D., & Nicholas, R. J. (2015). Direct measurement of the exciton binding energy and effective masses for charge carriers in organic–inorganic tri-halide perovskites. Nature Physics, 11(7), 582-587. https://doi.org/10.1038/nphys3357

[6]. Reyna, Y., Salado, M., Kazim, S., Perez-Tomas, A., Ahmad, S., & Lira-Cantu, M. (2016). Performance and stability of mixed FAPbI3 (0.85) MAPbBr3 (0.15) halide perovskite solar cells under outdoor conditions and the effect of low light irradiation. Nano Energy, 30, 570-579. https://doi.org/10.1016/j.nanoen.2016.10.053

[7]. Roy, P., Raoui, Y., & Khare, A. (2022). Design and simulation of efficient tin based perovskite solar cells through optimization of selective layers: Theoretical insights. Optical Materials, 125, 112057. https://doi.org/10.1016/j.optmat.2022.112057

[8]. Roy, P., Sinha, N. K., Tiwari, S., & Khare, A. (2020). A review on perovskite solar cells: Evolution of architecture, fabrication techniques, commercialization issues and status. Solar Energy, 198, 665-688. https://doi.org/10.1016/j.solener.2020.01.080

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[10]. Stranks, S. D., Eperon, G. E., Grancini, G., Menelaou, C., Alcocer, M. J., Leijtens, T., & Snaith, H. J. (2013). Electron-hole diffusion lengths exceeding 1 micrometer in an organometal trihalide perovskite absorber. Science, 342(6156), 341-344. https://doi.org/10.1126/science.1243982

[11]. Takahashi, Y., Hasegawa, H., Takahashi, Y., & Inabe, T. (2013). Hall mobility in tin iodide perovskite CH3NH3SnI3: Evidence for a doped semiconductor. Journal of Solid State Chemistry, 205, 39-43. https://doi.org/10.1016/j.jssc.2013.07.008

[12]. Valverde-Chávez, D. A., Ponseca, C. S., Stoumpos, C. C., Yartsev, A., Kanatzidis, M. G., Sundström, V., & Cooke, D. G. (2015). Intrinsic femtosecond charge generation dynamics in single crystal CH 3 NH 3 PbI 3. Energy & Environmental Science, 8(12), 3700-3707. https://doi.org/10.1039/C5EE02503F

[13]. Wang, Y., & Han, L. (2019). Research activities on perovskite solar cells in China. Science China Chemistry, 62, 822-828. https://doi.org/10.1007/s11426-019-9461-1

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Research Paper

Dynamic Harmonic Domain Approach to Assess Performance of Three-Phase Fixed Capacitor Thyristor Controlled Reactor (FC-TCR)

Jayababu Badugu* , G. Nageswara Reddy, Kurakula Vimala Kumar*

* Department of Electrical and Electronics Engineering, Vignan's Lara Institute of Technology and Science, Vadlamudi, Guntur, India.

Department of Electrical and Electronics Engineering, YSR Engineering College of Yogi Vemana University, Proddatur, Andhra Pradesh, India.

* Department of Electrical and Electronics Engineering, University College of Engineering Narasaraopet, Palnadu, India.

Badugu, J., Reddy, G. N., and Kumar, K. V. (2022). Dynamic Harmonic Domain Approach to Assess Performance of Three-Phase Fixed Capacitor Thyristor Controlled Reactor (FC-TCR). i-manager’s Journal on Electrical Engineering, 16(2), 28-40. https://doi.org/10.26634/jee.16.2.19226

Abstract

Harmonics have become an important issue as the number of non-linear elements and electronic devices coupled to electrical power systems increases by the day. A Fixed Capacitor Thyristor Controlled Reactor (FC-TCR) is widely used in power systems to continuously control reactive power. This paper presents the harmonic analysis of a three-phase FC-TCR under different operating conditions using the Dynamic Harmonic Domain (DHD) technique. The existing Harmonic Domain (HD) method is widely used to obtain the steady-state harmonics in the power grid. It is not possible to calculate transient harmonics using the harmonic domain method. The dynamic harmonic domain technique also provides a solution for the transient condition. The three-phase FC-TCR is simulated in a MATLAB environment and calculates transient harmonic quantities such as apparent power S(t), reactive power Q(t), real power P(t), and distortion power D(t), RMS values, and distortion factors of the three-phase FC-TCR when subjected to voltage disturbance.

References

[1]. Badugu, J., & Nageswarareddy, G. (2013). Identification of harmonic problems using power quality analyzer-a case study. International Journal of Research in Advent Technology, 1(5), 150-157.

[2]. Badugu, J., & Nageswarareddy, G. (2021). Harmonics prediction of power system network in the presence of facts devices. International Journal of Advance Research, Ideas and Innovations in Technology, 7(4), 1856-1860.

[3]. Badugu, J., Obulesu, Y. P., & Saibabu, C. (2018a). Harmonic analysis of three-phase fixed capacitor-thyristor controlled reactor under balanced and unbalanced conditions. IAES International Journal of Robotics and Automation, 7(1), 67-76. https://doi.org/10.11591/ijra.v7I1

[4]. Badugu, J., Obulesu, Y. P., & Saibabu, C. (2018b). Investigation of THD analysis in residential distribution systems with different penetration levels of electric vehicles. International Journal of Electrical and Computer Engineering Systems, 9(1), 21-27.

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[7]. Collins, C. D., Bathurst, G. N., Watson, N. R., & Wood, A. R. (2005a). Harmonic domain approach to STATCOM modelling. IEE Proceedings-Generation, Transmission and Distribution, 152(2), 194-200. https://doi.org/10.1049/ip-gtd:20041227

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Review Paper

Optimizing Power System Operations for Extreme Weather Events: A Review

A. Bindu*

Department of Electrical and Electronics Engineering, CSI Institute of Technology, Thovalai, Tamil Nadu, India.

Bindu, A. (2022). Optimizing Power System Operations for Extreme Weather Events: A Review. i-manager’s Journal on Electrical Engineering, 16(2), 41-53. https://doi.org/10.26634/jee.16.2.19301

Abstract

Extreme weather events, such as hurricanes, heat waves, and winter storms, can have a significant impact on power systems, leading to power outages and disruptions in service. This review aims to optimize power system operations to enhance resilience and minimize the impact of extreme weather events. The review will include the development of advanced modelling and simulation tools to analyze the impact of extreme weather events on power systems. These tools will be used to evaluate the performance of different power system configurations and identify vulnerabilities. Additionally, the review will investigate the potential of distributed energy resources, such as micro-grids and energy storage systems, to enhance power system resilience. The effectiveness of different control and protection strategies will also be evaluated. The review will provide valuable insights for power system operators and regulators in the planning and operation of power systems to withstand extreme weather events. Ultimately, the review will contribute to the development of a more robust and resilient power system, ensuring reliable and safe power supply to customers.

References

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[2]. Bie, Z., Lin, Y., Li, G., & Li, F. (2017). Battling the extreme: A study on the power system resilience. Proceedings of the IEEE, 105(7), 1253-1266. https://doi.org/10.1109/JPROC.2017.2679040

[3]. Ebi, K. L., Boyer, C., Bowen, K. J., Frumkin, H., & Hess, J. (2018). Monitoring and evaluation indicators for climate change-related health impacts, risks, adaptation, and resilience. International Journal of Environmental Research and Public Health, 15(9), 1943. https://doi.org/10.3390/ijerph15091943

[4]. Eskandarpour, R., Lotfi, H., & Khodaei, A. (2016, September). Optimal microgrid placement for enhancing power system resilience in response to weather events. In 2016 North American Power Symposium (NAPS) (pp. 1-6). IEEE. https://doi.org/10.1109/NAPS.2016.7747938

[5]. Guenaou, J., Henneaux, P., & Kirschen, D. S. (2022, October). Impact of distributed energy resources on power system resilience against earthquakes. In 2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) (pp. 1-5). IEEE. https://doi.org/10.1109/ISGT-Europe54678.2022.9960485

[6]. Hay, J. (2007). Extreme weather and climate events, and farming risks. Managing Weather and Climate Risks in Agriculture, 1-19. https://doi.org/10.1007/978-3-540-72746-0_1

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[8]. Leifeld, J., & Menichetti, L. (2018). The underappreciated potential of peatlands in global climate change mitigation strategies. Nature Communications, 9(1), 1071. https://doi.org/10.1038/s41467-018-03406-6

[9]. Mishra, N., Soni, H. K., Sharma, S., & Upadhyay, A. K. (2018). Development and analysis of artificial neural network models for rainfall prediction by using time-series data. International Journal of Intelligent Systems and Applications, 12(1), 16-23.

[10]. Mumtaz, F., & Bayram, I. S. (2017). Planning, operation, and protection of microgrids: An overview. Energy Procedia, 107, 94-100. https://doi.org/10.1016/j.egypro.2016.12.137

[11]. Panteli, M., & Mancarella, P. (2015). Influence of extreme weather and climate change on the resilience of power systems: Impacts and possible mitigation strategies. Electric Power Systems Research, 127, 259-270. https://doi.org/10.1016/j.epsr.2015.06.012

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i-manager's Journal on Electrical Engineering (JEE)

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Volume 16 Issue 2 October - December 2022

Conveyor Belt Regulator through Silo Operation

Abdullah Mohammed Salim Al-Hakmani* , Ch. Venkateswara Rao**, Sampath Kumar B.***, Mohammed Junaid Mouda****, Sayath Birose*****

*-***** University of Technology and Applied Sciences, Salalah, Sultanate of Oman.

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Comparison of Dynamic Models of SLIM

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* Vignan's Lara Instiute of Technology & Science, Vadlamudi, Andhra Pradesh, India. ** Vignan Institute of Technology and Science, Deshmuki, Yadadri, Telangana, India. *** University College of Engineering Narasaraopet, JNTUK, Guntur, Andhra Pradesh, India.

Nagaraju, M., Sukumar, G. D., and Ravindrababu, M. (2022). Comparison of Dynamic Models of SLIM. i-manager’s Journal on Electrical Engineering, 16(2), 12-21. https://doi.org/10.26634/jee.16.2.19255

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Molybdenum-Based Perovskite Solar Cell with Resistance and Layer Thickness Impact on PCE and Fill Factor

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Dynamic Harmonic Domain Approach to Assess Performance of Three-Phase Fixed Capacitor Thyristor Controlled Reactor (FC-TCR)

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Optimizing Power System Operations for Extreme Weather Events: A Review

A. Bindu*

Department of Electrical and Electronics Engineering, CSI Institute of Technology, Thovalai, Tamil Nadu, India.

Bindu, A. (2022). Optimizing Power System Operations for Extreme Weather Events: A Review. i-manager’s Journal on Electrical Engineering, 16(2), 41-53. https://doi.org/10.26634/jee.16.2.19301

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Abdullah Mohammed Salim Al-Hakmani* , Ch. Venkateswara Rao, Sampath Kumar B., Mohammed Junaid Mouda, Sayath Birose

M. Nagaraju* , G. Durga Sukumar, M. Ravindrababu*

* Vignan's Lara Instiute of Technology & Science, Vadlamudi, Andhra Pradesh, India.

Vignan Institute of Technology and Science, Deshmuki, Yadadri, Telangana, India.

* University College of Engineering Narasaraopet, JNTUK, Guntur, Andhra Pradesh, India.

Jayababu Badugu* , G. Nageswara Reddy, Kurakula Vimala Kumar*