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Suryaprakash, S.
- A Modified Single Phase Multilevel Inverter Topology for Distributed Energy Resources
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Authors
Affiliations
1 Department of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore-641049, IN
1 Department of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore-641049, IN
Source
Research Journal of Engineering and Technology, Vol 8, No 3 (2017), Pagination: 253-258Abstract
Distributed energy resources systems are small scale power generation which is used to modernize advanced renewable technologies to facilitate smarter grid. Even though MLI holds special features such as better quality waveform, low electromagnetic interference, harmonic reduction but then usage of more switches in conventional MLI poses a constraint. The objective of this paper is mainly focused on single phase Multilevel Inverter (MLI) for distributed energy resources thereby minimizing power electronic switches for higher level output which essentially reduces the cost, switching losses and harmonics for real time application. The proposed inverter is modeled and compared with Cascaded H-Bridge MLI; simulation results are shown for 15-level and performance of MLI is validated using MATLAB 7.10 version (Simulink).Keywords
Multilevel Inverter (MLI), Gate Pulses, Distributed Energy Resources (DER), Harmonics, Switching Losses.
References
- S. N. Singh, B. Singh and J. Ostergaard, "Renewable energy generation in India: Present scenario and future prospects," 2009 IEEE Power and Energy Society General Meeting, Calgary, AB, 2009, pp. 1-8.
- P. Khanzode, S. Nigam, S. P. Karthikeyan, K. S. Kumar and I. J. Raglend, "Indian power scenario-a road map to 2020," 2014 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2014], Nagercoil, 2014, pp. 70-78.
- S. Correia, S. F. Pinto and J. F. Silva, "Smart integration of Distributed Energy Resources in microgrids," 2017 International Young Engineers Forum (YEF-ECE), Almada, 2017, pp. 85-90.
- A. Mortezaei, M. G. Simões, F. P. Marafão and A. Al Durra, "5-level Cascaded H-Bridge Multilevel microgrid Inverter applicable to multiple DG resources with power quality enhancement capability," 2015 IEEE 13th Brazilian Power Electronics Conference and 1st Southern Power Electronics Conference (COBEP/SPEC), Fortaleza, 2015, pp. 1-6
- L. Manai, F. Armi and M. Besbes, "New topology of cascaded multilevel inverter with reduced number of switches control considering lower order harmonics elimination," 2016 4th International Conference on Control Engineering and Information Technology (CEIT), Hammamet, 2016, pp. 1-8.
- J. G. Shankar, J. B. Edward, P. Ponnambalam and K. S. Kumar, "A Single Phase Hybrid Multilevel Inverter with High Step up DC-DC Converter for Photovoltaic System," 2016 IEEE Region 10 Conference (TENCON), Singapore, 2016, pp. 327-336.
- J. Rodriguez, J. Lai, F.Z. Peng “Multilevel inverters: a survey of topologies, controls, and applications”, IEEE Trans Ind Appl, 49 (4)(2002), pp. 724-738
- J. Belwin ED ward J. Gowri Shankar, “Implementation of 5-level cascaded h-bridge multilevel inverter with single dc source for photo voltaic system using proteus,”2016 Journal of electrical engineering, Volume 16 Issue 4.
- J. Gowri Shankar and J. Belwin Edward “Design and Implementation of 15-Level Asymmetric Cascaded H Bridge Multilevel Inverter,” Journal of Electrical Engineering, Volume 17 Issue 2 2017
- J. G. Shankar and J. Belwin Edward, "A 15-level asymmetric cascaded H bridge multilevel inverter with less number of switches for photo voltaic system," 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT), Nagercoil, 2016, pp. 1-10.
- N. Vinothkumar, V. Kumar Chinnaiyan, Pradish. M and Prabhakar karthikeyan, "Multilevel Inverter Structure using Single Source and Double Source Module to Reduce Power Electronics Components", IET The Journal of Engineering, pp. 1-10, March 2017
- IOT Based Home Automation System Through Adaptive Decision Making Fuzzy Algorithm
Abstract Views :132 |
PDF Views:0
Authors
Affiliations
1 Department of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore, Tamilnadu, IN
1 Department of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore, Tamilnadu, IN
Source
Research Journal of Engineering and Technology, Vol 8, No 3 (2017), Pagination: 268-272Abstract
Real time automation is increasingly gets popular due to its flexibility in utilizing open source tool and adapting the new node without any complexity in programming. This paper proposes the human machine interface through context aware and decision support system using distance based fuzzy algorithm which utilizes the user’s domain knowledge to frame the rules. The developed system is based on Linux OS and the algorithm is developed in python and results were stored in internet by FHEM API, used in Raspberry Pi B+ kit which is an IoT application and the mobile SSH settings using Wi-Fi modem. Using this app we can access through home automation systems by connecting IP address of the web server and also voice assisted module helps the patients to control the appliance through voice control. Effective algorithmic decision making and voice assisted automation produces the better result in automating the things in real world.Keywords
Real Time Automation, Human Machine Interface, Decision Support System, FHEM API, Raspberry Pi B+, Voice Control.References
- K. Mukendi and M. Adonis, "The development of a remotely controlled home automation system for energy saving," 2017 International Conference on the Domestic Use of Energy (DUE), Cape Town, 2017, pp. 265-270.
- P. Padmavathi and M. Mathankumar (2015, April) “An Enhanced Approach on Secured Data Communication Using Mobile Relay Node in Wireless Sensor Network” International Journal of Applied Engineering Research, Vol. 10 No.20. https://www.ripublication.com/Volume/ijaerv10n20spl.htm
- C. Mohanraj et al. (2013) “Design and development of secret session key generation using embedded crypto device – ARM-LPC2148”, Journal of Artificial Intelligence, vol. 6 (2).http://scialert.net/abstract/?doi=jai.2013.134.144.
- S. Kim, H. Cho, T. Yang, C. Kim and S. H. Kim, "Low-Cost Multipath Routing Protocol by Adapting Opportunistic Routing in Wireless Sensor Networks," 2017 IEEE Wireless Communications and Networking Conference (WCNC), San Francisco, CA, 2017, pp. 1-6.
- A. C. Jose and R. Malekian, "Improving Smart Home Security: Integrating Logical Sensing Into Smart Home," in IEEE Sensors Journal, vol. 17, no. 13, pp. 4269-4286, July1, 1 2017.
- S. Jain, A. Vaibhav and L. Goyal, "Raspberry Pi based interactive home automation system through E-mail," 2014 International Conference on Reliability Optimization and Information Technology (ICROIT), Faridabad, 2014, pp. 277-280.
- G. D. Abowd, A. K. Dey, R. Orr and J. Brotherton, "Contextawareness in wearable and ubiquitous computing," Digest of Papers. First International Symposium on Wearable Computers, Cambridge, MA, USA, 1997, pp. 179-180.
- G. D. Abowd, A. K. Dey, R. Orr and J. Brotherton, "Context-awareness in wearable and ubiquitous computing," Digest of Papers. First International Symposium on Wearable Computers, Cambridge, MA, USA, 1997, pp. 179-180.
- Y. Evchina, A. Dvoryanchikova and J. L. Martinez Lastra, "Semantic information management for user and context aware smart home with social services," 2013 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), San Diego, CA, 2013, pp. 262-268. doi: 10.1109/CogSIMA.2013.6523856
- P. TalebiFard and V. C. M. Leung, “A data fusion approach to context-aware service delivery in heterogeneous network environments,” Procedia Comput. Sci., vol. 5, pp. 312–319, 2011.
- R. Schafer, “Rules for using multi-attribute utility theory estimating a user’s interests,” in Proc. Workshop Adaptivity User Modell, 2001.
- X. Wang, D. Rosenblum, and Y. Wang, “Context-aware mobile music recommendation for daily activities,” in Proc. 20th ACM Int.Conf. Multimedia, Nara, Japan, pp. 99–108, 2012.
- A. Al-Hmouz, J. Shen, R. Al-Homouz, and J. Yan, “Modeling and simulation of an adaptive neuro-fuzzy interface system (ANFIS) for mobile learning,” IEEE Trans. Learning Technol., vol. 5, no. 3, pp. 226–237, Jul.–Sep. 2012.
- Q. Duan, D. Miao, H. Zhang, and J. Zheng, “Personalized web retrieval based on rough-fuzzy method,” J. Comput. Inform. Syst., vol. 3, no. 2, pp. 203–208, 2007.
- G. Acampora, M. Gaeta, V. Loia, and A. V. Vasilakos, “Interoperable and adaptive fuzzy service for ambient intelligence applications,” ACM Trans. Autonomous Adaptive Syst., vol. 5, no. 2, pp. 1–26, 2010.