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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 11 Issue 4 April - June 2018

Research Paper

Design and Implementation of Solar PV Emulator Using Magna DC Power Supply

Aya Amer* , Nehaja Joglekar, Tassneem Zamzam*, Atif Iqbal****

- UG Scholar, Department of Electrical Engineering, Qatar University, Doha, Qatar.

** Associate Professor, Department of Electrical Engineering, Qatar University, Doha, Qatar.

Amer, A., Joglekar, N., Zamzam, T., and Iqbal, A. (2018). Design and Implementation of Solar PV Emulator Using Magna DC Power Supply. i-manager’s Journal on Electrical Engineering, 11(4), 1-8. https://doi.org/10.26634/jee.11.4.14652

Abstract

The aim of this paper is to emulate commercial PV module under different parameters and environmental condition (insolation or temperature change) by using Photovoltaic Power Profile Emulation (PPPE) software and Magna DC power supply. This method can be used, where the real PV panels are not available or hard to work within lab conditions. The PPPE software automatically calculates solar array voltage and current profiles based on predefined values entered by the user. After this, profiles are sequentially sent to a Magna-Power supply. The user can define a limitless number of profiles to be emulated and sequenced over a given period of time.

References

[1]. Application of Non-Conventional & Renewable Energy Sources. (n.d.). Bureau of Energy Efficiency. Retrieved from http://www.em-ea.org/Guide Books/book- 4/4.12 App of Non conventional.pdf

[2]. Arjyadhara, P., Ali, S. M., & Chitralekha, J. (2013). Analysis of solar PV cell performance with changing irradiance and temperature. International Journal of Engineering and Computer Science, 2(1), 214-220. s

[3]. Can, H. (2013). Model of a photovoltaic panel emulator in MATLAB-Simulink. Turkish Journal of Electrical Engineering & Computer Sciences, 21(2), 300-308.

[4]. Das, D., & Pradhan, S. K. (2011). Modeling and simulation of PV array with boost converter: An open loop study (Doctoral Dissertation, NIT, Rourkela).

[5]. ET-System DC Sources. PV Simulator Option. Technical Handbook. Retrieved from http://www.et-system.de/ en/applications/dc-sources.html

[6]. Kumari, J., & Babu, C. S. (2012). Mathematical modeling and simulation of photovoltaic cell using Matlab-Simulink environment. International Journal of Electrical and Computer Engineering, 2(1), 26-34.

[7]. Basics of MPPS Solar Charge Controller (n.d.). In LEONICS . Retrieved from http : / / www. leonics. com/support/article2_14j/articles2_14j_en.php

[8]. Meshram, P., & Mujumdar, U. B. (2013). Design and Development of MPPT based converter for efficient solar power conversion. In 2^nd National Conference on Innovative Paradigms in Engineering & Technology (pp. 35-39).

[9]. Messenger, R. A., & Abtahi, A. (2017). Photovoltaic Systems Engineering. CRC Press.

[10]. Pelin, D., Jukić Antolović, J., & Rapčan, V. (2014). PV emulator. International Journal of Electrical and Computer Engineering Systems, 5(1), 21-26.

[11]. Programmable DC Power Supplies. (n.d.). Retrieved from http://www.magna-power.com/products/magnadc

[12]. Taylor, T. H. (2001). Alternate Energy Sources. Bristol: Adam Hilger Ltd.

[13]. Xiao, W., Dunford, W. G., & Capel, A. (2004, June). A novel modeling method for photovoltaic cells. In Power Electronics Specialists Conference, 2004. PESC 04. 2004 IEEE 35^th Annual (Vol. 3, pp. 1950-1956). IEEE.

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Research Paper

Comparison of Harmonics, THD and Temperature Analysis of 3-Phase Induction Motor with Normal Inverter Drive and 5-Level DCMI Drive

Manjesh*

Associate Professor, Department of Electronic Science, Bangalore University, Bengaluru, Karnataka, India.

Manjesh (2018). Comparison of Harmonics, THD and Temperature Analysis of 3-Phase Induction Motor with Normal Inverter Drive and 5-Level DCMI Drive. i-manager’s Journal on Electrical Engineering, 11(4), 9-17. https://doi.org/10.26634/jee.11.4.14655

Abstract

In the present technology, the applications of DC motors are replaced by induction motors due to its advantages. Most of the applications are in domestic and industrial applications. The motor used in industrial applications are high torque and long working time, frequently used motors, therefore the efficiency and life time of the motor is very essential factors to be monitored during its working. In this work, the normal voltage source inverter and multilevel inverter are used to run the motor. The major hurdle of using an inverter is, it produces harmonics and these harmonics induce the unnecessary current and voltage harmonics into the loads. These harmonics are simply dissipated as heat in the motor and degrade the motor performance with reducing the motor lifetime. To study the effects of different levels of multi-level inverter drives with respect to heating of the motor, the thermocouples are placed at different parts of the induction motor. The harmonic study is carried out with 3-Phase Normal Inverter Drive and the 3-Phase Diode Clamped Multilevel Inverter (DCMI) drive with 5-Level, the comparison has been done with Normal Inverter Drive and Five Level DCMI drive. The reduction of harmonics is observed using 5-Level DCMI Drive, then the study has been extended experimentally to analyse the temperature of Three Phase Induction Motor. The rate of rise temperature of induction motor is obtained and found to be less than the Normal Inverter Drive, the work has been evaluated by the results presented in this work.

References

[1]. Ahmed, R. A., Mekhilef, S., & Ping, H. W. (2010). New multilevel inverter topology with reduced number of switches. In Proceedings of the 14 International Middle East Power Systems Conference (MEPCON'10) (pp. 19- 21).

[2]. Au, M. T., & Milanovic, J. V. (2007). Planning approaches for the strategic placement of passive harmonic filters in radial distribution networks. IEEE Transactions on Power Delivery, 22(1), 347-353.

[3]. Chandwani, H., Chaudhari, H. N. & Patel, D. (2013), Comparison of Asymmetrical Cascaded Multilevel Inverter Control Techniques. International Journal of Innovations in Engineering and Technology, 2(3), 31-36.

[4]. Das, J. C. (2015). Power System Harmonics and Passive Filter Designs. John Wiley & Sons.

[5]. Deepthi, J., & Saxena, S. N. (2011). Study of variation of THD in a Diode clamped multilevel inverter with respect to modulation index and control strategy. IJCA Proceedings on International and Workshop on Engineering Trends in Technology (ICWET), (12), 37-42.

[6]. Eltamaly, A. M. (2008). A modified harmonics reduction technique for a three-phase controlled converter. IEEE Transactions on Industrial Electronics, 55(3), 1190-1197.

[7]. Etesami, M. H., Farokhnia, N., & Fathi, S. H. (2015). Colonial competitive algorithm development toward harmonic minimization in multilevel inverters. IEEE Transactions on Industrial Informatics, 11(2), 459-466.

[8]. Gautam, S. P., Sahu, L. K., & Gupta, S. (2016). Reduction in number of devices for symmetrical and asymmetrical multilevel inverters. IET Power Electronics, 9(4), 698-709.

[9]. Hasan, K. N. B. M., Rauma, K., Luna, A., Candela, J. I., & Rodríguez, P. (2014). Harmonic compensation analysis in offshore wind power plants using hybrid filters. IEEE Transactions on Industry Applications, 50(3), 2050-2060.

[10]. Jain, K., & Chaturvedi, P. (2012). Matlab-based simulation & analysis of three-level SPWM inverter. International Journal of Soft Computing and Engineering (IJSCE), 2(1), 56-59.

[11]. Jain, S. K., & Singh, S. N. (2011). Harmonics estimation in emerging power system: Key issues and challenges. Electric Power Systems Research, 81(9), 1754-1766.

[12]. Kumar, N., Gupta, S., & Phulambrikar, S. P. (2013). A novel three-Phase Multilevel Inverter using less number of switches. International Journal of Engineering and Advanced Technology (IJEAT), 2(4), 157-160.

[13]. Mindykowski, J., Xiaoyan, X., & Tarasiuk, T. (2013). A new concept of harmonic current detection for shunt active power filters control. Measurement, 46(10), 4334- 4341.

[14]. Mohammadreza, D. (2010). Analysis of different topologies of multilevel inverters (Masters Thesis, Chalmers University of Technology).

[15]. Okrasa, R. (1997). Adjustable Speed Drive - Reference Guide. Toronto: Ontario Hydro.

[16]. R. Parekh (2005). AN995: V/F control of 3-phase induction motors using space vector modulation. Appl. Note AN955, Microchip Technol. Inc. (No. 955, pp. 1-26).

[17]. Rasilo, P., Salem, A., Abdallh, A., De Belie, F., Dupré, L., & Melkebeek, J. A. (2015). Effect of multilevel inverter supply on core losses in magnetic materials and electrical machines. IEEE Transactions on Energy Conversion, 30(2), 736-744.

[18]. Raushan, R., Mahato, B., & Jana, K. C. (2016). Comprehensive analysis of a novel three-phase multilevel inverter with minimum number of switches. IET Power Electronics, 9(8), 1600-1607.

[19]. Rodriguez, J., Lai, J. S., & Peng, F. Z. (2002). Multilevel inverters: A survey of topologies, controls, and applications. IEEE Transactions on Industrial Electronics, 49(4), 724-738.

[20]. Salem, A., Ahmed, E. M., Orabi, M., & Ahmed, M. (2015). New three-phase symmetrical multilevel voltage source inverter. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 5(3), 430-442.

[21]. Su, W. F., Lin, C. E., & Huang, C. L. (1998). Hybrid filter application for power quality improvement. Electric Power Systems Research, 47(3), 165-171.

[22]. Sundaram, E., & Venugopal, M. (2016). On design and implementation of three phase three level shunt active power filter for harmonic reduction using synchronous reference frame theory. International Journal of Electrical Power and Energy Systems, 81, 40- 47.

[23]. Taghizadeh, H., & Hagh, M. T. (2008). Harmonic elimination of multilevel inverters using Particle Swarm Optimization. In Industrial Electronics, 2008. ISIE 2008. IEEE International Symposium on (pp. 393-396). IEEE.

[24]. Thielemans, S., Ruderman, A., & Melkebeek, J. A. (2009). Flying-capacitor multilevel converter voltage balance dynamics for pure resistive load. In Advanced Electromechanical Motion Systems & Electric Drives Joint t h Symposium, 2009. ELECTROMOTION 2009. 8 International Symposium on (pp. 1-6). IEEE.

[25]. Thongprasri, P. (2011). A 5-level three-phase cascaded hybrid multilevel inverter. International Journal of Computer and Electrical Engineering, 3(6), 789-794.

[26]. Tolbert, L. M., Peng, F. Z., & Habetler, T. G. (1998). Multilevel inverters for electric vehicle applications. In Power Electronics in Transportation, 1998 (pp. 79-84). IEEE.

[27]. Umesh, B. S., & Sivakumar, K. (2016). Multilevel inverter scheme for performance improvement of polephase- modulated multiphase induction motor drive. IEEE Transactions on Industrial Electronics, 63(4), 2036-2043.

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Research Paper

Transmission Cost Allocation Using Co-Operative Game Theory Concepts

Smitha M. S. G.* , SatyaRamesh.P.V., Sujatha.P*

Research Scholar, Department of Electrical and Electronics Engineering, Jawaharlal Nehru Technological University, Anantapur, India.

Divisional Engineer, State Load Dispatch Center, Andhra Pradesh Transmission Corporation, India.

Professor, Department of Electrical and Electronics Engineering, JNTUA College of Engineering, Ananthapuramu, India.

Smitha. M.S.G., Ramesh. P. V. S., and Sujatha, P. (2018). Transmission Cost Allocation Using Cooperative Game Theory Concepts. i-manager’s Journal on Electrical Engineering, 11(4), 18-26. https://doi.org/10.26634/jee.11.4.14660

Abstract

Transmission cost allocation is an emerging topic of interest in the deregulated power system. In this paper, co-operative game theory concepts such as Shapley value, Tau value, Nucleolus and Proportional Nucleolus methods are applied for analyzing the allocation of transmission cost among the players. Studies on transmission cost allocation based on Shapley and Nucleolus have been done earlier. The Proportional Nucleolus which works on extended core concept is utilized in the co-operative game for allocating transmission cost to the players and gives solution for co-operative games in the empty-core environment also. The structure of the game and its fairness is also discussed in this paper. The transmission cost allocation based on the co-operative game methods are systematically analyzed and compared with existing tracing methods. The proposed methods are carried out by illustrating on the sample six bus system. The paper emphasis the proportional nucleolus of co-operative game theory is the best suitable method for allocating transmission costs.

References

[1]. Andreoiu, A., Bhattacharya, K., & Canizares, C. (2005). Pricing power system stabilisers using game theory. IEE Proceedings-Generation, Transmission and Distribution, 152(6), 780-786.

[2]. Bai, X., Shahidehpour, S. M., Ramesh, V. C., & Yu, E. (1997). Transmission analysis by Nash game method. IEEE Transactions on Power Systems, 12(3), 1046-1052.

[3]. Contreras, J., & Wu, F. F. (2000). A kernel-oriented algorithm for transmission expansion planning. IEEE Transactions on Power Systems, 15(4), 1434-1440.

[4]. Da Silva, E. L., Morales, J. C., & De Melo, A. C. G. (2001). Allocating congestion cost using game theory. In Power Tech Proceedings, 2001 IEEE Porto (pp. 1-5).

[5]. Ferrero, R. W., Shahidehpour, S. M., & Ramesh, V. C. (1997). Transaction analysis in deregulated power systems using game theory. IEEE Transactions on Power Systems, 12(3), 1340-1347.

[6]. Gomez, J. C. (2003). An extension of the core solution concept (No. 04-01). Discussion papers, Institute of Economics, University of Copenhagen, Denmark.

[7]. Hsieh, S. C., & Wang, H. M. (2002, December). Allocation of transmission losses based on cooperative game theory and current injection models. In Industrial Technology, 2002. IEEE ICIT'02. 2002 IEEE International Conference on (Vol. 2, pp. 850-853). IEEE.

[8]. Lemaire, J. (1984). An application of game theory: cost allocation. ASTIN Bulletin: The Journal of the IAA, 14(1), 61-81.

[9]. Lo, K. L., & Lozano, C. A. (2000). Game theory application for determining wheeling charges. In Electric Utility Deregulation and Restructuring and Power Technologies, 2000. Proceedings. DRPT 2000. International Conference on (pp. 308-313). IEEE.

[10]. Minoia, A., Ernst, D., Dicorato, M., Trovato, M., & Ilic, M. (2006). Reference transmission network: A game theory approach. IEEE Transactions on Power Systems, 21(1), 249-259.

[11]. Papalexopoulos, A., & Obessis, M. (1996). Cost allocation in electric power networks using Cooperative Game Theory. Pacific Gas and Electric Company, San Francisco, California.

[12]. Rathore, P., Agnihotri, G., Khan, B., & Naidu, G. (2014). Transmission usage and cost allocation using Shapley value and tracing method: A comparison. Electrical and Electronics Engineering: An International Journal (ELELIJ), 3, 11-29.

[13]. Ruiz, P. A., & Contreras, J. (2007). An effective transmission network expansion cost allocation based on game theory. IEEE Transactions on Power Systems, 22(1), 136-144.

[14]. Satyaramesh, P. V., & Radhakrishna, C. (2009). Use of Cooperative Game Theory concepts for loss allocation in bilateral electricity markets. International Journal of Power & Energy Systems, 29(4), 272.

[15]. Sore, F., Rudnick, H., & Zolezzi, J. (2006). Definition of an efficient transmission system using cooperative games theory. IEEE Transactions on Power Systems, 21(4), 1484-1492.

[16]. Stamtsis, G. C., & Erlich, I. (2004). Use of cooperative game theory in power system fixed-cost allocation. IEE Proceedings-Generation, Transmission and Distribution, 151(3), 401-406.

[17]. Tsukamoto, Y., & Iyoda, I. (1996). Allocation of fixed transmission cost to wheeling transactions by cooperative game theory. IEEE Transactions on Power Systems, 11(2), 620-629.

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Research Paper

Implementation of Current Control Technique in Grid Connected Solar Photovoltaic Systems for Power Quality Improvement

Ravi Dharavath* , I. Jacob Raglend, CH V. Ganesh*

* Research Scholar, Department of Electrical Engineering, VIT University, Vellore, Tamil Nadu, India.

Professor, School of Electrical Engineering, VIT University, Vellore, Tamil Nadu, India.

* Assistant Professor, Department of Electrical and Electronics Engineering, St. Peter's Engineering College, JNTUH, Telangana, India.

Dharavath, R., Raglend, I. J., and Ganesh, Chv.(2018). Implementation of Current Control Technique in Grid Connected Solar Photovoltaic Systems for Power Quality Improvement. i-manager’s Journal on Electrical Engineering, 11(4), 27-34. https://doi.org/10.26634/jee.11.4.14659

Abstract

In the present scenario, the grid connected renewable energy sources are playing an important role in meeting the peak power demand and providing quality of supply. One of the most favorable renewable energy sources with reasonable cost for producing the power is a solar photovoltaic system, which converts the solar power into the electrical power. The proposed work deals with a detail modeling of Grid connected solar photovoltaic system. The maximum power from the solar photovoltaic system is extracted using incremental conductance methods under dynamic variations in irradiance and temperature. The extracted power is integrated with the grid through the inverter using a hysteresis current control technique with the PI controller. The inverter and controller are used for providing quality of power supply and can meet the necessary peak demand. Under the dynamic irradiance and the temperature variations in the performance of the grid connected solar photovoltaic system is simulated in MATLAB-SIMULINK software.

References

[1]. Chung, Y. H., Kim, H. J., Kim, K. S., Choe, J. W., & Choi, J. (2008). Power quality control center for the microgrid system. In Power and Energy Conference, 2008. PECon nd 2008. IEEE 2 International (pp. 942-947). IEEE.

[2]. Dharavath, R., Raglend, I. J., & Manmohan, A. (2017). Implementation of solar PV-Battery storage with DVR for power quality improvement. In Power and Advanced Computing Technologies (i-PACT), 2017 Innovations in (pp. 1-5). IEEE.

[3]. Electricity Sector in India (n.d). In Wikipedia. Retrieved on June 7 2017 from https://en.wikipedia.org/wiki/ Electricity_sector_in_India#cite_note-capacity-4.

[4]. Kumar, A. N., & Dharavath, R. (2016). Distributed generation integration and power quality improvement of SRM drive under various loading conditions. In Electrical, Electronics, and Optimization Techniques (ICEEOT), International Conference on (pp. 3434-3441). IEEE.

[5]. Liang, X. (2017). Emerging power quality challenges due to integration of renewable energy sources. IEEE Transactions on Industry Applications, 53(2), 855-866.

[6]. Manju, S., & Sagar, N. (2017). Progressing towards the development of sustainable energy: A critical review on the current status, applications, developmental barriers, and prospects of solar photovoltaic systems in India. Renewable and Sustainable Energy Reviews, 70, 298- 313.

[7]. Saravanan, S., & Babu, N. R. (2016). Maximum power point tracking algorithms for photovoltaic system-A review. Renewable and Sustainable Energy Reviews, 57, 192-204.

[8]. Sumathi, S., Kumar, L. A., & Surekha, P. (2015). Solar PV and Wind Energy Conversion Systems: An Introduction to Theory, Modeling with MATLAB/SIMULINK, and the Role of Soft Computing Techniques. Springer.

[9]. Vidyut PRAVAH (n.d). Electricity Price & Availability Highlights.Retrieved on June 92017 from http://vidyutpravah.in/

[10]. Zakzouk, N. E., Elsaharty, M. A., Abdelsalam, A. K., Helal, A. A., & Williams, B. W. (2016). Improved performance low-cost incremental conductance PV MPPT technique. IET Renewable Power Generation, 10(4), 561-574.

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Research Paper

Analysis of Adaptive Linear Neural Network (Adaline) In Power System Harmonics Signal

Pratap Sekhar Puhan* , Sandeep S. D., D. Sutar*

* Professor, Department of Electrical and Electronics Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, India.

Assistant Professor, Department of Electrical and Electronics Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, Telangana, India.

* Assistant Professor, Department of Electrical Engineering, Bhadrak Institute of Engineering and Techgnology, Bhadrak, Odisha, India.

Puhan, P. S., Sandeep, S. D., and Sutar, D. (2018). Analysis of Adaptive Linear Neural Network (Adaline) In Power System Harmonics Signal. i-manager’s Journal on Electrical Engineering, 11(4), 35-42. https://doi.org/10.26634/jee.11.4.14656

Abstract

Estimation of power system parameter plays an important role in the modern power system. In this paper estimation of harmonics components in a power system synthetic signal is done by an improved estimation techniques called as ADALINE. This neural estimator basically uses an adaptive interpreted linear neuron. Learning parameter is adjusted to keep the difference between the Real values and Expected values to satisfy the difference arises due to error equation. Tracking of the fourier co-efficent of the proposed signal, which is also constitutes a noise and DC decaying component can be done easily and accurately using the proposed algorithm. To verify the effectiveness of the proposed algorithm estimation of amplitude as well as Phase of fundamental and harmonics is carried out. The simulation results obtained are encouraging to work more on estimation of signal.

References

[1]. Al-Feilat, E. A. A., El-Amin, I., & Bettayeb, M. (1994). Power system harmonic estimation: A comparative study. Electric Power Systems Research, 29(2), 91-97.

[2]. Bettayeb, M., & Qidwai, U. (2003). A hybrid least squares-GA-based algorithm for harmonic estimation. IEEE Transactions on Power Delivery, 18(2), 377-382.

[3]. Dash, P. K., Swain, D. P., Mishra, B. R., & Rahman, S. (1996, January). Power quality assessment using an adaptive neural network. In Power Electronics, Drives and Energy Systems for Industrial Growth, 1996., Proceedings of the 1996 International Conference on (Vol. 2, pp. 770- 775). IEEE.

[4]. Dash, P. K., Swain, D. P., Routray, A., & Liew, A. C. (1996). Harmonic estimation in a power system using adaptive perceptrons. IEE Proceedings-Generation, Transmission and Distribution, 143(6), 565-574.

[5]. Haykin, S. S. (2008). Adaptive Filter Theory. Pearson Education India.

[6]. Kennedy, K., Lightbody, G., & Yacamini, R. (2003, July). Power system harmonic analysis using the Kalman filter. In Power Engineering Society General Meeting, 2003, IEEE (Vol. 2, pp. 752-757). IEEE.

[7]. Kumar, A., Das, B., & Sharma, J. (2006). Robust dynamic state estimation of power system harmonics. International Journal of Electrical Power & Energy Systems, 28(1), 65-74.

[8]. Liu, S. (1998, October). An adaptive Kalman filter for dynamic estimation of harmonic signals. In Harmonics th and Quality of Power Proceedings, 1998. Proceedings. 8 International Conference on (Vol. 2, pp. 636-640). IEEE.

[9]. Ljung, L. (1999). System Identification-Theory for the nd User, 2 Edition. PTR Prentice-Hall, Upper Saddle River, USA.

[10]. Lobos, T., Kozina, T., & Koglin, H. J. (2001). Power system harmonics estimation using linear least squares method and SVD. IEE Proceedings-Generation, Transmission and Distribution, 148(6), 567-572.

[11]. Mishra, S. (2005). A hybrid least square-fuzzy bacterial foraging strategy for harmonic estimation. IEEE Transactions on Evolutionary Computation, 9(1), 61-73.

[12]. Mori, H., Itou, K., Uematsu, H., & Tsuzuki, S. (1992). An artificial neural-net based method for predicting power system voltage harmonics. IEEE Transactions on Power Delivery, 7(1), 402-409.

[13]. N. R. Watson & J. Arrillaga (2003). Review Harmonics in large systems. Electric Power System Research, 66, 15- 29.

[14]. P. K. Dash & A. Sharaf (1998). Kalman filtering approach for estimation of power system Harmonics. rd Proc. 3 Int. Conf. Harmonics Power System.

[15]. Panda, G., Ray, P. K., & Puhan, P. S. (2014). Harmonic estimation of distorted power system signals employing two hybrid strategies. International Journal of Modelling, Identification and Control, 22(1), 20-32.

[16]. Puhan, P. S., Ray, P. K., & Panda, G. (2015). A comparative analysis of shunt active power filter and hybrid active power filter with different control techniques applied for harmonic elimination in a single phase system. International Journal of Modelling, Identification and Control, 24(1), 19-28.

[17]. Qidwai, U., & Bettayeb, M. (1998). GA based nonlinear harmonic estimation. IEEE Trans. Power Delivery, 18(2), 377-382.

[18]. Ray, P. K., & Subudhi, B. (2015). Neuro-evolutionary approaches to power system harmonics estimation. International Journal of Electrical Power & Energy Systems, 64, 212-220.

[19]. Ray, P. K., Puhan, P. S., & Panda, G. (2015). Improved recursive newton type algorithm based power system frequency estimation. International Journal of Electrical Power & Energy Systems, 65, 231-237.

[20]. Ray, P. K., Puhan, P. S., & Panda, G. (2016). Real time harmonics estimation of distorted power system signal. International Journal of Electrical Power & Energy Systems, 75, 91-98.

[21]. Reddy, V. V. N., Kumar, D. A., & Reddy, K. V. (2015). Fuzzy Back-Propagation Network based controller for Power Quality Improvement using UPQC. i-manager's Journal on Instrumentation & Control Engineering, 3(4), 1- 12.

[22]. Sekaran, E. C. (2006). Comparison of PI and Fuzzy logic control for harmonic reduction in power electronic converters. i-manager's Journal on Future Engineering and Technology, 2(1), 36-41.

[23]. Yadav, S., & Singh, S. (2017). Ant Colony Optimization based shunt active power filter for harmonic compensation. i-manager's Journal on Electrical Engineering, 11(1), 19-26.

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Research Paper

GIS Based Site Suitability Modelling For Locating Solar Power Park In Thiruvannamalai District,Tamil Nadu

R. Reshma* , M. Ramesh, Stephen Jayaseelan*, R. Jaganathan****

* PG Scholar, Department of Geography, University of Madras, Chennai, Tamil Nadu, India.

Chief Technical Officer, National Bureau of Soil Survey and Land Use Planning, Bengaluru, Karnataka, India.

* Research Scholar, Department of Geography, University of Madras, Chennai, Tamil Nadu, India.

**** Professor and Head, Department of Geography, University of Madras, Chennai, Tamil Nadu, India.

Reshma, R., Ramesh, M., Jayaseelan, S., and Jaganathan, R. (2018). GIS Based Site Suitabilty Modelling For Locating Solar Power Park In Thiruvannamalai District,Tamil Nadu. i-manager’s Journal on Electrical Engineering, 11(4), 43-51. https://doi.org/10.26634/jee.11.4.14658

Abstract

Owing to the demand of the electricity consumption across the world, an important trait has been brought to the context by including the solar energy as an alternate source of power generation. The solar energy is termed as the best renewable resource that meets all the needs because of it tremendous benefit. Renewable energy generation can assist countries encounter their sustainable development that aims through delivery of spotless, safe, reliable and inexpensive energy. This paper gives the idea of using the on multiple criteria's decisions and methodology to find optimum sites for planting the solar power park concentrating on numerous other factors. Determining an apposite location that is favourable to all the circumstances such as the economy, environmental and social issues is a tedious task. Hence, considering the problem in account the best solution can be given as using the Geographical Information System (GIS) based model for this analysis. Here, the GIS-based model works with the multi-criteria-analysis for solar site assessment for Thiruvannamalai District, Tamil Nadu. The criteria such as distance from road, availability of barren lands, distance from waterbodies, slope, direction of sun radiation and existing built-up area etc. have been taken into consideration as analysis criteria. The study area extends between 78.20 to 79.50 eastern longitude and 11.55 to 13.15 northern latitude, and covers area of 622059 ha. At last number of maps was prepared to show the selected criteria's and a final output of the selected area which is very much suitable, moderately suitable and less suitable area to plant the solar power park.

References

[1]. Effat, H. A. (2013). Selection of potential sites for solar energy farms in Ismailia Governorate, Egypt using SRTM and Multicriteria analysis. International Journal of Advanced Remote Sensing and GIS, 2(1), 205-220.

[2]. Energy Alternative India, (2011). India solar PV advisor. Retrieved from http://www.eai.in/ref/services/ Preview_of_India_Solar_PV_Advisor.pdf ss

[3]. Kalaiselvan, M., Purushothaman, B. M., Kalaiselvan, M., & Purushothaman, B. M. (2016). GIS based site suitability analysis for establishing a solar power park in Namakkal District, Tamil Nadu. International Journal for Innovative Research in Science & Technology, 2(10), 204- 209.

[4]. Momeni, M., Pemberton, R., & Yang, X. (2012). Statewide analysis for optimized solar farm location. Retrieved from http://web.pdx.edu/~jduh/courses/ geog492w12/Projects/1_5_SolarFarmOregon.pdf

[5]. Mondino, E. B., Fabrizio, E., & Chiabrando, R. (2015). Site selection of large ground-mounted photovoltaic plants: A GIS decision support system and an application to Italy. International Journal of Green Energy, 12(5), 515- 525.

[6]. National Renewable Energy Laboratory. Retrieved from http://www.nrel.gov/

[7]. Noorollahi, E., Fadai, D., Akbarpour Shirazi, M., & Ghodsipour, S. H. (2016). Land suitability analysis for solar farms exploitation using GIS and fuzzy analytic hierarchy process (FAHP) - A case study of Iran. Energies, 9(8), 643.

[8]. Prasad, S. S., kumar, K. D., and Suresh, V. M. (2014). Location of solar power park- Geo-Informatics Approach- A case study of Madurai District, Tamil Nadu, India. African Journal of Geo-Science Research, 2(1), 23-27.

[9]. Sosa, A., McDonnell, K., & Devlin, G. (2015). Analysing performance characteristics of biomass haulage in Ireland for bioenergy markets with GPS, GIS and fuel diagnostic tools. Energies, 8(10), 12004-12019.

[10]. Tamil Nadu Global Investors Meet. (2015). Thiruvannamalai District Profile. Retrieved from http://www.tndipr.gov.in/pdf/Global%20Investors%20Me et%20(English)%20Inner%20pages.pdf

[11]. Thiruvannamalai District Collector Office. (2016). Thiruvannamalai District Statistical Handbook.

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Research Paper

Hybrid Technique based Slip frequency control for the Dynamic Analysis of IM

Hemant Sahebrao Kulat* , Anupama Pushkar Huddar**

* Research Scholar, Department of Electrical and Electronics Engineering, Chhattisgarh Swami Vivekanand Technical University, Bhilai, Chhattisgarh, India.

** Professor and Head, Department of Electrical Engineering, Bhilai Institute of Technology, Durg, Chhattisgarh, India.

Kulat and H. S., and Huddar, A. P. (2018). Hybrid Technique based Slip frequency control for the Dynamic Analysis of IM. i-manager’s Journal on Electrical Engineering, 11(4), 52-65. https://doi.org/10.26634/jee.11.4.14654

Abstract

In the paper, the slip frequency control of Induction Motor (IM) is analyzed and developed the control loop with the help of hybrid technique. The hybrid technique is the combination of Adaptive Neuro Fuzzy Inference System (ANFIS) and Firefly Algorithm (FA), which is works based on the Phase Locked Loop (PLL). Here, the FA is developed to train the ANFIS and established the rule based layer formation. The bio-inspired optimization technique of FA is applied to develop the performance of ANFIS by tuning the membership function and reduce the error value. After that, the ANFIS is designed and this is suggested for the enhancement of stability and controlling the speed, torque and slip frequency. In the controller part of analysis, the IM behaviors are determined normally. After that, the error speed signal is calculated, and established on the comparison of reference and motor speed. The resulted error and change in error speed signals are used to the input of the proposed hybrid controller loop. The speed characteristics of IM is analyzed with the help of proposed technique. The proposed method is implemented in MATLAB/Simulink platform and compared with the existing methods such as, ANFIS and Particle Swarm Optimization (PSO) algorithm. In order to prove the effectiveness of the proposed method, the characteristics of speed, torque, slip frequency and current are evaluated.

References

[1]. Abdel-Khalik, A. S., & Gadoue, S. M. (2011). Improved flux pattern by third harmonic injection for multiphase induction machines using neural network. Alexandria Engineering Journal, 50(2), 163-169.

[2]. Achour, T., Debbou, M., & Pietrzak-David, M. (2015). Control strategy of a dual induction motor: Anti-slip control application. Control Engineering Practice, 36, 58- 71.

[3]. Ali, J. A., Hannan, M. A., Mohamed, A., & Abdolrasol, M. G. (2016). Fuzzy logic speed controller optimization approach for induction motor drive using backtracking search algorithm. Measurement, 78, 49-62.

[4]. Alsofyani, I. M., & Idris, N. R. N. (2013). A review on sensorless techniques for sustainable reliablity and efficient variable frequency drives of induction motors. Renewable and Sustainable Energy Reviews, 24, 111- 121.

[5]. Amezquita-Brooks, L., Liceaga-Castro, E., & Liceaga- Castro, J. (2014). Novel design model for the stator currents subsystem of induction motors. Applied Mathematical Modelling, 38(23), 5623-5634.

[6]. Bensiali, N., Etien, E., & Benalia, N. (2015). Convergence analysis of back-EMF MRAS observers used in sensorless control of induction motor drives. Mathematics and Computers in Simulation, 115, 12-23.

[7]. Cao, M., & Yin, P. (2014). Modeling and simulation of vector slip frequency control system of induction motor. In Advanced Materials Research (Vol. 951, pp. 76-79). Trans Tech Publications.

[8]. Cavallo, A., De Maria, G., Natale, C., & Pirozzi, S. (2014). Slipping detection and avoidance based on Kalman filter. Mechatronics, 24(5), 489-499.

[9]. Jiangming, D., Tefang, C., Jianxiang, T., & Chunyang, C. (2015). Variable slip-frequency strategy for reducing non-equal deviations output by paralleled single-sided linear induction motors. IET Science, Measurement & Technology, 9(6), 734-743.

[10]. Kobayashi, N., Wijaya, F. P., Kondo, K., & Yamazaki, O. (2016). Induction motor speed-sensorless vector control using mechanical simulator and disturbance torque compensation. IEEE Transactions on Industry Applications, 52(3), 2323-2331.

[11]. Kumar, N., Chelliah, T. R., & Srivastava, S. P. (2015). Adaptive control schemes for improving dynamic performance of efficiency-optimized induction motor drives. ISA Transactions, 57, 301-310.

[12]. Kumar, T. V., & Rao, S. S. (2010, December). Direct torque control method for induction motor drives based on modified amplitude and angle decoupled control of stator flux. In Power Electronics, Drives and Energy Systems (PEDES) & 2010 Power India, 2010 Joint International Conference on (pp. 1-6). IEEE.

[13]. Lamim Filho, P. C. M., Pederiva, R., & Brito, J. N. (2014). Detection of stator winding faults in induction machines using flux and vibration analysis. Mechanical Systems and Signal Processing, 42(1-2), 377-387.

[14]. Lascu, C., Jafarzadeh, S., Fadali, M. S., & Blaabjerg, F. (2017). Direct torque control with feedback linearization for induction motor drives. IEEE Transactions on Power Electronics, 32(3), 2072-2080.

[15]. Lima, F., Kaiser, W., da Silva, I. N., & de Oliveira Jr, A. A. (2014). Open-loop neuro-fuzzy speed estimator applied to vector and scalar induction motor drives. Applied Soft Computing, 21, 469-480.

[16]. Lopez, V. G., Alanis, A. Y., Sanchez, E. N., & Rivera, J. (2015). Real-time implementation of neural optimal control and state estimation for a linear induction motor. Neurocomputing, 152, 403-412.

[17]. Marcetic, D. P., Krcmar, I. R., Gecic, M. A., & Matic, P. R. (2014). Discrete rotor flux and speed estimators for highspeed shaft-sensorless IM drives. IEEE Transactions on Industrial Electronics, 61(6), 3099-3108.

[18]. Mengoni, M., Zarri, L., Tani, A., Parsa, L., Serra, G., &Casadei, D. (2015). High-torque-density control of multiphase induction motor drives operating over a wide speed range. IEEE Transactions on Industrial Electronics, 62(2), 814-825. .

[19]. Mishra, R. N., & Mohanty, K. B. (2016). Real time implementation of an ANFIS-based induction motor drive v i a f e e d b a c k l i n e a r i z a t i o n f o r p e r f o r m a n c e enhancement. Engineering Science and Technology, an International Journal, 19(4), 1714-1730

[20]. Sarhan, H., Issa, R., Alia, M., & Assbeihat, J. M. (2011). Slip compensation in efficiency-optimized threephase induction motor drive systems. Intelligent Control and Automation, 2(2), 95-99.

[21]. Sun, W., Liu, X., Gao, J., Yu, Y., Wang, G., & Xu, D. (2016). Zero stator current frequency operation of speedsensorless induction motor drives using stator input voltage error for speed estimation. IEEE Transactions on Industrial Electronics, 63(3), 1490-1498.

[22]. Sutikno, T., Idris, N. R. N., & Jidin, A. (2014). A review of direct torque control of induction motors for sustainable reliability and energy efficient drives. Renewable and Sustainable Energy Reviews, 32, 548-558.

[23]. Talhaoui, H., Menacer, A., Kessal, A., & Kechida, R. (2014). Fast Fourier and discrete wavelet transforms applied to sensorless vector control induction motor for rotor bar faults diagnosis. ISA Transactions, 53(5), 1639- 1649.

[24]. Tir, Z., Malik, O. P., & Eltamaly, A. M. (2016). Fuzzy logic based speed control of indirect field oriented controlled Double Star Induction Motors connected in parallel to a single six-phase inverter supply. Electric Power Systems Research, 134, 126-133.

[25]. Traoré, D., De Leon, J., & Glumineau, A. (2010). Sensorless induction motor adaptive obser verbackstepping controller: Experimental robustness tests on low frequencies benchmark. IET Control Theory & Applications, 4(10), 1989-2002.

[26]. Verma, A., Sarangi, S., & Kolekar, M. H. (2014). Stator winding fault prediction of induction motors using multiscale entropy and grey fuzzy optimization methods. Computers & Electrical Engineering, 40(7), 2246-2258.

[27]. Yan, J., Wang, X., Deng, Z., & Qixing, L. (2014, August). Slip frequency correction based on torque observer for induction machine indirect vector control system. In Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014 IEEE Conference and Expo (pp. 1-4). IEEE.

[28]. Yang, X. S., Hosseini, S. S. S., & Gandomi, A. H. (2012). Firefly algorithm for solving non-convex economic dispatch problems with valve loading effect. Applied Soft Computing, 12(3), 1180-1186.

[29]. Yu, J., Chen, B., & Yu, H. (2010). Position tracking control of induction motors via adaptive fuzzy backstepping. Energy Conversion and Management, 51(11), 2345-2352.

[30]. Zaafouri, A., Regaya, C. B., Azza, H. B., & Châari, A. (2016). DSP-based adaptive backstepping using the tracking errors for high-performance sensorless speed control of induction motor drive. ISA Transactions, 60, 333- 347.

[31]. Zorgani, Y. A., Koubaa, Y., & Boussak, M. (2016). MRAS state estimator for speed sensorless ISFOC induction motor drives with Luenberger load torque estimation. ISA Transactions, 61, 308-317.

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Research Paper

Effects of Voltage Crest Factor in Rapid Start Lamps with HPF

Aniruddha Mukherjee* , M. K. Gupta**

* Research Scholar, Department of Electrical and Electronics Engineering, Suresh Gyan Vihar University, Jaipur, Rajasthan, India.

** Professor, Department of Electrical and Electronics Engineering, Suresh Gyan Vihar University, Jaipur, Rajasthan, India.

Mukherjee, A., and Gupta, M. K. (2018). Effects Of Voltage Crest Factor In Rapid Start Lamps With HPF. i-manager’s Journal on Electrical Engineering, 11(4), 66-71. https://doi.org/10.26634/jee.11.4.14423

Abstract

The aspect of lamp expectancy for compact fluorescent lamps (CFL) has already been explored by many lighting engineers. It is also well understood that there several parameters that are always influencing the life and performance of CFLs. The parameter such as lamp current crest factor happens to be a pivotal piece of information in connection with lamp life. It has been observed experimentally that the range of lamp current crest factor should be 1.9 to 2.1 for CFLs. Thus implying a reliable heating of the lamp electrodes without any damage. In most of the high power factor (HPF) lamps it has been observed that the lamp current crest factor is within the prescribed limit. But however if the electrode heating is not sufficient it will result in sputtering of the electrode coating and if it more than sufficient evaporation will occur. In both the cases the lamp electrodes are prone to damage. It has been observed that the lamp starting voltage is an important parameter that governs the necessary and sufficient heating of the lamp electrodes. In this paper explores the impact of high power factor (HPF) circuit on the life of self-ballasted lamps by analyzing the lamp voltage crest factor. The experiment carried out on different types of 18W lamps data for lamp voltage crest factor has been collected. The research work done in this paper provides information about the lamp voltage crest factor with corresponding change in electrode temperature. The lamps used in this paper are put to accelerated test with 5 minutes on and 5 minutes off cycle. The lamps with improved circuit is compared with the other types. The lamp voltage responsible for preheating is finally considered while regulating voltage crest factor using IR215X IC for the lamp ballast. The degradation of lamp life is observed physically. The data is plotted in MATLAB and analyzed. An empirical relation has been derived from the curve fitting tool with the set of results obtained. This work serves an important aspect of HPF circuitry as it explores an ingenious parameter influencing the life of CFLs

References

[1]. Chondrakis, N. G., & Topalis, F. V. (2009). Starting characteristics of fluorescent tubes and compact fluorescent lamps operating with electronic ballasts. Measurement, 42(1), 78-86.

[2]. Hadrath, S. (2007). On electrode erosion in fluorescent lamps during instant start (Doctoral Dissertation, Universitätsbibliothek).

[3]. Ji, Y., & Davis, R. (1996, October). Reducing the uncertainty in fluorescent lamp/ballast system compatibility. In Industry Applications Conference, 1996. Thirty-First IAS Annual Meeting, IAS'96., Conference Record of the 1996 IEEE (Vol. 4, pp. 2189-2193). IEEE.

[4]. Ji, Y., Davis, R., O'Rourke, C., & Chui, E. W. M. (1999). Compatibility testing of fluorescent lamp and ballast systems. IEEE Transactions on Industry Applications, 35(6), 1271-1276.

[5]. Kheraluwala, M. H., & El-Hamamsy, S. A. (1995, June). Modified valley-fill high power factor electronic ballast for compact fluorescent lamps. In Power Electronics th Specialists Conference, 1995. PESC'95 Record., 26 Annual IEEE (Vol. 1, pp. 10-14). IEEE.

[6]. Lam, J. C., Pan, S., & Jain, P. K. (2014). A single-switch valley-fill power-factor-corrected electronic ballast for compact fluorescent lightings with improved lamp current crest factor. IEEE Transactions on Industrial Electronics, 61(9), 4654-4664.

[7]. Lam, J., & Jain, P. K. (2012, October). A simple single switch electronic ballast for compact fluorescent lamps with passive power factor correction (PFC) and soft th switching capability. In IECON 2012-38 Annual Conference on IEEE Industrial Electronics Society (pp. 4503-4508). IEEE.

[8]. Mukherjee, A., & Soni, A. (2015, February). Effect of power factor improvement on switching life of self ballasted fluorescent lamps. In Signal Processing, Informatics, Communication and Energy Systems (SPICES), 2015 IEEE International Conference on (pp. 1-4). IEEE.

[9]. Mukherjee, A., Mandal, R. S., Sur, A. K., & Mazumdar, S. (2010). Power factor and harmonic analysis of self ballasted compact Fluorescent Lamps. Light & Engineering, 18(1), 101-107.

[10]. National Lighting Product Information Program. (2000). Specifier Reports on Electronic Ballasts, 8(1). Retrieved from http://www.lrc.rpi.edu/programs/NLPIP/ PDF/VIEW/SREB2.pdf

[11]. O'Rourke, C., & Figueiro, M. G. (2001). Long-term performance of screwbase compact fluorescent lamps. Journal of the Illuminating Engineering Society, 30(2), 30- 39.

[12]. Rosillo, F. G., Chivelet, N. M., & Aguilera, M. E. (2009, November). Effects of electronic ballasts in fluorescent lamp lifetime. In Industrial Electronics, 2009. IECON'09. th 35 Annual Conference of IEEE (pp. 3512-3517). IEEE.

[13]. Verderber, R. R., Morse, O. C., & Alling, W. R. (1993). Harmonics from compact fluorescent lamps. IEEE Transactions on Industry Applications, 29(3), 670-674.

[14]. Wood, P. N. (1998, October). Flourescent ballast design using passive PFC and crest factor control. In Industry Applications Conference, 1998. Thirty-Third IAS Annual Meeting. The 1998 IEEE (Vol. 3, pp. 2076-2081). IEEE.

[15]. Yamagata, Y., Kai, M., Naito, S., Tomita, K., Uchino, K., & Manabe, Y. (2010). Relationship between Ba atom emission and electrode temperature in a low-pressure fluorescent lamp. Thin Solid Films, 518(13), 3449-3452.

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

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Volume 11 Issue 4 April - June 2018

Aya Amer* , Nehaja Joglekar**, Tassneem Zamzam***, Atif Iqbal****

*-*** UG Scholar, Department of Electrical Engineering, Qatar University, Doha, Qatar. **** Associate Professor, Department of Electrical Engineering, Qatar University, Doha, Qatar.

Amer, A., Joglekar, N., Zamzam, T., and Iqbal, A. (2018). Design and Implementation of Solar PV Emulator Using Magna DC Power Supply. i-manager’s Journal on Electrical Engineering, 11(4), 1-8. https://doi.org/10.26634/jee.11.4.14652

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Manjesh*

Associate Professor, Department of Electronic Science, Bangalore University, Bengaluru, Karnataka, India.

Manjesh (2018). Comparison of Harmonics, THD and Temperature Analysis of 3-Phase Induction Motor with Normal Inverter Drive and 5-Level DCMI Drive. i-manager’s Journal on Electrical Engineering, 11(4), 9-17. https://doi.org/10.26634/jee.11.4.14655

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Smitha M. S. G.* , SatyaRamesh.P.V.**, Sujatha.P***

Smitha. M.S.G., Ramesh. P. V. S., and Sujatha, P. (2018). Transmission Cost Allocation Using Cooperative Game Theory Concepts. i-manager’s Journal on Electrical Engineering, 11(4), 18-26. https://doi.org/10.26634/jee.11.4.14660

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Ravi Dharavath* , I. Jacob Raglend**, CH V. Ganesh***

Dharavath, R., Raglend, I. J., and Ganesh, Chv.(2018). Implementation of Current Control Technique in Grid Connected Solar Photovoltaic Systems for Power Quality Improvement. i-manager’s Journal on Electrical Engineering, 11(4), 27-34. https://doi.org/10.26634/jee.11.4.14659

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Pratap Sekhar Puhan* , Sandeep S. D.**, D. Sutar***

Puhan, P. S., Sandeep, S. D., and Sutar, D. (2018). Analysis of Adaptive Linear Neural Network (Adaline) In Power System Harmonics Signal. i-manager’s Journal on Electrical Engineering, 11(4), 35-42. https://doi.org/10.26634/jee.11.4.14656

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R. Reshma* , M. Ramesh**, Stephen Jayaseelan***, R. Jaganathan****

Reshma, R., Ramesh, M., Jayaseelan, S., and Jaganathan, R. (2018). GIS Based Site Suitabilty Modelling For Locating Solar Power Park In Thiruvannamalai District,Tamil Nadu. i-manager’s Journal on Electrical Engineering, 11(4), 43-51. https://doi.org/10.26634/jee.11.4.14658

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Hemant Sahebrao Kulat* , Anupama Pushkar Huddar**

* Research Scholar, Department of Electrical and Electronics Engineering, Chhattisgarh Swami Vivekanand Technical University, Bhilai, Chhattisgarh, India. ** Professor and Head, Department of Electrical Engineering, Bhilai Institute of Technology, Durg, Chhattisgarh, India.

Kulat and H. S., and Huddar, A. P. (2018). Hybrid Technique based Slip frequency control for the Dynamic Analysis of IM. i-manager’s Journal on Electrical Engineering, 11(4), 52-65. https://doi.org/10.26634/jee.11.4.14654

Abstract

References

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Aniruddha Mukherjee* , M. K. Gupta**

* Research Scholar, Department of Electrical and Electronics Engineering, Suresh Gyan Vihar University, Jaipur, Rajasthan, India. ** Professor, Department of Electrical and Electronics Engineering, Suresh Gyan Vihar University, Jaipur, Rajasthan, India.

Mukherjee, A., and Gupta, M. K. (2018). Effects Of Voltage Crest Factor In Rapid Start Lamps With HPF. i-manager’s Journal on Electrical Engineering, 11(4), 66-71. https://doi.org/10.26634/jee.11.4.14423

Abstract

References

Full Article (HTML)

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Aya Amer* , Nehaja Joglekar, Tassneem Zamzam*, Atif Iqbal****

- UG Scholar, Department of Electrical Engineering, Qatar University, Doha, Qatar.

** Associate Professor, Department of Electrical Engineering, Qatar University, Doha, Qatar.

Smitha M. S. G.* , SatyaRamesh.P.V., Sujatha.P*

Ravi Dharavath* , I. Jacob Raglend, CH V. Ganesh*

Pratap Sekhar Puhan* , Sandeep S. D., D. Sutar*

R. Reshma* , M. Ramesh, Stephen Jayaseelan*, R. Jaganathan****

* Research Scholar, Department of Electrical and Electronics Engineering, Chhattisgarh Swami Vivekanand Technical University, Bhilai, Chhattisgarh, India.

** Professor and Head, Department of Electrical Engineering, Bhilai Institute of Technology, Durg, Chhattisgarh, India.

* Research Scholar, Department of Electrical and Electronics Engineering, Suresh Gyan Vihar University, Jaipur, Rajasthan, India.

** Professor, Department of Electrical and Electronics Engineering, Suresh Gyan Vihar University, Jaipur, Rajasthan, India.