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

Current Issue Vol. 17 Issue 4

Design and Analysis of Improved Mountain Gazelle Optimization Tuned PID and FOPID Controllers for PV MPPT System
Performance Analysis of Power System Dynamics with Facts Controllers: Optimal Placement and Impact of SSSC and STATCOM
Empowering Hybrid EVS with Bidirectional DC - DC Converter for Seamless V2G and G2V Integration
Solar Wireless Charging of Battery in Electrical Vehicle
Advancements in Multilevel Inverter Technologies for Photovoltaic-Z-Source Based EV Applications: A Comprehensive Analysis and Future Directions

Most Cited

Volume 8 Issue 1 July - September 2014

Article

Looking beyond a Future without Fossil Fuel

Vijula Suresh*

PG Teacher, Sacred Heart Matriculation Higher Secondary School, Church Park, Chennai, Tamil Nadu.

Suresh, V. (2014). Looking Beyond a Future Without Fossil Fuel. i-manager’s Journal on Electrical Engineering, 8(1), 1-10. https://doi.org/10.26634/jee.8.1.2993

Abstract

Depleting Natural Energy resources with its huge environmental hazards has forced scientists to search for a perfect alternative energy that can substitute this conventional power sources like Coal and Petrol. Although alternative fuels have certain disadvantages, in the near future, they will emerge as a force to reckon with, in meeting the world's energy shortage and thus replacing oil and gas. This paper deals with different sources of energy like Bio ,Solar, Wind, Nuclear, Hydrogen, Algae, Silk and Human energy. The paper also examines the benefits, the setbacks and cost effectiveness of all these forms of energy, the countries involved in making and the effect of the alternated fuels which are reducing our carbon footprint and arresting climate change.

References

[1]. Chennai consumes 20 of the power retrieved from http://www.thehindu.com/news/cities/chennai/chennaic onsumes-20-of-the-power-of-the- state/article5934753.ece

[2]. http://www.greenbang.com/how-much-coal-isleft_ 21367.html

[3]. http://en.wikipedia.org/wiki/Ethanol_fuel

[4]. Sukhatme, (2008). Solar Energy – Principles of Thermal Collection and Storage.

[5]. Abbasi, S. A. & NaseemaAbbasi. (2010). Renewable Energy Sources and their Environmental Impact, pp 26- 54.

[6]. ZacharayShahan, (2013), Top wind power countries in the world retrieved from http://cleantechnica.com/ 2013/06/20/top-wind-power-countries-in-the-world-percapita- per-gdp-in-total

[7]. http://en.wikipedia.org/wiki/Nuclear_power

[8]. http://www.nei.org/Knowledge-Center/Nuclear- Statistics/World-Statistics/Top-10-Nuclear-Generating- Countries

[9]. Rebecca L. Busby, (2005), Hydrogen and Fuel Cells, pp 1-18.

[10] . http://auto.howstuffworks.com/fuel- efficiency/biofuels/5-ways-use-algae-fuel.htm#page=1

[11]. Carin Hall, (2012), Armed with Algae, retrieved fromhttp://www.energydigital.com/renewables/3133/ Armed-with-Algae

[12]. Silk to energy retrieved from http://www.thehindu. com/todays-paper/tp-features/tp-metroplus/silk-toenergy/ article6214616.ece

[13]. David Hayes, (2011). A Study into the Harvesting of Energy from the Movement of Pedestrians.

[14]. Sciill Staff, (2009). Popular Science Harvesting Energy from Humans.

[15]. http://www.thegreenmicrogym.com/ electricitygenerating- equipment/

[16]. Mukesh Kumar Bhimwal, K. M. Gangotri, (2012). Photochemical Conversion of Solar Energy into Electrical Energy in an Eosin–Mannose System, Arabian Journal for Science and Engineering, January Volume 37, Issue 1, pp 19-26.

[17]. James R. Bolton, (1979). Solar Energy Conversion in Photosynthesis — Features Relevant to Artificial Systems for the Photochemical Conversion of Solar Energy, Solar Energy (Contemporary Issues in Science and Society), pp 31-50.

[18]. Electricity from Silkworm Cocoons, Energy Harvesting Journal, Sept.

[19]. Renewable Energy, (2014). Australian Government Renewal Energy, 2014.

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Research Paper

Modelling and Detection of Bearing Fault in PWM Inverter Fed Induction Motor Drives

Khadim Moin Siddiqui* , Kuldeep Sahay, V. K. Giri*

- Electrical Engineering Department, Institute of Engineering & Technology, Lucknow, India.

Electrical Engineering Department, Madan Mohan Malaviya University of Technology, Gorakhpur, India.

Siddiqui, K. M., Sahay, K. and Giri, V. K. (2014). Modelling and Detection of Bearing Fault in PWM Inverter Fed Induction Motor Drives. i-manager’s Journal on Electrical Engineering, 8(1), 11-24. https://doi.org/10.26634/jee.8.1.2995

Abstract

Induction Motor (IM) with electronic inverters presents greater advantages on cost and energy efficiency as compared with other industrial solutions for varying speed applications. These inverter fed-motors are recently gathering great recognition for Multi-Megawatt industrial drive applications. In this paper, a dynamic simulation model of PWM inverter fed IM has been presented and analyzed. The model has been developed in the recent MATLAB/Simulink environment to analyze the transient behaviour of IM in healthy and faulty condition of bearing. The dynamic simulation of IM is one of the key steps in the validation of the design process of the motor-drive system. It is extremely needed with the priority for eliminating the probable faults beforehand due to inadvertent design mistakes and changes during the operation. The model gives encouraging results with reduced harmonics[1]. In the present work, a successful diagnosis of bearing faults of an IM in transient condition has been carried out. Therefore, an early detection of bearing fault is possible by this model and may avoid the motor to reach in the catastrophic conditions. Consequently, this technique may save millions of dollars for industries. Further, the time domain analysis has been carried out for bearing fault detection purpose.

References

[1]. Khadim Moin Siddiqui, Kuldeep Sahay and V.K. Giri (2014). Simulation and Transient Analysis Of Pwm Inverter Fed Squirrel Cage Induction Motor Drives. i-manager's Journal on Electrical Engineering. 7(3), Jan-Mar, 2014, Print ISSN 0973-8835, E-ISSN 2230-7176, pp. 9-19.

[2]. Nandi, S., & Toliyat, H.A., (1999). “Condition Monitoring and Fault Diagnosis of electrical Machine”, In Proc. IEEE IAS Annual Meeting, Vol.1, pp.197-204.

[3]. Benbouzid, M.E.H., & Kliman, G.B., (2003). “What Stator Current Processing-Based Technique to use for Induction Motor Faults Diagnosis?”, IEEE trans. Energy Conversion, Vol.18(2), pp.238-244.

[4]. S c h o e n , R . , . H a b e t l e r, T. , K a m r a n , F. , & Bartheld,(1995). “R., Motor Bearing Damage Detection using Stator Current Monitoring”, IEEE trans. Ind. Applicat., Vol.31(6), pp.1274-1279.

[5]. IEEE Motor Reliability Working Group (1985), “Report Large Motor Reliability Survey in Industrial and Commercial Installations”, IEEE Trans. Ind. Applicat., Vol.31(6), pp.853-872.

[6]. BlÖdt, M., Granjon, P., Raison, B., & Rostaing, G., (2004). “Models for Bearing Damage Detection in Induction Motors Using Stator Current Monitoring”, IEEE International Symposium on Industrial Electronics, Vol.1, pp.383-388.

[7]. Siddiqui, K.M., & Giri, V.K., (2012). “Broken Rotor Bar Fault Detection in Induction Motors using Wavelet Transform”, Int. Conf. Proc., IEEE, Computing, Electronics and Electrical Technologies [ICCEET], Chennai, India, pp.1-6.

[8]. Ayaz, E., (2006). Continuous Wavelet Transform for Bearing Damage Detection in Electric Motors, IEEE MELECON, Benalmadena (Malaga), Spain, pp.16-19.

[9]. Siddiqui, K.M., Sahay, K. & Giri, V.K., (2014). Health Monitoring and Fault Diagnosis in Induction Motor- A Review, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol.3(1), pp.6549-6565.

[10]. Niaoqing, H., Zhang, Y., Fengshou, G., Guojun, Q., & Andrew B., (2008). “Early, Fault Detection Using a Novel Spectrum Enhancement Method for Motor Current th Signature Analysis”, 7 WSEAS Int. Conf. on Artificial Intelligence Knowledge Engineering and Data Bases (AIKED'08), University of Cambridge UK, pp.470-475.

[11]. Jung, J.H., Jong, J.L., & Bong, H. K.,(2006). “Online Diagnosis of Induction Motors Using MCSA”, IEEE Trans. on Industrial Electronics, Vol.53, pp.1842-1852.

[12]. Watson, J.F., & Elder, S., (1989). Fault Detection in Induction Motors as a Result of Transient Analysis, In Proc. th 4 . Conf. Electrical Machines and Drives, pp.182-186.

[13]. Thomson, W.T., & Fenger, M., (2001). Current Signature Analysis to Detect Induction Motor Faults, IEEE Industry Applications Magazine, Vol.7, pp.26-34.

[14]. Singhal, A., Khandekar, M. A., (2013). Bearing Fault Detection in Induction Motor Using Fast Fourier Transform, IEEE Int. Conf. on Advanced Research in Engineering & Technology, India.

[15]. Wade, S., Dunnigan, M. W., & Wil, B. W., (1997). Induction Machine Vector Control with Rotor Resistance Identification, IEEE Transactions on Power Electronics, Vol.12(3), pp.495–506.

[16]. Krause, P.C., & Thomas, C. H., (1965). “Simulation of Symmetrical Induction Machinery”, IEEE Trans. on Power apparatus and Systems, Vol.84, pp.1038-1053.

[17]. Ozelgin, I.,(2008). “Analysis of magnetic flux density for airgap eccentricity and bearing faults” International Journal of Systems Applications, Engineering & Development, Vol 2(4).

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Research Paper

Reduced Rule FLC for Sensorless Control of Induction Motor Drive

Mohammad Haseeb Khan* , Arshia Azam**

* Professor, Electrical and Electronics Department, Muffakham Jah College of Engineering and Technology, Hyderabad, Telangana, India.

** Professor, Electronics and Communication Department, Muffakham Jah College of Engineering and Technology, Hyderabad, Telangana, India.

Khan, M. H., and Azam, A. (2014). Reduced Rule FLC for Sensorless Control of Induction Motor Drive. i-manager’s Journal on Electrical Engineering , 8(1), 25-30. https://doi.org/10.26634/jee.8.1.2996

Abstract

This paper presents a novel method of reducing fuzzy rules present in a fuzzy logic controller. The proposed Reduced Rule Fuzzy Logic Controller (RRFLC) is used in Model Referencing Adaptive System (MRAS) based sensorless control of induction motor drive. To improve the performance of any fuzzy logic controller, it is required to increase the number of rules present in the rule base of FLC. This increases the computational memory and computational time required for processing, there by slowing down the response of the process or plant under control, induction motor in the present case. Hence, in this paper, a novel method of reducing rules using Equilibrium value is proposed in which the number of rules are reduced from 49 to 16 and at the same time the performance of the induction motor remains similar to that of large rules with a reduction of speed of induction motor by 2 rpm. Simulations results are presented and analyzed to show the effectiveness of the proposed method.

References

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[8]. Arshia Azam, J. Amarnath and Ch. D. V. Paradesi Rao,(2009). “Auto Regressive Tree Modeling for Parametric Optimization in Fuzzy Logic Control System, ”Proceedings of World Academy of Science, Engineering and Technology PWASET, Vol. 37, January pp 235-239.

[9]. Zeng, Xiao- Jun, Singh, Madan G., (1994). “Approximation Theory of Fuzzy Systems-SISO Case,” IEEE Trans. on Fuzzy Systems, Vol. 2, No. 2, pp. 162-194.

[10]. Zeng, Xiao-Jun, Singh, Madan G., (1995). “Approximation Theory of Fuzzy Systems-MIMO Case,” IEEE Trans. on Fuzzy Systems, Vol. 3, No.2, pp. 219-235.

[11]. Rakesh K. Arya, R. Mitra and Vijay Kumar, (2004). “Approximations of large rule Takagi-Sugeno fuzzy controller by four rule Takagi-Sugeno fuzzy controller,” Proc. of IEEE conference on Cybernetics and Intelligent Systems CIS-04, Vol. 3, 1-3 Dec, Singapore, pp. 1340- 1345.

[12]. Rakesh K. Arya, R. Mitra and Vijay Kumar, (2005). “A new Robust fuzzy controller for Nonlinear and large dead time systems,” IEICE Trans. on Fundamentals/Special sections on nonlinear analysis and applications,” Vol. E- 88-A, No. 10, Oct, 2527-2534.

[13]. Rakesh K. Arya, R. Mitra and Vijay Kumar, (2004). “Approximations of large rule fuzzy controller by simplest fuzzy controller,” Proc. of IEEE International Conference on Fuzzy System, FUZZ-04, Vol. 3, Hungary, Budapest, pp. 1239-1244.

[14]. Gadoue, S.M. Giaouris, D. Findch J.W. (2009). “Sensorless control of Induction Motor drives at very low and zero speeds using Neural Network Flux observer”, IEEE Trans. On Industrial Electronics, Vol. 56 No. 8, Aug, pp 3029-3039.

[15]. Gadoue, S.M. Giaouris, D. Findch J.W. (2010). “MRAS sensorless vector control of an Induction motor using new sliding – mode and fuzzy logic adaptation mechanisms”, IEEE Trans. on Energy Conversion, Vol. 25, No. 2, June, pp 394-102.

[16]. Gadoue, S.M. Giaouris, D. Findch J.W., (2008). “A neural network based stator current MRAS observer for speed sensorless induction motor drives” IEEE International symposium on Industrial Electronics, ISIE 2008, June/July, pp 650-655.

[17]. Arshia Azam, Md. Haseeb Khan, (2013). “Reduced rule fuzzy logic controller for performance improvement of process control,” Proc. of 2013 IEEE International conference on Information and communication Technologies (ICT 2013), April, India, pp 853-857.

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Research Paper

Voltage Sag/Swell Compensation Using Dynamic Voltage Restorer Based on Super Capacitor

K. Venkateswarlu* , B. Ashwin Kumar, E. Venkatesh*

*-*** Assistant Professor, Department of EEE, Sri Indu College of Engineering & Technology, Hyderabad, India

Venkateswarlu, K., Kumar, B. A., and Venkatesh, E. (2014). Voltage Sag/Swell Compensation Using Dynamic Voltage Restorer Based on Super Capacitor. i-manager’s Journal on Electrical Engineering , 8(1), 31-38. https://doi.org/10.26634/jee.8.1.2997

Abstract

To mitigate disturbances at the load end, one of the custom power devices such as Dynamic Voltage Restorer (DVR) with super capacitor is used. The super capacitor as an energy storage is to supply real power to the inverter during the disturbances. The operation of the DVR depends on the control strategy. The control strategy used in this paper is SRF theory and Proportional Integral (PI) controller technique is applied to the DVR. The performances of DVR with and without capacitor are evaluated. The simulations are carried out using MATLAB/SIMULINK software.

References

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[2]. Omar Rosli, Rahim NA, (2010), “Mitigation of voltage swells disturbances in low voltage distribution system using dynamic voltage restorer,” Journal on Asian Power Electron, 4(3).

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[6]. Dash PK, Padhee Malhar, Barik SK, (2012), “Estimation of power quality indices in distributed generation systems during power islanding conditions,” Int.., Journal Electrical Power Energy, 36:18–30.

[7]. Ghosh A, Ledwich G, (2002), “Compensation of distribution system voltage using DVR,” IEEE Trans.., Power Delivery, 17(4):1030–6.

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[10]. Hossein SH, Bannei MR, (2004), “A new minimal energy control of the DC Link energy in four-wire dynamic th voltage restorer,” In 30 Annual Conference of the IEEE Industrial Electronics Society, November 2–6, Busan, Korea.

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[13]. Nielsen JG, Blaabjerg F, (2005), “A detailed comparison of system topologies for dynamic voltage restorer,” IEEE Trans.., Ind.., Appl.., 41(5):1272–80.

[14]. Vilathgamuwa MA, Ranjithperera AD, Choi SS, (2002), “Performance improvement of the dynamic voltage restorer with closed- loop load voltage and current-mode control,” Power Electron 17(9):824–34.

[15]. Choi B, Li D, Vilathaguwa DM, (2002), “Design and analysis of the inverter side filter used in the dynamic voltage restorer (DVR),” IEEE Trans.., Power Delivery, 17(6):1058–66.

[16]. Ramasamy M, Thangavel S, (2012), “Photovoltaic based dynamic voltage restorer with power saver capability using PI controller,” Int.., Journal Electrical Power Energy, 36:51–9.

[17]. Chung Yop, Park Sang-Young, (2001), “The control and analysis of zero sequence components in DVR system,” Power Eng.., Soc.., Winter Meet 3:1021–6.

[18]. P.K.W. Chan, K.K.S. Leung, H.S.H. Chung, S.Y.R. Hui, (2006), “Boundry Controller for Dynamic Voltage Restorer to Achieve Fast Dynamic response,” IEEE conf.., p.1379–84.

[19]. Ezoji H, Sheikholeslami A, Rezanezhad M Livani H, (2010), “A new control method for dynamic voltage restorer with asymmetrical inverter legs based on fuzzy logic controller,” Simulation Model Practical Theory, 806–19.

[20]. Marei MI, EI-Saadany EF, Salama MMA, (2007), “A new approach to control DVR based on symmetrical components estimation,” IEEE Trans.., Power Delivered 22(1):2017–24.

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[22]. Carl NM, Ho Henry, Chaung SH, (2007), “Fast dynamic control scheme for capacitor supported dynamic voltage restorer design issue,” Implementation and Analysis, IEEE.

[23]. Kasuni Parera, Daniel Salomon, Arulampaiam, Atputharajah Sanath Alahakoon, (2006), “Automated control technique for a single phase dynamic voltage restorer,” IEEE.

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Review Paper

A Comprehensive Survey of Maximum Power Tracker Techniques for Photovoltaic System

Bal Mukund Sharma* , Kuldeep Sahay**

Sharma, B. M., and Sahay, K. (2014). A Comprehensive Survey of Maximum Power Tracker Techniques for Photovoltaic System. i-managerâ€™s Journal on Electrical Engineering , 8(1), 39-55.

Sharma, B. M., and Sahay, K. (2014). A Comprehensive Survey of Maximum Power Tracker Techniques for Photovoltaic System. i-manager’s Journal on Electrical Engineering , 8(1), 39-55. https://doi.org/10.26634/jee.8.1.2998

Abstract

The different MPPT techniques for maximum power point tracking of Photo Voltaic (PV) arrays are discussed in detail in this paper. Maximum Power Point Tracking (MPPT) techniques are employed in PV systems to make full utilization of PV array output power which depends on solar irradiation and temperature. The peak power is reached with the help of a dc/dc converter by adjusting its duty cycle. The algorithm changes the duty cycle of the dc/dc converter to maximize the power output of the module and make it operate at the peak power point of the module. This paper should serve as a convenient reference for future work in PV power generation.

References

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[30]. W. Wu, N. Pongratananukul, W. Qiu, K. Rustom, T. Kasparis, and I. Batarseh, (2003), “DSP-based multiple peak power tracking for expandable power system,” in Eighteenth Annu. IEEE Appl. Power Electron. Conf. Expo., pp. 525–530.

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