i-manager Publications

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

Current Issue Vol. 17 Issue 2

Most Cited

Volume 12 Issue 2 October - December 2018

Research Paper

Solar Powered Obstacle Avoiding Lawn Mower

P. S. V. Kishore* , P. Suresh Kumar , Smruti Dash *, K. Ramesh ****

*-**** Assistant Professor, Department of Electrical and Electronics Engineering, Vignan's IIT, Visakhapatnam, Andhra Pradesh, India.

Kishore, P. S. V., Kumar, P. S., Dash, S., and Ramesh, K. (2018). Solar Powered Obstacle Avoiding Lawn Mower. i-manager’s Journal on Electrical Engineering, 12(2), 1-5. https://doi.org/10.26634/jee.12.2.14169

Abstract

The cost of fuel is getting increased and the effect of gases being emitted from the burnt fuel is weakening the ozone layer. Carbon emission has also become a big challenge in today's world. Therefore, by using solar power, we can reduce carbon footprints. Lawn mowers are becoming popular now-a-days. Grass cutting being a tedious work for human beings, can be simplified by using an automatic grass cutter, which can be performed without a physical person being present. While cutting the grass, there are some obstacles, which obstruct the cutting of grass and sometimes the blades of the machine get damaged, so it is necessary to avoid obstacles. For that we have to identify the obstacles first and then we have to change the path of the lawn mower. Supplying power to the lawn mower is a big issue while designing the model. In this paper, the authors have used a solar panel to charge the battery and the power stored in the battery is utilized to power the electric motors, which will rotate the blades to cut the grass.

References

[1]. Dipin, A., & Chandrasekhar, T. K. (2014). Solar powered vision based robotic lawn mower. International Journal of Engineering Research and Reviews, 2(2), 53- 56.

[2]. Satwik, D., Rao, M. N. R., & Reddy, G. S. (2015). Design and fabrication of lever operated solar lawn mower and contact stress analysis of spur gears. International Journal of Science, Engineering and Technology Research (IJSETR), 4(8), 2815-2821.

[3]. Nourani-Vatani, N., Bosse, M., Roberts, J., & Dunbabin, M. (2006). Practical path planning and obstacle avoidance for autonomous mowing. In Proceedings of the Australasian Conference on Robotics and Automation 2006 (pp. 1-9).

[4]. Kumar, R. C., Khan, M. S., Kumar, D., Birua, R., Mondal, S., & Parai, M. K. (2013). Obstacle avoiding robot – a promising one. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 2(4), 1430-1434.

[5]. Nasucha, M. (2015). Development of an obstacle avoiding robot. Jurnal Sistem Komputer, 5(2).

[6]. Dutta, P. P., Baruah, A., Konwar, A., & Kumar, V. (2016). A technical review of lawn mower technology. ADBUJournal of Engineering Technology, 4(1), 179-182.

[7]. Hicks, R. W., & Hall, E. L. (2000, October). Survey of robot lawn mowers. In Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision (Vol. 4197, pp. 262-270). International Society for Optics and Photonics.

[8]. Sivagurunathan, R., Sivagurunathan, L., & Hao, J. C. J. (2017). Design and fabrication of low cost portable lawn mower. Scholars Journal of Engineering and Technology, 5(10), 584-591.

[9]. Amrutesh, P., Sagar, B., & Venu, B. (2014). Solar grass cutter with linear blades by using scotch yoke mechanism. Int. Journal of Engineering Research and Applications, 4(9), 10-21.

[10]. Okafor, B. (2013). Simple design of self-powered lawn mower. International Journal of Engineering and Technology, 3(10), 933-938.

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Research Paper

Soft Computing Approach to detect Fault in Induction Motor

Pratap Sekhar Puhan* , Sudarsan Behera**

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

**Assistant Professor, Department of Computer Science Engineering, Sreenidhi Institute of Science and Technology, Telangana, India.

Puhan, P. S., and Behera, S. (2018). Soft Computing Approach to Detect the Fault in Induction Motor. i-manager’s Journal on Electrical Engineering, 12(2), 6-14. https://doi.org/10.26634/jee.12.2.14845

Abstract

Soft Computing based intelligent system plays an important role in the process of diagnosis and detection of different types of faults in induction motor in the recent age. This paper presents two soft computing approaches to detect and diagnosis of bearing fault in induction motor. Radial basis function and feed forward back propagation technique in neural network controller with Park's Transformation is used in this work to increases the accuracy level. First the Neural networks structure is formed by taking the number of neurons and various functions involved such as Tan sigmoid, log sigmoid. Taking stator current three phase signals from the Machine fault simulator converts it to two phase Signal using PARK'S Transformation. Then the model is tested and trained. The results shows that both FFBPN and RBFNN gives better results when PARK'S Transformation Implemented, However if it is minutely checked radial basis function technique in neural network gives more encouraging results which be utilize in Induction motor for setting of on line condition monitoring effectively.

References

[1]. Alguindigue, I. E., Loskiewicz-Buczak, A., & Uhrig, R. E. (1993). Monitoring and diagnosis of rolling element bearings using Artificial Neural Networks. IEEE Transactions on Industrial Electronics, 40(2), 209-217.

[2]. Amir, P. F. (2008). An adaptive input-output feedback linearization controller for doubly-fed induction machine drives. Serbian Journal of Electrical Engineering, 5(1), 139-154.

[3]. Broomhead, D., & Lowe, D. (1988). Multivariable functional interpolation and adaptive networks. Int. J. Complex System, 2(3), 321-355.

[4]. Chou, B. (1991). Using Neural Neural Networks to detect incipient faults in induction motors. Journal of Neural Network Computing, 12(3).

[5]. Filippetti, F., Franceschini, G., Tassoni, C., & Vas, P. (2000). Recent developments of induction motor drives fault diagnosis using AI techniques. IEEE Transactions on Industrial Electronics, 47(5), 994-1004.

[6]. Khan, M. R., & Khan, M. F. (2015). Effect of resonance on the performance of single phase two winding self excited induction generator. i-manager's Journal on Electrical Engineering, 9(2), 8-15.

[7]. Knight, A. M., & Bertani, S. P. (2005). Mechanical fault detection in a medium-sized induction motor using stator current monitoring. IEEE Transactions on Energy Conversion, 20(4), 753-760.

[8]. Li, B., Chow, M. Y., Tipsuwan, Y., & Hung, J. C. (2000). Neural-network-based motor rolling bearing fault diagnosis. IEEE Transactions on Industrial Electronics, 47(5), 1060-1069.

[9]. Nandi, S., & Toliyat, H. A. (1999). Condition monitoring and diagnosis of electrical machine. In A Review IEEE Ind. Application Society Annual Meeting.

[10]. Patel, R. K., & Giri, B. R. T. C. (2015a). Application of DWT and PDD for bearing fault diagnosis using vibration signal. J. Elect. Eng.,15 (4), 139-144.

[11]. Patel, R. K., & Giri, V. K. (2015b). Fault classification of induction motor bearing using statistical features and Artificial Neural Network. Journal on Electrical Engineering, 9(2),41-48.

[12]. Puhan, P. S., & Behera, S. (2017, December). Application of soft computing methods to detect fault in AC motor. In Advances in Computing, Communication and Control (ICAC3), 2017 International Conference on (pp. 1-5). IEEE.

[13]. Schoen, R. R., Habetler, T. G., Kamran, F., & Bartfield, R. G. (1995). Motor bearing damage detection using stator current monitoring. IEEE Transactions on Industry Applications, 31(6), 1274-1279.

[14]. Tavner, P. J., Gaydon, B. G., & Ward, D. M. (1986, May). Monitoring generators and large motors. In IEE Proceedings B-Electric Power Applications, 133(3), 169- 180.

[15]. Wu, S., & Chow, T. W. (2004). Induction machine fault detection using SOM-based RBF neural networks. IEEE Transactions on Industrial Electronics, 51(1), 183-194.

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Research Paper

Differential Evolution Algorithm Based TID Controller for Autonomous Hybrid Power System

V. S. R. Pavan Kumar* , U. Salma**

* Ph.D Scholar, Department Electrical and Electronics Engineering, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India.

** Associate Professor, Department Electrical and Electronics Engineering, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India.

Neeli, V. S. R. P. K., and Salma, U. (2018). Differential Evolution Algorithm Based TID Controller for Autonomous Hybrid Power System. i-manager’s Journal on Electrical Engineering, 12(2), 15-23. https://doi.org/10.26634/jee.12.2.14780

Abstract

The objective of this paper is to design a load frequency controller for Autonomous hybrid power system with heuristic optimization approach like Differential Evolution Algorithm. A novel controller such as TID (Tilt-Integral-Derivative) Controller is employed to suppress the oscillations in the system that occurs due to variation or disturbances. The gain values of the controller are obtained by the DE algorithm. In order to allivate the effective nature of the proposed controller the responses are compared with the conventional PID controller in all test conditions applied. The DE tuned TID controller resembles stronger robustness properties than the conventional PID controller.

References

[1]. Behera, S. P., Biswal, A., Samantray, S. S., & Swain, B. (2018). Hybrid power systems Frequency regulation using Hybrid PIDF based robust controller design and Differential Evolution (DE) algorithm. International Conference on Technologies for Smart-City Energy Security and Power (ICSESP) (pp. 1-6).

[2]. Bhatti, T. S., Al-Ademi, A. A. F., & Bansal, N. K. (1997). Load frequency control of isolated wind diesel hybrid power systems. Energy Conversion and Management, 38(9), 829-837.

[3]. Chatterjee, A., Ghoshal, S. P., & Mukherjee, V. (2012). Solution of combined economic and emission dispatch problems of power systems by an opposition-based harmony search algorithm. International Journal of Electrical Power & Energy Systems, 39(1), 9-20.

[4]. Das, D. C., Roy, A. K., & Sinha, N. (2011a). PSO optimized frequency controller for wind-solar thermaldiesel hybrid energy generation system: A study. International Journal of Wisdom Based Computing, 1(3), 128-133.

[5]. Das, D. C., Roy, A. K., & Sinha, N. (2011b, December). PSO based frequency controller for wind-solar-diesel hybrid energy generation/energy storage system. In Energy, Automation, and Signal (ICEAS), 2011 International Conference on (pp. 1-6). IEEE.

[6]. Das, D. C., Roy, A. K., & Sinha, N. (2012). GA based frequency controller for solar thermal–diesel–wind hybrid energy generation/energy storage system. International Journal of Electrical Power & Energy Systems, 43(1), 262- 279.

[7]. Das, D. C., Sharma, A., Dema, D., & Modi, A. (2015, November). Performance analysis of Solar PV-diesel based autonomous hybrid power system using FFA and CSA optimized controller. In TENCON 2015-2015 IEEE Region 10 Conference (pp. 1-6). IEEE.

[8]. Das, D. C., Sinha, N., & Roy, A. K. (2014a). Automatic generation control of an organic rankine cycle solar–thermal/wind–diesel hybrid energy system. Energy Technology, 2(8), 721-731.

[9]. Das, D. C., Sinha, N., & Roy, A. K. (2014b). Small signal stability analysis of dish-Stirling solar thermal based autonomous hybrid energy system. International Journal of Electrical Power & Energy Systems, 63, 485-498.

[10]. Kumar, R. H., & Ushakumari, S. (2014, March). Biogeography based tuning of PID controllers for Load Frequency Control in microgrid. In Circuit, Power and Computing Technologies (ICCPCT), 2014 International Conference on (pp. 797-802). IEEE.

[11]. Lee, D. J., & Wang, L. (2008). Small-signal stability analysis of an autonomous hybrid renewable energy power generation/energy storage system part I: Timedomain simulations. IEEE Transactions on Energy Conversion, 23(1), 311-320.

[12]. Mohanty, B., Panda, S., & Hota, P. K. (2014). Controller parameters tuning of Differential Evolution algorithm and its application to load frequency control of multi-source power system. International Journal of Electrical Power & Energy Systems, 54, 77-85.

[13]. Mohanty, S. R., Kishor, N., & Ray, P. K. (2014). Robust H-infinite loop shaping controller based on hybrid PSO and harmonic search for frequency regulation in hybrid distributed generation system. International Journal of Electrical Power & Energy Systems, 60, 302-316.

[14]. Pan, I., & Das, S. (2016). Fractional order fuzzy control of hybrid power system with renewable generation using chaotic PSO. ISA Transactions, 62, 19-29.

[15]. Senjyu, T., Nakaji, T., Uezato, K., & Funabashi, T. (2005). A hybrid power system using alternative energy facilities in isolated island. IEEE Transactions on Energy Conversion, 20(2), 406-414.

[16]. Shankar, G., & Mukherjee, V. (2016). Load frequency control of an autonomous hybrid power system by quasioppositional harmony search algorithm. International Journal of Electrical Power & Energy Systems, 78, 715- 734.

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Research Paper

Comparison Between Inverter Control Techniques in Grid Connected Solar Photovoltaic Systems

Sushil Kumar Gupta* , Aarti Ahlawat, Diksha Gupta*

* Professor, Department of Electrical Engineering, Deenbandhu Chotu Ram University of Science and Technology, Sonipat, Haryana, India.

Post-graduate, Department of Electrical Engineering, Deenbandhu Chotu Ram University of Science and Technology, Sonipat, Haryana, India.

* Project Engineer, Wipro Technologies Ltd, Greater Noida, India.

Gupta, S. K., Ahlawat, A., and Gupta. (2018). Comparison Between Inverter Control Techniques in Grid Connected Solar Photovoltaic Systems. i-manager’s Journal on Electrical Engineering, 12(4), 24-31. https://doi.org/10.26634/jee.12.2.14334

Abstract

This paper deals with interaction of 10 kW Solar PV system with grid and study of real power flow from Solar PV to the load and to the grid. The proposed PV power plant system is modeled using MATLAB/Simulink software and its performance is studied. The whole system deals with simulation of a PV panel, MPPT controller, boost converter, and 3ɸ VSI and the control algorithms used in the system. The Solar Photovoltaic system has a MPPT tracking system with DC-DC boost converter to track the maximum power from the solar panels. The MPPT technique implemented in this system is the Modified Perturb and Observe method which is used to improve the efficiency of the system. The interface between grid and solar PV is carried out through a Voltage Source inverter and thus eliminating the current harmonics based on a control technique used in Voltage source inverters. The analysis and control design of grid connected PV inverter using PI control technique is performed in synchronous d-q rotating reference frame to achieve maximum output voltage response and active power. The SPWM (Sinusoidal Pulse Width Modulation), SRFT (Synchronous Reference Frame Theory) and IRPT (Instantaneous Reactance Power Theory) inverter techniques are implemented to control the proposed solar photovoltaic system. A current control strategy with PWM technique is proposed to provide pulse for VSI. This system demonstrates the elimination of harmonics and improves power factor.

References

[1]. Babu, K. D., Ramaprabha, R., Rajini, V., & Bansal, K. (2016, March). Auto synchronization of photovoltaic fed grid systems. In Electrical Energy Systems (ICEES), 2016 3^rdInternational Conference on (pp. 207-214). IEEE.

[2]. Bhople, S. U., & Rayarao, S. K. (2016). Comparison of various reference current generation techniques for performance analysis of shunt active power filter using Matlab simulation. International Journal of Current Engineering and Technology, 6(2), 606-611.

[3]. Bouhafs, A., Lokmane, B. M., & Mohamed, Djarallah. (2015). Grid connected photovoltaic system, for a 800 W. Energy Procedia, 74, 414-422.

[4]. Chovatia, C. M., Gupta, N. P., & Gupta, P. N. (2012). Harmonic Mitigation using Shunt Active Filter at Utility end in grid connected to Renewable Source of Energy. International Journal of Emerging Technology and Advanced Engineering, 2(8), 230-235.

[5]. Dubey, K., & Shah, M. T. (2016). Design and simulation of solar PV system. International Conference on Automatic Control and Dynamic Optimization Techniques (ICACDOT) (pp. 1-9).

[6]. Francis, W. K., & Mathew, P. J. (2014). MATLAB/Simulink PV Module Model of P & O and DC Link CDC MPPT Algorithms with Labview Real Time Monitoring and Control Over P & O Technique. Int. J. Adv. Res. Electr. Electron. Instrum. Eng., 3(5), 92-101.

[7]. Gupta, S. K., & Bansal, R. (2014). ATC in competitive electricity market using TCSC. International Journal of Electrical, Electronic Science and Engineering, 8(2), 308- 311.

[8]. Hauke, B. (2014). Basic Calculation of a Boost Converter's Power Stage (SLVA372C). Retrieved from Texas Instruments website: http://www.ti.com/lit/an/ slva372c/slva372c.pdf

[9]. Jyothi, G. A., & Narasimham, P. V. R. L. (2015). Implementation of reactive power theory for current harmonic reduction and reactive power compensation in three phase four wire system. IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE), 10(1), 68-74.

[10]. Lakshmanan, S. A., Rajpourhit, B. S., & Jain, A. (2014, March). Modeling and analysis of 3-phase VSI using SPWM technique for grid connected solar PV system. In Electrical, Electronics and Computer Science (SCEECS), 2014 IEEE Students' Conference on (pp. 1-6). IEEE.

[11]. Lueangamornsiri, T., Thongpull, K., Chalermyanont, K., & Wichakool, W. (2016, June). Design and development of a stand-alone solar energy harvesting system by MPPT and quick battery charging. In Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2016 13^th International Conference on (pp. 1-5). IEEE.

[12]. Singh, B., Shahani, D. T., & Verma, A. K. (2013, July). IRPT based control of a 50 kW grid interfaced solar photovoltaic power generating system with power quality improvement. In Power Electronics for Distributed Generation Systems (PEDG), 2013 4^th IEEE International Symposium on (pp. 1-8). IEEE.

[13]. Tripathi, R. N., & Singh, A. (2013, October). SRF theory based grid interconnected Solar Photovoltaic (SPV) system with improved power quality. In 2013 International Conference on Emerging Trends in Communication, Control, Signal Processing and Computing Applications (C2SPCA) (pp. 1-6). IEEE.

[14]. Varshney, G., Chauhan, D. S., & Dave, M. P. (2016). Evaluation of power quality issues in grid connected PV systems. International Journal of Electrical and Computer Engineering (IJECE), 6(4), 1412-1420.

[15]. Verma, A. K., Singh, B., & Shahani, D. T. (2012, September). Grid interfaced solar photovoltaic power generating system with power quality improvement at AC mains. In Sustainable Energy Technologies (ICSET), 2012 IEEE Third International Conference on (pp. 177-182). IEEE.

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Research Paper

A New Photovoltaic Topology with Reliable and Reactive Power Capability

B. Obulapathi* , Shaik Hussain Vali**

*Junior Research Fellow, Visvesvaraya National Institute of Technology (VNIT), Nagpur, Maharashtra, India.

**Assistant Professor and Research Scholar, Department of Electrical and Electronics Engineering, JNTUACEP, Andhra Pradesh, India.

Bobulapathi, B., and Vali, S. H. (2018). A New Photo Voltaic Topology with Reliable and Reactive Power Capability. i-manager’s Journal on Electrical Engineering, 12(2), 32-41. https://doi.org/10.26634/jee.12.2.15058

Abstract

The photovoltaic technology is one of the base sources of distributed generations for future generation, but it lacks certainty in power production. Absence of transformer in DC/AC conversion will reduce the cost and volume of the PV inverter. The absence of transformer creates galvanic isolation problem that produces leakage currents between grid and PV panel. The grid connected PV inverters with bipolar SPWM is able to supply active and reactive power to grid. The bipolar SPWM has high switching losses and voltage stress across the filter inductor, which is double the supply voltage. The conventional unipolar SPWM mitigates voltage stress and switching losses, but it lacks reactive power capability. In this paper, a new topology is proposed to give solutions to the above mentioned problems associated with reliability, leakage currents, and reactive power capability in a single topology. A transformerless H6 inverter is used to reduce leakage currents. A modified unipolar SPWM technique is applied to H6 inverter to mitigate voltage stress and switching loss with reactive power capability. A battery storage system is also connected between PV panel and inverter to make PV system reliable at least in power supply.

References

[1]. Barater, D., Concari, C., Buticchi, G., Gurpinar, E., De, D., & Castellazzi, A. (2016). Performance evaluation of a three-level ANPC photovoltaic grid-connected inverter with 650-V SiC devices and optimized PWM. IEEE Transactions on Industry Applications, 52(3), 2475-2485.

[2]. Chen, B., Gu, B., Zhang, L., & Lai, J. S. (2016). A novel pulse-width modulation method for reactive power generation on a CoolMOS and SiC-diode-based transformerless inverter. IEEE Transactions on Industrial Electronics, 63(3), 1539-1548.

[3]. Demirok, E., Gonzalez, P. C., Frederiksen, K. H., Sera, D., Rodriguez, P., & Teodorescu, R. (2011). Local reactive power control methods for overvoltage prevention of distributed solar inverters in low-voltage grids. IEEE Journal of Photovoltaics, 1(2), 174-182.

[4]. Denholm, P., & Kulcinski, G. L. (2004). Life cycle energy requirements and greenhouse gas emissions from large scale energy storage systems. Energy Conversion and Management, 45(13-14), 2153-2172.

[5]. Freddy, T. K. S., Lee, J. H., Moon, H. C., Lee, K. B., & Rahim, N. A. (2017). Modulation technique for singlephase transformerless photovoltaic inverters with reactive power capability. IEEE Transactions on Industrial Electronics, 64(9), 6989-6999.

[6]. Freddy, T. K. S., & Rahim, N. A. (2016). Photovoltaic inverter topologies for grid integration applications. In Advances in Solar Photovoltaic Power Plants (pp. 13-42). Springer, Berlin, Heidelberg.

[7]. Islam, M., Afrin, N., & Mekhilef, S. (2016). Efficient single phase transformerless inverter for grid-tied PVG system with reactive power control. IEEE Transactions on Sustainable Energy, 7(3), 1205-1215.

[8]. Linden, D., & Reddy, T. B. (2002). Handbook of Batteries, 3^rd Edn. New York: Mcgraw-Hill.

[9]. Wu, T. F., Kuo, C. L., Sun, K. H., & Hsieh, H. C. (2014). Combined unipolar and bipolar PWM for current distortion improvement during power compensation. IEEE Transactions on Power Electronics, 29(4), 1702-1709.

[10]. Xiao, H., Xie, S., Chen, Y., & Huang, R. (2011). An optimized transformerless photovoltaic grid-connected inverter. IEEE Transactions on Industrial Electronics, 58(5), 1887-1895.

[11]. Yang, Y., Blaabjerg, F., & Wang, H. (2014). Lowvoltage ride-through of single-phase transformerless photovoltaic inverters. IEEE Transactions on Industry Applications, 50(3), 1942-1952.

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

Current Issue Vol. 17 Issue 2

Most Read

Most Cited

Volume 12 Issue 2 October - December 2018

Solar Powered Obstacle Avoiding Lawn Mower

P. S. V. Kishore* , P. Suresh Kumar **, Smruti Dash ***, K. Ramesh ****

*-**** Assistant Professor, Department of Electrical and Electronics Engineering, Vignan's IIT, Visakhapatnam, Andhra Pradesh, India.

Kishore, P. S. V., Kumar, P. S., Dash, S., and Ramesh, K. (2018). Solar Powered Obstacle Avoiding Lawn Mower. i-manager’s Journal on Electrical Engineering, 12(2), 1-5. https://doi.org/10.26634/jee.12.2.14169

Abstract

References

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Soft Computing Approach to detect Fault in Induction Motor

Pratap Sekhar Puhan* , Sudarsan Behera**

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

Puhan, P. S., and Behera, S. (2018). Soft Computing Approach to Detect the Fault in Induction Motor. i-manager’s Journal on Electrical Engineering, 12(2), 6-14. https://doi.org/10.26634/jee.12.2.14845

Abstract

References

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Differential Evolution Algorithm Based TID Controller for Autonomous Hybrid Power System

V. S. R. Pavan Kumar* , U. Salma**

* Ph.D Scholar, Department Electrical and Electronics Engineering, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India. ** Associate Professor, Department Electrical and Electronics Engineering, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India.

Neeli, V. S. R. P. K., and Salma, U. (2018). Differential Evolution Algorithm Based TID Controller for Autonomous Hybrid Power System. i-manager’s Journal on Electrical Engineering, 12(2), 15-23. https://doi.org/10.26634/jee.12.2.14780

Abstract

References

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Comparison Between Inverter Control Techniques in Grid Connected Solar Photovoltaic Systems

Sushil Kumar Gupta* , Aarti Ahlawat**, Diksha Gupta***

Gupta, S. K., Ahlawat, A., and Gupta. (2018). Comparison Between Inverter Control Techniques in Grid Connected Solar Photovoltaic Systems. i-manager’s Journal on Electrical Engineering, 12(4), 24-31. https://doi.org/10.26634/jee.12.2.14334

Abstract

References

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A New Photovoltaic Topology with Reliable and Reactive Power Capability

B. Obulapathi* , Shaik Hussain Vali**

*Junior Research Fellow, Visvesvaraya National Institute of Technology (VNIT), Nagpur, Maharashtra, India. **Assistant Professor and Research Scholar, Department of Electrical and Electronics Engineering, JNTUACEP, Andhra Pradesh, India.

Bobulapathi, B., and Vali, S. H. (2018). A New Photo Voltaic Topology with Reliable and Reactive Power Capability. i-manager’s Journal on Electrical Engineering, 12(2), 32-41. https://doi.org/10.26634/jee.12.2.15058

Abstract

References

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P. S. V. Kishore* , P. Suresh Kumar , Smruti Dash *, K. Ramesh ****

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

**Assistant Professor, Department of Computer Science Engineering, Sreenidhi Institute of Science and Technology, Telangana, India.

* Ph.D Scholar, Department Electrical and Electronics Engineering, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India.

** Associate Professor, Department Electrical and Electronics Engineering, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India.

Sushil Kumar Gupta* , Aarti Ahlawat, Diksha Gupta*

*Junior Research Fellow, Visvesvaraya National Institute of Technology (VNIT), Nagpur, Maharashtra, India.

**Assistant Professor and Research Scholar, Department of Electrical and Electronics Engineering, JNTUACEP, Andhra Pradesh, India.