IJITCE.CO.UK December 2018 Vol.8 Issue.12

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018

UK: Managing Editor International Journal of Innovative Technology and Creative Engineering 1a park lane, Cranford London TW59WA UK

USA: Editor International Journal of Innovative Technology and Creative Engineering Dr. Arumugam Department of Chemistry University of Georgia GA-30602, USA.

India: Editor International Journal of Innovative Technology & Creative Engineering 36/4 12th Avenue, 1st cross St, Vaigai Coliny Ashok Nagar Chennai , India 600083 Email: editor@ijitce.co.uk

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018

IJITCE PUBLICATION

International Journal of Innovative Technology & Creative Engineering Vol.8 No.12 December 2018

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018

From Editor's Desk Dear Researcher, Greetings!

The month of November witnessed some of important events in India Whats Humprey Awards presented by SPIN Chennai International Computer Security Day conducted by Cyber Society of India.

IJITCE was a journal partner in both the above conferences IJITCE was also invited as a partner for the Watts Humphrey Awards, a prestigious recognition from SPIN Chennai initiated to honor the software engineering Guru Dr. Watts Humphrey. Teams from various organizations across industries will be invited to nominate their practice / case study. Jury will evaluate the submissions (offline) and shortlisted teams presented their story and showcased their practices on the day of the awards in front of the Grand Jury.

International Computer Security was observed on 30 Nov 2018. Cyber Society of India organized one day event in Chennai India to create awareness among the Public. The event will be conducted in association with the Tamil Nadu State Police and Voice of Voiceless, an NGO. A Research article in this issue discusses about Design and Implementation of Inductive Power Transfer for EV Battery Charging.

Thanks, Editorial Team IJITCE http://www.google.com/#q=%222045-8711%22 http://www.bing.com/search?q=%222045-8711%22 http://fr.search.yahoo.com/search;_ylc=X3oDMTFiN25laTRvBF9TAzIwMjM1MzgwNzUEaXRjAzEEc2VjA3NyY2hfc WEEc2xrA3NyY2h3ZWI-?p=%222045-8711%22

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018

Editorial Members Dr. Chee Kyun Ng Ph.D Department of Computer and Communication Systems, Faculty of Engineering,Universiti Putra Malaysia,UPMSerdang, 43400 Selangor,Malaysia.

Dr. Simon SEE Ph.D Chief Technologist and Technical Director at Oracle Corporation, Associate Professor (Adjunct) at Nanyang Technological University Professor (Adjunct) at ShangaiJiaotong University, 27 West Coast Rise #08-12,Singapore 127470 Dr. sc.agr. Horst Juergen SCHWARTZ Ph.D, Humboldt-University of Berlin,Faculty of Agriculture and Horticulture,Asternplatz 2a, D-12203 Berlin,Germany Dr. Marco L. BianchiniPh.D Italian National Research Council; IBAF-CNR,Via Salaria km 29.300, 00015 MonterotondoScalo (RM),Italy Dr. NijadKabbaraPh.D Marine Research Centre / Remote Sensing Centre/ National Council for Scientific Research, P. O. Box: 189 Jounieh,Lebanon Dr. Aaron Solomon Ph.D Department of Computer Science, National Chi Nan University,No. 303, University Road,Puli Town, Nantou County 54561,Taiwan Dr. Arthanariee. A. M M.Sc.,M.Phil.,M.S.,Ph.D Director - Bharathidasan School of Computer Applications, Ellispettai, Erode, Tamil Nadu,India Dr. Takaharu KAMEOKA, Ph.D Professor, Laboratory of Food, Environmental & Cultural Informatics Division of Sustainable Resource Sciences, Graduate School of Bioresources,Mie University, 1577 Kurimamachiya-cho, Tsu, Mie, 514-8507, Japan Dr. M. Sivakumar M.C.A.,ITIL.,PRINCE2.,ISTQB.,OCP.,ICP. Ph.D. Project Manager - Software,Applied Materials,1a park lane,cranford,UK Dr. Bulent AcmaPh.D Anadolu University, Department of Economics,Unit of Southeastern Anatolia Project(GAP),26470 Eskisehir,TURKEY Dr. SelvanathanArumugamPh.D Research Scientist, Department of Chemistry, University of Georgia, GA-30602,USA. Dr. S.Prasath Ph.D Assistant Professor, Department of Computer Science, Nandha Arts & Science College, Erode , Tamil Nadu, India

Review Board Members Dr. Paul Koltun Senior Research ScientistLCA and Industrial Ecology Group,Metallic& Ceramic Materials,CSIRO Process Science & Engineering Private Bag 33, Clayton South MDC 3169,Gate 5 Normanby Rd., Clayton Vic. 3168, Australia Dr. Zhiming Yang MD., Ph. D. Department of Radiation Oncology and Molecular Radiation Science,1550 Orleans Street Rm 441, Baltimore MD, 21231,USA Dr. Jifeng Wang Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign Urbana, Illinois, 61801, USA Dr. Giuseppe Baldacchini ENEA - Frascati Research Center, Via Enrico Fermi 45 - P.O. Box 65,00044 Frascati, Roma, ITALY. Dr. MutamedTurkiNayefKhatib Assistant Professor of Telecommunication Engineering,Head of Telecommunication Engineering Department,Palestine Technical University (Kadoorie), TulKarm, PALESTINE.

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 Dr.P.UmaMaheswari Prof &Head,Depaartment of CSE/IT, INFO Institute of Engineering,Coimbatore.

Dr. T. Christopher, Ph.D., Assistant Professor &Head,Department of Computer Science,Government Arts College(Autonomous),Udumalpet, India.

Dr. T. DEVI Ph.D. Engg. (Warwick, UK), Head,Department of Computer Applications,Bharathiar University,Coimbatore-641 046, India.

Dr. Renato J. orsato Professor at FGV-EAESP,Getulio Vargas Foundation,São Paulo Business School,RuaItapeva, 474 (8° andar),01332-000, São Paulo (SP), Brazil Visiting Scholar at INSEAD,INSEAD Social Innovation Centre,Boulevard de Constance,77305 Fontainebleau - France Y. BenalYurtlu Assist. Prof. OndokuzMayis University Dr.Sumeer Gul Assistant Professor,Department of Library and Information Science,University of Kashmir,India Dr. ChutimaBoonthum-Denecke, Ph.D Department of Computer Science,Science& Technology Bldg., Rm 120,Hampton University,Hampton, VA 23688 Dr. Renato J. Orsato Professor at FGV-EAESP,Getulio Vargas Foundation,São Paulo Business SchoolRuaItapeva, 474 (8° andar),01332-000, São Paulo (SP), Brazil Dr. Lucy M. Brown, Ph.D. Texas State University,601 University Drive,School of Journalism and Mass Communication,OM330B,San Marcos, TX 78666 JavadRobati Crop Production Departement,University of Maragheh,Golshahr,Maragheh,Iran VineshSukumar (PhD, MBA) Product Engineering Segment Manager, Imaging Products, Aptina Imaging Inc. Dr. Binod Kumar PhD(CS), M.Phil.(CS), MIAENG,MIEEE HOD & Associate Professor, IT Dept, Medi-Caps Inst. of Science & Tech.(MIST),Indore, India Dr. S. B. Warkad Associate Professor, Department of Electrical Engineering, Priyadarshini College of Engineering, Nagpur, India Dr. doc. Ing. RostislavChoteborský, Ph.D. Katedramateriálu a strojírenskétechnologieTechnickáfakulta,Ceskázemedelskáuniverzita v Praze,Kamýcká 129, Praha 6, 165 21 Dr. Paul Koltun Senior Research ScientistLCA and Industrial Ecology Group,Metallic& Ceramic Materials,CSIRO Process Science & Engineering Private Bag 33, Clayton South MDC 3169,Gate 5 Normanby Rd., Clayton Vic. 3168 DR.ChutimaBoonthum-Denecke, Ph.D Department of Computer Science,Science& Technology Bldg.,HamptonUniversity,Hampton, VA 23688 Mr. Abhishek Taneja B.sc(Electronics),M.B.E,M.C.A.,M.Phil., Assistant Professor in the Department of Computer Science & Applications, at Dronacharya Institute of Management and Technology, Kurukshetra. (India).

Dr. Ing. RostislavChotěborský,ph.d, Katedramateriálu a strojírenskétechnologie, Technickáfakulta,Českázemědělskáuniverzita v Praze,Kamýcká 129, Praha 6, 165 21

Dr. AmalaVijayaSelvi Rajan, B.sc,Ph.d, Faculty – Information Technology Dubai Women’s College – Higher Colleges of Technology,P.O. Box – 16062, Dubai, UAE

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 Naik Nitin AshokraoB.sc,M.Sc Lecturer in YeshwantMahavidyalayaNanded University Dr.A.Kathirvell, B.E, M.E, Ph.D,MISTE, MIACSIT, MENGG Professor - Department of Computer Science and Engineering,Tagore Engineering College, Chennai Dr. H. S. Fadewar B.sc,M.sc,M.Phil.,ph.d,PGDBM,B.Ed. Associate Professor - Sinhgad Institute of Management & Computer Application, Mumbai-BangloreWesternly Express Way Narhe, Pune - 41 Dr. David Batten Leader, Algal Pre-Feasibility Study,Transport Technologies and Sustainable Fuels,CSIRO Energy Transformed Flagship Private Bag 1,Aspendale, Vic. 3195,AUSTRALIA Dr R C Panda (MTech& PhD(IITM);Ex-Faculty (Curtin Univ Tech, Perth, Australia))Scientist CLRI (CSIR), Adyar, Chennai - 600 020,India Miss Jing He PH.D. Candidate of Georgia State University,1450 Willow Lake Dr. NE,Atlanta, GA, 30329 Jeremiah Neubert Assistant Professor,MechanicalEngineering,University of North Dakota Hui Shen Mechanical Engineering Dept,Ohio Northern Univ.

Dr. Xiangfa Wu, Ph.D. Assistant Professor / Mechanical Engineering,NORTH DAKOTA STATE UNIVERSITY SeraphinChallyAbou Professor,Mechanical& Industrial Engineering Depart,MEHS Program, 235 Voss-Kovach Hall,1305 OrdeanCourt,Duluth, Minnesota 55812-3042 Dr. Qiang Cheng, Ph.D. Assistant Professor,Computer Science Department Southern Illinois University CarbondaleFaner Hall, Room 2140-Mail Code 45111000 Faner Drive, Carbondale, IL 62901 Dr. Carlos Barrios, PhD Assistant Professor of Architecture,School of Architecture and Planning,The Catholic University of America Y. BenalYurtlu Assist. Prof. OndokuzMayis University Dr. Lucy M. Brown, Ph.D. Texas State University,601 University Drive,School of Journalism and Mass Communication,OM330B,San Marcos, TX 78666 Dr. Paul Koltun Senior Research ScientistLCA and Industrial Ecology Group,Metallic& Ceramic Materials CSIRO Process Science & Engineering Dr.Sumeer Gul Assistant Professor,Department of Library and Information Science,University of Kashmir,India Dr. ChutimaBoonthum-Denecke, Ph.D Department of Computer Science,Science& Technology Bldg., Rm 120,Hampton University,Hampton, VA 23688

Dr. Renato J. Orsato Professor at FGV-EAESP,Getulio Vargas Foundation,São Paulo Business School,RuaItapeva, 474 (8° andar)01332-000, São Paulo (SP), Brazil Dr. Wael M. G. Ibrahim Department Head-Electronics Engineering Technology Dept.School of Engineering Technology ECPI College of Technology 5501 Greenwich Road - Suite 100,Virginia Beach, VA 23462

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 Dr. Messaoud Jake Bahoura Associate Professor-Engineering Department and Center for Materials Research Norfolk State University,700 Park avenue,Norfolk, VA 23504 Dr. V. P. Eswaramurthy M.C.A., M.Phil., Ph.D., Assistant Professor of Computer Science, Government Arts College(Autonomous), Salem-636 007, India.

Dr. P. Kamakkannan,M.C.A., Ph.D ., Assistant Professor of Computer Science, Government Arts College(Autonomous), Salem-636 007, India.

Dr. V. Karthikeyani Ph.D., Assistant Professor of Computer Science, Government Arts College(Autonomous), Salem-636 008, India.

Dr. K. Thangadurai Ph.D., Assistant Professor, Department of Computer Science, Government Arts College ( Autonomous ), Karur - 639 005,India.

Dr. N. Maheswari Ph.D., Assistant Professor, Department of MCA, Faculty of Engineering and Technology, SRM University, Kattangulathur, Kanchipiram Dt - 603 203, India.

Mr. Md. Musfique Anwar B.Sc(Engg.)

Lecturer, Computer Science & Engineering Department, Jahangirnagar University, Savar, Dhaka, Bangladesh.

Mrs. Smitha Ramachandran M.Sc(CS)., SAP Analyst, Akzonobel, Slough, United Kingdom.

Dr. V. Vallimayil Ph.D., Director, Department of MCA, Vivekanandha Business School For Women, Elayampalayam, Tiruchengode - 637 205, India.

Mr. M. Moorthi M.C.A., M.Phil., Assistant Professor, Department of computer Applications, Kongu Arts and Science College, India PremaSelvarajBsc,M.C.A,M.Phil Assistant Professor,Department of Computer Science,KSR College of Arts and Science, Tiruchengode Mr. G. Rajendran M.C.A., M.Phil., N.E.T., PGDBM., PGDBF., Assistant Professor, Department of Computer Science, Government Arts College, Salem, India.

Dr. Pradeep H Pendse B.E.,M.M.S.,Ph.d Dean - IT,Welingkar Institute of Management Development and Research, Mumbai, India Muhammad Javed Centre for Next Generation Localisation, School of Computing, Dublin City University, Dublin 9, Ireland Dr. G. GOBI Assistant Professor-Department of Physics,Government Arts College,Salem - 636 007 Dr.S.Senthilkumar Post Doctoral Research Fellow, (Mathematics and Computer Science & Applications),UniversitiSainsMalaysia,School of Mathematical Sciences, Pulau Pinang-11800,[PENANG],MALAYSIA. Manoj Sharma Associate Professor Deptt. of ECE, PrannathParnami Institute of Management & Technology, Hissar, Haryana, India RAMKUMAR JAGANATHAN Asst-Professor,Dept of Computer Science, V.L.B Janakiammal college of Arts & Science, Coimbatore,Tamilnadu, India Dr. S. B. Warkad Assoc. Professor, Priyadarshini College of Engineering, Nagpur, Maharashtra State, India Dr. Saurabh Pal Associate Professor, UNS Institute of Engg. & Tech., VBS Purvanchal University, Jaunpur, India Manimala Assistant Professor, Department of Applied Electronics and Instrumentation, St Joseph’s College of Engineering & Technology, Choondacherry Post, Kottayam Dt. Kerala -686579 Dr. Qazi S. M. Zia-ul-Haque Control Engineer Synchrotron-light for Experimental Sciences and Applications in the Middle East (SESAME),P. O. Box 7, Allan 19252, Jordan

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Dr. A. Subramani, M.C.A.,M.Phil.,Ph.D. Professor,Department of Computer Applications, K.S.R. College of Engineering, Tiruchengode - 637215 Dr. SeraphinChallyAbou Professor, Mechanical & Industrial Engineering Depart. MEHS Program, 235 Voss-Kovach Hall, 1305 Ordean Court Duluth, Minnesota 558123042 Dr. K. Kousalya Professor, Department of CSE,Kongu Engineering College,Perundurai-638 052 Dr. (Mrs.) R. Uma Rani Asso.Prof., Department of Computer Science, Sri Sarada College For Women, Salem-16, Tamil Nadu, India.

MOHAMMAD YAZDANI-ASRAMI Electrical and Computer Engineering Department, Babol"Noshirvani" University of Technology, Iran.

Dr. Kulasekharan, N, Ph.D Technical Lead - CFD,GE Appliances and Lighting, GE India,John F Welch Technology Center,Plot # 122, EPIP, Phase 2,Whitefield Road,Bangalore – 560066, India.

Dr. Manjeet Bansal Dean (Post Graduate),Department of Civil Engineering,Punjab Technical University,GianiZail Singh Campus,Bathinda -151001 (Punjab),INDIA Dr. Oliver Jukić Vice Dean for education,Virovitica College,MatijeGupca 78,33000 Virovitica, Croatia Dr. Lori A. Wolff, Ph.D., J.D. Professor of Leadership and Counselor Education,The University of Mississippi,Department of Leadership and Counselor Education, 139 Guyton University, MS 38677

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018

Contents Whats Humprey awards 2018

……………………………..…..[559]

International Indian Icon (3iii) Season II Grand Finale

…….…………..…………..…..[561]

International Computer Security Day 2018

……………………………..…..[563]

Connected Vehicles

……………………………..…..[567]

Design and Implementation Of Inductive Power Transfer For Ev Battery Charging.…. [568] Grey Wolf Optimization Algorithm for Generation Rescheduling In Deregulated Power System for Congestion Management…............……. [573]

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018

Whats Humprey awards 2018 Software Process Improvement Network, Chennai (www.spinchennai.org) also known as SPIN Chennai is a leadership forum for open exchange of software process improvement experiences and ideas and was established 20 years ago in affiliation with Watts Humphrey Institute, USA as well as Software Engineering Institute of Carnegie Mellon University. Chennai SPIN is one of the oldest of the 130 SPINs in the world today. SPIN Chennai has been the pioneer in promoting various high maturity quality and management practices, processes, frameworks and models including CMMI, ISO, People CMM, Six Sigma, Lean, TOC, BS7799, GDPR, Agile, SAFE, Kanban, Malcolm Bladridge, Balanced Score Card, Blue Ocean Strategy, 5S, 7QC Tools, TQM, Design Thinking, Soc2, Security and Privacy frameworks etc in India.. Some of the world renowned gurus who have given guidance and have visited SPIN Chennai for various sessions include Watts Humphrey (USA), Lewis Trigger (Israel), Bill Curtis (USA)….SPIN Chennai’s partner organizations include FICCI, Nasscom, CII, IEEE, CSI,CIOKlub, CXO Club, ISACA, PMI, CYSI, CSPF, IOD, eWIT, Veltech TBI ecosystem etc.

instituted several years ago. This year 2018 Watts Humphrey awards, the theme is on “Agile and Automation for Business Value and Impact”. The topics on which the case studies were invited include the following:

SPIN Chennai – A dynamic ecosystem

the TOP 10 teams. The TOP 10 teams were invited to present their case study / story at the grand finale.

On 12th November 2018, the grand finale was held at Cognizant Technology Solutions,Chennai. The Winner and Runners were selected by the Jury based on various parameters.

Over the years, SPIN Chennai has evolved itself as a dynamic ecosystem with a nearly 2000 strong community of “whos who” you can think of including Domain experts, SME’s, Thought leaders, leading practitioners, researchers, academics, trainers, mentors, start-ups, consultants, publishers and journal partners like the Internationally renowned IJITCE, HR experts, Operations experts, infrastructure people, marketing experts, supply chain experts, media partners etc .

Being Agile Lean Software Development Agile and Scale Automating for continuous delivery Devops implementation Process Automation

Practices and experiments on Being Agile w.r.to Culture and Practices Applying lean startup and design thinking to software development Your experience, techniques and framework for large scale Agile Transformation Share Automation story on increasing deployment frequency, lead time to change, MTTR, Change Failure rate.

Share experience and impact on Culture, Automation, Lean, Measurement etc while adopting DevOps Share case studies on process automation using RPA and other tools

Evaluation Criteria The evaluation criteria included (1) Relevance to the theme (2) Originality / Uniqueness (3) Measurable Results (4) Benefits/Impact to customers. During the presentation round, additionally some weightage was given to clear articulation and presentation as well.

About Watts Humphrey awards SPIN Chennai has been associated with the global quality guru Dr.Watts Humphrey for many years till 2010. In his memory, Watts Humphrey awards were

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018

Chief Guest for Watts Humphrey Awards 2018

Watts Humphrey Award Contestants

Dr. Bill Curtis, Co-creator of CMM, PCMM, SVP & Chief Scientist of CAST Research Labs, Executive Director – Consortium for IT Software Quality, presided over the awards function as chief guest and honored the awardees and finalists.

Watts Humphrey Awards 2018 received 24 nominations from various organization such as WIPRO, Infosys, Cognizant, HCL, Virtusa, Intellect Design, Firstsource and Aricent . An eminent 5 member jury evaluated the 24 teams and selected

Final Top 3 Winners Cognizant selected as Winner followed by Infosys and Virtusa as 1st Runner Up and 2nd Runner Up respectively. The winner and runners were awarded grand plaque, cash awards, certificates, 1 year SPIN Chennai complementary membership, SPIN international conference tickets and a presentation slot at the Conference in 2019.

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018

INTERNATIONAL INDIAN ICON (3iii) Season II Grand Finale Chicago/Sandwich, IL: Gee Vision in association with Zee TV declared Season II INTERNATIONAL INDIAN ICONs during the grand finale held on November 24th at Redberri Convention Center, Sandwich IL. The winners were from a variety of category from almost all corners of the world. 3iii Season-II reached its culmination with two grand events on November 23rd,2018 and November 24th,2018. The grand Redberri Convention Center welcomed thousands of guests from all over the world.

The celebrity judges from Bollywood, Choreographer Longinus Fernandes and Music Composer Arko Pravo Mukherjee along with Dance Judge Prachi Jaitly and Singing Judge Vaishali Dhande mentored over hundred participants.

The participants who contested for the title of International Indian Icon Season-I 2017 and Season II 2018 raised the bar with their immaculate technique and talent. While the first season was focused on America and Canada, SeasonII had participants from UK, Europe, Canada and America for all categories.

International Indian Icon (3iii) has been taking over the world with its unique concept of first of its kind in any talent platform giving Indian overseas a muchneeded platform to showcase their talent.

It is envisioned as the world’s 1st on-line/onsite grand Indian reality show narrative over five seasons culminating at the end of the 5th season.

While the 1st season of 3iii was open to Talent across all residents of The United States of America and Canada in either of the three performance categories –Singing, Dance and Instruments, season II added five more categories and reached more countries. It is a platform of immense possibilities for artists around the world to showcase their skills to be evaluated by a team of Gee Panel of judges consisting of highly qualified and celebrated individuals from the field of performing arts as well as celebrity judges in the advanced stages of the competition.

Gee Vision organized the official launch of International Indian Icon Season II in Feb this year at Ashyana Banquets in the presence of Various distinguished comprising guests elected officials as well as community leaders. Season II Grand-finale had the honor of having various dignitaries to enjoy the cultural program.

Speaking about the event, Richard Olson, Mayor, City of Sandwich, IL. Invited at International Indian Icon to Redberri Convention Center.

He congratulated all the participants who are working hard to compete in this competition. Olson mentions, “Gee Vision has introduced a unique platform for global talent who can showcase their art in front of the whole world. I assure my full support to this unique effort by Gee Vision and wholeheartedly send my warm wishes for a successful Season II. I also, look forward to Season 561

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018

III next year and send my best compliments to the entire International Indian Icon Team.� 3iii is envisioned as the world’s 1st on-line/on-site a grand Indian reality show narrative over five seasons culminating at the end of the 5th season.

congratulated all the winners and invited everyone to join them in Season III. The beauty of the concept lies in NO restrictions at all. Anyone can participate from the declared countries. No age restriction. No language or any format restriction, anyone can play any type of instrument to take part in the competition. If any one likes Indian singing, dance or any instrument and have valid ID of the country they are living in, can participate in 3iii competition.

3iii advisory board thanked everyone who attended the grand events and encouraged Indian talent all over the world so that no talent is left behind to make use of this amazing opportunity of showcasing his/her talent to the world through 3iii to achieve dreams of their choice. The online and on-site talent show has won millions of hearts across the globe and we look forward to seeing its journey in the coming seasons.

3iii 2018 Season-II Winners:

The unique positioning of 3iii has proved to be the main focus of its success: no other platform in India or in the expat community has been designed to showcase talents amongst all forms of talent on a single stage.

Indian Americans, Canadians, Caribbean, European live in that part of the world where the industry of entertainment thrives unlike any around the globe. The entire core team

Singing: Sai Manasa Gadepalli Dancing: Aanya Sood Instruments: Swara Kadam Fashion Icon: Preethi Pagadala Acting: Siddh Jain I Got Talent: Meghana Basi

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International Computer Security Day 2018 The Computer Security Day Programme was held on 30 11 2018 by the Cyber Society of India (CySI) along with the Voice of Voiceless (VoV) at the Commissioner of Police Office Chennai. The Programme started at 09.30 AM with the Invocation Song “Tamil Thai Vazthu” rendered by Mr.M.P.R.Khader Mohideen.

Dignitaries were then welcomed with Flower Bouquets. “Cyber Security Day Pledge‟ was administered by Mr. Justice K. N. Basha which was followed by all the participants reaffirming to be a responsible Netizen.

Mr. Balu Swaminathan, President, CySI welcomed the dignitaries on the dais, the guests and invitees present. In his welcome address, he briefed about CySI and said that Computer Security Day Programme will create awareness amongst the citizens about the security aspects to be adopted by them and protect themselves from cyber-attacks and stressed the need for individual policing in Cyber Crime. He encouraged the attendees to understand the Caricature presented on Computer Security Day and made a special mention about the excellent support received from the Commissioner of Police and other Officers of the COP Office in conducting this Programme and thanked them profusely for the same. He then elaborated on the programme for the day and also appreciated the Speakers for readily accepting the invitation without any hesitation.

Mr. R Ramamurthy, Chairman, Cyber Security and Privacy Foundation delivered the Key Note address. He underlined the need for such programs, which will create awareness about the Cyber threats faced by the citizens and empower them to protect themselves from such attacks. He also emphasized that there should be no loopholes in the software and urged the need for strong and periodical software audits.

He spoke about the dearth of Cyber Security professionals in our Country as we at present have only around 60,000 Cyber Security Professionals against the requirement of around 4,00,000 Professionals and suggested formation of a Council for Cyber Society Professionals like the BAR Council etc.

Dr. A K Viswanathan, IPS, Commissioner of Police, Chennai in his Inaugural Address very impressively walked the audience through the Cyber Crimes taking place in the recent times.

He made a mention of growing Cyber Related Bank Frauds and wanted 2 citizens to protect themselves from fraudsters by following precautions. He wanted citizens to identify fraudulent websites, protect children by educating them and urged parents to periodically check their smart phones whether any unusual incidents are noticed. He also spoke about the fraudulent Job Rackets, Online shopping websites, the need to keep the passwords as secret and cited instances of persons impersonating as Bank Executives and 563

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018

seeking details. He then explained about various steps taken by the Police in Colleges and other Institutions about Cyber Security Awareness. He also cautioned citizens about hurting others in social media and concluded his address by saying that Computer Security Day will be useful in combating cybercrimes and creating greater awareness.

Information officer. He also elaborated on the C-DAC & CERT-IN and about commencing of CERT-TN by the Government of Tamilnadu and stressed that Cyber Security is National Security.  Mr. Justice (Retd) K N Basha, in his Special Address expressed happiness that a large number of Women Advocates are participating in the Programme and recalled that more than 10000 cases are registered on cyber related cases which shows the increasing awareness regarding cybercrimes. Stressing the need to update Computers with AntiVirus software, he briefed the audience with specific cases of people being victimized after luring them to reveal the password /OTP etc., He stressed the need for keeping password as secret and not to share the OTP with unknown persons. He made specific mention of the case of the State of Tamil Nadu Vs Suhas Katti, which is known for the first conviction under IT Act 2000 in India achieved successfully within a relatively quick time of seven months from the filing of the FIR in the year 2004 and went on to 3 appreciate Mr. S Balu, the President, CySI, who was the investigating officer handling that case then.

Mr. Nanda Kumar, Secretary, Voice of Voiceless (VoV) briefed the audience about VoV and its activities and also its association with Cyber Society of India. He gave details of the number of cases registered with reference to cyber Crimes.

Dr. Santhosh Babu, I.A.S., I.T. Secretary, Secretary to Govt. I. T. Department, TN in his Presidential Address expressed happiness about CySI & VoV joining hands to observe the International Computer Security Day with a pledge and informed that he would recommend to the Government to introduce Computer Security Day Pledge also among the other Pledges we take during the year. He suggested that citizens should watch some of the films of recent times{ like Irumbuthirai} which centers around about cybercrimes, to improve awareness He briefed about the I.T Security Policy being introduced by the Government and stressed the need for Cyber Security

The Inaugural Session came to an end with the singing of National Anthem.Then the program of day was started after Tea break. Mr. Nagarjoon, B.E. a budding Artist of Independent Artists Show rendered a song regarding Cyber Crime, which was well appreciated by the audience. Mr. S R Senthil Kumar, DC-CCB, Chennai gave a detailed presentation on the Cyber Crime scenario and advised that all the information on cybercrime should percolate to friends and relatives and touched on Skimmers, Google Map (Bug) Fraud and warned the citizens to be alert. He briefed the audience about the App “KAVALAN SOS” launched by Chennai Police and impressed upon the

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Citizens to make the best use of it by downloading in their smart phones.

Mr. Na Vijaya Shankar narrated the various laws and legal aspects relating to Information Technology. He highlighted the role of Police Officers and Software Professionals in combating cybercrime. He touched upon Cyber Stone Palters, Right to Privacy, Artificial Intelligence (AI) and touched upon Bitcoins, terming it as Currency of the Criminals. Mr. N Karthikeyan, Cyber Law Advocate and Life member of CySI, in his address informed that anyone can be a victim if proper cyber security precaution is not taken. He spoke about Cyber Civilization, Cyber Criminals and various solutions available for the users. He also took the audience through how Google works and touched upon Data Technology and emphasized not to get addicted to social media and allow it to decide our activities. He also briefed the audience about Digital Banking and its benefits. The brief Interaction session that followed witnessed active exchange of information and the audience well utilized the occasion to pick the brains of the learned dignitaries as many questions were responded well by the learned speakers.

various devices used by fraudsters for committing cybercrime and discussed with the help of case studies. She also presented the Fire Eye Cyber Threat Map for the benefit of the participants. The last session was by Mr. V Balu, Advocate, who explained to the receptive audience on such topics as Digital Slavery, Origin of Social Media Crimes, dangers of Smart phones, Dangers of Social Media, Dangers of WhatsApp, Face Book and emphasized the need to go through the Privacy Agreement before accepting the same and improve awareness on Technology.  Certificates to all the participants were distributed by Mr. R. Dhinakaran, Addl. CoP, L&O (North).

Dr. Kala Bhaskar, Director in Charge, Center for Cyber Forensics and Information Security, University of Madras, in her presentation touched upon Digital Forensics, Dark Web, Digital Evidence, various forms of Cyberattacks, Bit Coins etc. She also 4 elaborated on Computer Crimes, Computer Forensics,

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Mr V N Prem Anand , Secretary Cyber Society of India informed that the International Journal of Innovative Technology and Creative Engineering, United Kingdom, sponsors of the certificates, would cover the event in the next issue of their Journal, which is being distributed worldwide..

Mr. C Badri, Joint Secretary, CySI summed up the dayâ€&#x;s proceedings and the event concluded with Mr. Prem Anand, Secretary, CySI proposing the Vote of Thanks.

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CONNECTED VEHICLES Presentation by V N Prem Anand at Green Energy 2018

A few years ago, personal vehicle and fleet navigation was completely dependent on paper.

Digital maps have now come to stay and technology has completely revolutionized our world. Mapping the world on the internet rather than on paper has not only changed the way we navigate but also opened up various new business models.

Autonomous vehicles are being adopted with most manufacturers investing heavily to make their vehicles part of a connected world. Whether it is your own car or the truck that your business owns, all these are now becoming part of an expanding connected world.

Connectivity is becoming the key differentiator, changing the landscape of the entire fleet and logistics industry. Technological trends like Artificial Intelligence, Big data, and the Internet of Things (IoT) are transforming business processes, workflows, and business models. Technology is moving at unimaginable speed, bringing changes and creating challenges. It will be survival of the fittest for those who adapt to these technological advancements early can successfully compete in this changing ecosystem.

How to use this data? We can use the data to automatically process customer orders and schedule trips with optimal routes charted out mapping all your drop off locations, all these powered by Artificial Intelligence. Secure transportation of high-value goods or assure the condition of cargo in transit with real-time monitoring and report to customers. Increased efficiency of loading and unloading stations, warehouse operations, and manpower management with having visibility into ETA of consignment will become easy. To sum it up Digital Transformation will provide visibility into business processes and decision making.

The logistics and transport industry is becoming more innovative by leveraging on IoT based systems with next-gen technologies taking over and more machine learning becoming a reality. The fleet industry will . The entire industrial landscape is evolving and only the enterprises that are ready to embrace this change and develop adaptive environment can truly leverage the power of connected vehicles. Anything is possible with connected vehicles.

Data from the connected world empowers decisionmaking. It optimizes the business processes and makes operations smooth and effortless with statistical decisions and automated workflows.

Engineers will design innovative systems making machines, manpower, operations, and customers work cohesively through the use of technology.

Logistics is one such industry evolving under this influence and IoT is becoming the buzz word for digital transformation. Not long ago, knowing where your fleet is, and when it will arrive, had various unknowns. But today, you can actually track a cargo from its loading, while on transit, its condition along the way, optimize the route along the way, ensure it is secure with geo-fencing, and know exactly when it will get delivered. Data brings visibility into the process, reduces the unknowns, and increases efficiency.

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DESIGN AND IMPLEMENTATION OF INDUCTIVE POWER TRANSFER FOR EV BATTERY CHARGING V.AISHWARYA*, C.KAVITHA*, R. KAVIYA*, DR.R.SEYEZHAI** ,S.HARIKA*** UG Students*, Department of Electrical and Electronics Engineering, SSN College of Engineering, Chennai, India Associate Professor**, Research Scholar***, Renewable Energy Conversion Lab, Department of Electrical and Electronics Engineering, SSN College of Engineering, Chennai, India **seyezhair@ssn.edu.in, ***sriharkal@gmail.com

Abstract -- Leading to an increased consideration of clean and renewable alternatives to traditional technologies, the automotive industry has shown a growing interest in electric and hybrid electric vehicle (EV). However, the transition to all-electric transportation is now limited by the high cost of the vehicles, the limited range and the long charging time. Inductive Power Transfer (IPT) systems can be the solution to the range restrictions of EVs by charging the vehicle while driving and reducing required battery size as well as overall cost of the vehicle. These systems transfer electric energy from source to a load without any wired connection and it is achieved through the affordable inductive coupling between two coils termed as transmitter and receiver coil. This paper proposes a bridgeless Interleaved Boost Converter (IBC) as the front end converter for the IPT system. The compensation network and the Inductive coil is designed and simulation studies are carried out in MATLAB/SIMULINK. The functional parameters of bridgeless topology is compared with the conventional bridged configuration. The hardware of the Bridgeless IBC, Inverter and Compensation network is implemented and the results are verified.

Keywords: EV, IPT, IBC.

I.

be automated more easily as there is no wire to move and no connection to be made. It could be safer as users do not handle high power cables. It could be less prone to wear as there is no connector to plug and unplug. It could also be less prone to damage from weather conditions and vandalism due to all components being embedded / concealed. These characteristics makes wireless charging more robust and easier to deploy in dirty and wet environments, compared to wired charging [3].

Due to these advantages, WPT also offers the possibility to charge an EV on the road, during both stopped or moving condition, by embedding the charger transmitter under the road surface [4]. IPT is a type of wireless power transfer that employs the induction of electricity by a changing magnetic field. In a typical setup, a transmitter coil is placed on/in the ground, powered by a high frequency inverter to generate an alternating magnetic field [5]. A receiver coil, mounted on the bottom of the vehicle, is then positioned above the transmitter coil such that the alternating magnetic field induces electricity in the receiver coil. Power is then transferred through a rectifier to the battery charger to charge the battery of the vehicle.

INTRODUCTION

With the rapid depletion in conventional sources of energy and the dramatic increase in the pollution level due to burning of fossil fuels, there is a need to adopt alternative energy sources. The conventional petrol and diesel vehicles are one of the major sources of air pollution, as burning fossil fuel releases a lot of toxic fumes. Electric Vehicle and Hybrid Electric Vehicle is an attractive solution to this problem. The EV is powered exclusively by electricity which uses energy stored in its rechargeable batteries [1]. Electrical energy has the advantage of the ease of transmission and is also a clean form of energy. One of the challenges in using EVs is refuelling. A battery-powered car would need to charge for several hours, usually overnight and yet the range would still be less than a petrol fuelled car.

WPT technology can be used to charge EVs without the use of wires, which has a number of advantages as opposed to wired charging [2]. The charging process can

II.

ANALYSIS OF DIFFERENT CONVERTER TOPOLOGIES FOR IPT

Boost converter is a popular option for most of the power electronic systems by serving as a pre-regulator due to its simplicity in design and high performance.

There are different types of DC-DC boost converters that can be used for EV battery charging application. In this paper, the comparative analysis of traditional boost converter, bridged and bridgeless IBC converter is carried out [6]. A simple boost converter or a step-up converter is a DC- DC power converter where the output voltage is greater than the input voltage. It belongs to a class of Switched Mode Power Supply (SMPS) comprising of semiconductor elements; diode and transistor and an energy storage element such as inductor or capacitor or a combination of the two. Filters consisting of capacitors or inductors are added at the output of the converter in order to lessen the output voltage ripple.

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 However, as the power rating increases, it is necessary to connect converters in series or parallel [7]. In high power rating application, interleaving of boost converters is usually employed to improve the converter performance and also to partially reduce the input current, output voltage and inductor current ripple and step down the converter size effectively. As interleaving doubles the switching frequency and effectively reduce the ripple at the input current and output voltage, the size of energy storage elements also significantly reduces [8].

Additionally, it improves the transient response and increases the voltage gain of the converter. From the analysis, it is observed that there are different types of interleaved boost converter topologies such as conventional bridged IBC, bridgeless IBC. In bridged IBC, the two phase interleaved boost converter consists of two identical boost converters connected in parallel. The two switches are alternatively switched with both the switches having the same frequency. In bridgeless IBC, additional two switches and inductors are required compared to bridged topology. A bridgeless interleaved boost converter eliminates the bridge rectifier employed in the conventional topology.

This reduces the losses due to the presence of the diodes in the bridge rectifier [9]. Although it introduces some new losses due to the presence of additional switches and inductors, the efficiency of the bridgeless topology is better, as the losses due to the bridge rectifier is very large. Also, the THD of the current is reduced and the power factor is improved.

III.

Fig.1 Output Voltage Ripple

Fig.2 Output Current Ripple

The comparison shows that the ripple is reduced in the case of an IBC and that ripple reduction is maximised at a duty ratio of 50%. Then the conventional bridged IBC is compared with the bridgeless IBC. The ripple analysis between conventional IBC and proposed bridged IBC is shown in Figs 3-Figs 4.

SIMULATION RESULTS

The three topologies of boost converter, namely the conventional boost converter, interleaved boost converter and bridgeless interleaved boost converter were simulated in MATLAB/Simulink. The performance parameters such as the output voltage and current ripple, supply current THD and power factor of the three converters are analysed and compared. The power loss and efficiency analysis of the IBC and bridgeless IBC are also analysed. The ripple analysis between boost and conventional IBC is shown in Figs 1-Figs 2.

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Fig.3 Output Voltage Ripple

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Fig.4 Output Current Ripple

From the results, it is observed that the proposed bridgeless interleaved boost converter has reduced output voltage and output current ripple compared to existing topologies. The performance parameter such as THD, distortion factor, displacement factor and power factor is evaluated and compared between bridged and bridgeless converter and the results are depicted in Table I.

Fig.5 IPT system for battery charging

TABLE. I POWER FACTOR AND THD COMPARISON BETWEEN BRIDGED AND BRIDGELESS IBC

Topology Bridged Interleaved Boost Converter Bridgeless Interleaved Boost Converter

THD Distortion (%) Factor

Displacement Power Factor Factor

99.19 0.7100

0.9900

0.7029

31.33

0.9998

0.9541

0.9542

Fig.6. Output Voltage of Bridged IBC

From Table I, it is observed that the proposed bridgeless IBC has low THD and high power factor. Thus the proposed topology is best candidate for IPT system. The Simulink diagram of the IPT system incorporating proposed IBC is shown in Fig.5. The output voltage and output current waveform of the proposed IBC and FFT analysis of the supply current is shown in Figs. 6-Figs.8.

Fig.7. Output Current of Bridged IBC

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Fig.8 FFT Analysis of Supply Current

The input voltage of 24V is boosted to 48 V and output current of 0.3A is achieved as depicted in Figs.6 - Figs.7.

From Fig.8, it is observed that the THD of supply current is reduced to 31.33%.

I.

HARDWARE RESULTS

The experimental setup of wireless charger incorporating proposed bridgeless IBC is built and shown in Fig.9. The input of 6.3 V dc is converted to 4.76V ac voltage and transformed to the secondary side of wireless charger . The output voltage waveform of the secondary side is shown in Fig.10.

Inverter

Fig.10 Secondary Output Waveform

II.

CONCLUSION

The three boost converter topologies, namely, the Conventional Boost converter, Bridged Interleaved Boost Converter and Bridgeless Interleaved Boost Converter were simulated using MATLAB. Various performance parameters of the topologies such as output voltage and current ripple, THD, input current power factor and efficiency were analysed and compared. Comparison graphs were plotted for these parameters. It was observed that the Bridgeless interleaved boost converter offered better performance in terms of higher power factor, lower THD, better efficiency, improved RMS value of current for inductor, MOSFET and the fast diode. The efficiency was found to be increasing with load. Also the RMS value of current for inductor, MOSFET and the fast diode was found to be decreasing with increase in load.

Hence, the bridgeless interleaved boost converter is widely preferred for applications which require higher power factor and increased efficiency.

The compensation network and the Inductive coil was designed for Wireless Power Transfer. The hardware of the Bridgeless IBC, Inverter and Compensation network was implemented and the results were verified.

Bridgeless IBC

Fig.9 Hardware implementation of inductive power transfer

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 REFERENCES 1. Chun Qiu, K. T. Chau, Tze Wood Ching, Chunhua Liu (2014) „Overview of Wireless Charging Technologies for Electric Vehicles‟, Journal of Asian Electric Vehicles, Volume 12, Number 1.

2. Fariborz Musavi, Wilson Eberle, William G. Dunford (2011) „A HighPerformance Single-Phase Bridgeless Interleaved PFC Converter for Plug-in Hybrid Electric Vehicle Battery Chargers‟, IEEE Transactions on Industry Applications, Vol. 47, No. 4.

3. Ivan Luigi Spano, Andrea Mocci, Alessandro Serpi, Ignazio Marongiu, Gianluca Gatto (2014) „Performance and EMC Analysis of an Interleaved PFC Boost Converter Topology‟, 49th International Universities Power Engineering Conference (UPEC), pp. 1-6.

4. Luciano S. C e Silva, Falcondes J.M. de Seixas, Priscila da S. Oliveira (2012) "Experimental evaluation of the bridgeless interleaved boost PFC converter‟,10th IEEE/IAS International Conference on Industry Applications (INDUSCON), pp. 5-7.

5. Lukic. S, Z. Pantic (2013) „Cutting the Cord: Static and Dynamic Inductive Wireless Charging of Electric Vehicles‟, IEEE Electrification Magazine, Vol. 1, pp. 57-64.

6. Mihaela-Codruta Ancuti, Marcus Svoboda, Sorin Musuroi, Alexandru Hedes (2014) „Boost interleaved PFC versus bridgeless boost interleaved PFC converter performance/efficiency analysis‟, Proceedings of International Conference Applied and Theoretical Electricity (ICATE).

7. Mounica Ganta , Pallam reddy Nirupa, Thimmadi Akshitha, Dr Seyezhai R (2012) „Simple And Efficient Implementation Of TwoPhase Interleaved Boost Converter For Renewable Energy Source „,International Journal of Emerging Technology and Advanced Engineering, Volume 2, Issue 4.

8. Pierre Magne, Ping Liu, Berker Bilgin and Ali Emadi (2015) „Investigation of number of phases in Interleaved DC-DC Boost converter‟, Transportation Electrification conference and Expo (ITEC).

9. Robin Tanzania (2016) „Design of Wireless Power Transfer Coils to Minimise Capacitor Stress and AC Resistance‟. Retrieved from database name https://repository.ntu.edu.sg/handle/10356/66032

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Grey Wolf Optimization Algorithm for Generation Rescheduling In Deregulated Power System for Congestion Management Pawan C. Tapre1 Department of Electrical Engineering CVRU, Ph.D. Scholar Bilaspur (C.G.), India pawan.tapre25@rediffmail.com

Dr. Dharmendra kumar Singh2 Department of Electronics Engineering Associate Professor, CVRU, Bilaspur (C.G.),India dmsingh2001@rediffmail.com

Dr. Sudhir Paraskar3 Department of Electrical Engineering, Professor, SSGMCE, Shegaon(M.S.), India srparaskar@gmail.com

Abstract— The practitioners and researchers has received considerable attention solving complex optimization problems with metaheuristic algorithms during the past decade. Many of these algorithms are inspired by various phenomena of nature. One of the promising solutions for secure and continuous power flow in the transmission line is rescheduling based congestion management approach but the base problem is rescheduling cost.. To solve the congestion with minimized rescheduling cost , a new population based algorithm, the Grey Wolf Optimization (GWO ) Algorithm, is introduced in this paper . The basic motivation for development of this optimization algorithm is based on special lifestyle of grey wolf and their cooperation characteristics. Based on some benchmark Grey Wolf Optimization(GWO) Algorithm is compared with the existing conventional algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Artificial Bee Colony (ABC), and Firefly (FF) by analyzing the convergence, cost, and congestion. In IEEE-14 and IEEE-30 bus system experimental investigation is carried out and the obtained results by the proposed algorithm GWO (Grey Wolf Optimization ) Algorithm in comparison to the other algorithms used in this paper.

Keywords— Rescheduling; Congestion Management; Optimization Algorithm; GWO, flexible AC transmission systems.

1. Introduction Restructuring of the electricity supply industries is a very complex exercise based on national energy strategies and policies, macroeconomic developments and national conditions, and its application varies from country to country . It is important to point out that there is no single solution applicable to all countries and there is a broad range of diverse trends. Liberalization, deregulation (or reregulation) and privatization are all processes under the general label of market reform.

Reregulation is a more accurate term than deregulation. Privatization is the sale of government assets to the private sector, by itself, privatization is not sufficient to introduce competition into a reformed sector . Competition will be the result of careful regulation of the privatized entities to allow new entrants access to the market. Competition is fundamental to most market reforms and it is introduced in order to reduce costs and increase efficiency. There is considerable variation in the extent of the competition which is introduced.

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 The changes were initiated by: " a realization that generation and distribution functions need not be monopolies;

electricity to a number of competing customers (loads).

Here we are concerned with competition in a wholesale electricity. Here some of these challenges are outlined.

" a feeling that public service obligations are no longer necessary ; " the cost reduction potential of competition ; " increased fuel availability and fuel supply stability; and " the development of new technologies in power generation and information technology.

1.1 Previous Power System In the past, power systems were developed to transmit large amounts of power at high voltage from remote generating stations and to distribute power at lower voltage down to millions of small consumers .

Deregulation has led the electricity industry to focus attention on the costs of generation and provides incentives for generators to reduce their costs and minimize their risks, e.g. by investing in smaller scale plants .

1.2 Congestion The implementation of deregulation is further complicated by the presence of congestion. Congestion refers to the binding of thermal limits of the transmission network .

Congestion can be relieved by re-dispatch of generators.

In the traditional power system, the utility can achieve that by re-dispatching the cheapest generator(s) available while alleviating the constraints . In the deregulated environment, generation and transmission fall into different entities .

2 Challenges Electricity markets throughout the world are undergoing major changes [1} . These changes are varied in their nature but the underlying trend is towards a more competitive and open environment and this results in electricity being traded as a commodity and in the creation of competitive markets to facilitate this trade.

Political forces [2,3] are driving these changes . A competitive electricity market is one in which a number of suppliers (generators) are competing to sell their

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2.1 Market Power Evaluation and Mitigation Evaluation of market models can have many different viewpoints. The market must function in a reliable, efficient and fair manner. The generators will want to maximize their profits through the markets . The consumers will seek the best value for the service they receive which may conflict with the aims of the generators [4]. This will necessitate analysing the social benefit that the market offers and the prices that are charged . It will also be prudent to ensure that market power and gaming do not exist and that markets are not overly volatile.

2.2 System Capacity The issue of planning in generation and transmission must be addressed with a view to maintenance and enhancements to meet increasing demand. On the generation side these functions are generally left to the market, the assumption being that energy prices will signal the best times to maintain units and when to build new plant. A market for generating capacity over a longer time frame (more than one year) may provide the necessary market signals to ensure that the system will expand according to the needs of the consumers [5].

2.3 Reliability While it is desirable to encourage competition in the electricity market to reduce the costs and improve the service quality for consumers, it is also vitally important to maintain the system reliability [6]. In an operational environment, an important reliability measure is system security. System security refers to a system's ability to withstand likely disturbances . A system is said to be in a secure state if it is able to meet the load demand without violating the operating constraints in case of a likely contingency, such as a line or generator outage [7]. In other words, security is defined with respect to a set of next contingencies that

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 are likely to occur. Consequently, a system engineer at the ISO who studies system security may find it difficult to predict the future generation and load conditions for evaluation of system security .

(4) Regulated rates: The electric utility's rates were either set or regulated in accordance with government regulatory rules and guidelines.

2.4 Technical Issues (5) Guaranteed rate of return: Regardless of wholesale electricity markets power system planning and operation has many technical challenges. The OPF algorithm which is at the heart of the marginal cost pricing paradigm [8] and of power system security analysis will have to meet everincreasing challenges [9]. However, any actions need to allow market forces to push the industry towards possible long-term competitive solutions.

The government guaranteed that regulated rates would provide the electric utility with a ,reasonable' or `fair' profit margin above its cost.

(6) Least cost operation : The electric utility was required to operate in a manner that minimized overall revenue requirements .

3. The Traditional Power Industry

3.1 Motivations for Restructuring the Power Industry

The electricity supply industry in nearly every country for about the last hundred years has been a natural monopoly and as a monopoly attracted regulation by government. Without exception, the industry has been operated as a vertically integrated regulated monopoly that owned the generation, transmission and distribution facilities. It was also a local monopoly, in the sense that in any area one company or government agency sold electric power and services to all customers . In many countries, especially developing countries, the electric utility was owned by the state or local government, and in other countries, by an investor-owned private entity . The traditional power industry had several characteristics [10] :

Since the 1980s, the electricity supply industry has been undergoing rapid and irreversible change reshaping an industry that for a long time has been remarkably stable and had served the public well. A significant feature of these changes is to allow for competition among generators and to create market conditions in the industry, which are seen as necessary to reduce the costs of energy production and distribution, eliminate certain inefficiencies, shed labour and increase customer choice . This transition towards a competitive power market is commonly referred to as electricity supply industry restructuring or deregulation.

(1) Monopoly franchise :

3.2 Components of Restructured Systems

Only the national or local electric utility was permitted to produce, transmit, distribute and sell commercial electric power within its service territory.

The structural components representing various segments of the electricity market are generation companies (Gencos), distribution companies (Discos), scheduling coordinators (SCs), transmission owners (TOs), an independent system operator (ISO), and a power exchange (PX). Depending on the structure and the regulatory framework, some of these components may be consolidated together, or may be further unbundled.

(2) Obligation to serve: The utility had to provide electricity for the needs of all consumers in its service area, not just those that were profitable.

(3) Regulatory oversight : The utility's business and operating practices had to conform to guidelines and rules set down by government regulators.

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3.2.1 Gencos

3.2.5 Independent System Operator (ISO)

Gencos are responsible for operating and maintaining generating plant in the generation sector and in most of cases are the owners of the plant. Open transmission access allows Gencos to access the transmission network without distinction and to compete.

The ISO is the supreme entity in the control of the transmission system. The basic requirement of an ISO is disassociation from all market participants and absence from any financial interest in the generation and distribution business . However, there is no requirement, in the context of open access, to separate transmission ownership and operation.

3.2.2 BOT Plant Operators and Contracted IPPs Build, operate and transfer BOT; (or build, operate and own) plant or IPPs who have longterm contracts with surrounding, usually national, utilities play an important role in providing additional generation in many fastgrowing systems . Take-or-pay power purchase agreements are often in force as an economic incentive to investors.

3.2.3 Discos and Retailers Discos assume the same responsibility on the distribution side as in a traditional supply utility . However, a trend in deregulation is that Discos may now be restricted to maintaining the distribution network and providing facilities for electricity delivery while retailers are separated from Discos and provide electric energy sales to end consumers . Another trend in developing countries is to sell to an investor, or to corporatize, portions of the distribution system so that investment for reinforcement can be raised and better operating practices implemented.

3.2.6 Power Exchange (PX) The PX handles the electric power pool, which provides a forum to match electric energy supply and demand based on bid prices . The time horizon of the pool market may range from half an hour to a week or longer . The most usual is the day-ahead market to facilitate energy trading one day before each operating day. An hour-ahead market is also useful since it provides additional opportunities for energy trading to redress short-term imbalance .

3.2.7 Scheduling Coordinators (SCs) SCs aggregate participants in the energy trade and are free to use protocols that may differ from pool rules. In other words, market participants may enter an SC's market under the SC's rules and this could give rise to different market strategies.

3.3 PX and ISO : Functions and Responsibilities

3.2.4 Transmission Owners (TOs) Where the transmission network was state owned before restructuring, obviously this integrity will be retained and a distinction between owner and operator is redundant. A basic premise of open transmission access is that transmission operators treat all users on a nondiscriminatory basis in respect of access and use of services. This requirement cannot be ensured if transmission owners have financial interests in energy generation or supply. A requirement, therefore, is to designate an independent system operator to operate the transmission system.

3.3.1 PX Functions and Responsibilities A PX of some form is essential for efficient trading in electricity . The PX establishes an environment in which generators and consumers bid to sell and buy energy.

Parties to bilateral contracts can operate their own separate energy trades and schedule their transactions outside the PX's market. The primary function of the PX is to provide a forum to match electric energy supply and demand in the current and forward energy markets . In its simplest form a PX provides a bulletin board type of environment for energy suppliers and energy customers to engage in bilateral forward contracts . However, the

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 more usual function is to act as a pool for energy supply and demand bids, and to establish a market-clearing price (MCP).

" Conduct physical network operations and network switching " Deal with outages and emergencies .

Basically, the working process of the PX is: " Coordinate real-time system operation .

(1) receive bids from power producers and customers ; (2) match the bids, decide the MCP prepare scheduling plan; (3) provide schedules to the ISO or transmission system operators ; (4) adjust the scheduling plan when the transmission system is congested.

(1) Power market administration function : There are two types of energy markets : the pool market and the contract (bilateral and multilateral transactions) market. The former could be run by the PX or an ISO-PX combine while the latter may be coordinated by one or more SCs. The pool market includes :

3.3.2 ISO Functions and Responsibilities The ISO has three objectives: security maintenance, service quality assurance and promotion of economic efficiency and equity[5].

" Run a power pool where parties can bid to buy and sell energy. " Develop a preferred schedule for the pool.

To achieve these objectives the ISO performs one or more ofthe following functions :

" Submit the supply and load schedule to the ISO according to pre-specified protocols

(1) Power system operations function : This fundamental function includes the operationplanning function and real-time control.

The contract market includes :

The operation-planning function includes :

" Manage and coordinate submissions from SCs.

" Perform power system scheduling.

" Submit preferred schedules to the ISO according to prespecified protocols .

" Manage bilateral and multilateral transactions.

" Co-ordinate with energy markets . " Perform power system dispatch .

(2) Ancillary services provision function : " Own certain ancillary services for satisfactory grid operation

" Determine available transfer capabilities (ATCs). " Determine real-time ATCs. " Pre-calculate short-run costs transmission-related services.

and

prices

for

" Purchase ancillary services transactions from market participants according to prespecified protocols. " Provide ancillary services to transmission users.

" Calculate services.

hourly prices

for

transmission-related " Allocate costs of ancillary services among all users.

Real-time control includes : " Monitor power system operation status . " Monitor system security .

577

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 (3) Transmission facilities provision function : " Maintain the transmission network.

Where Vi, Vj → Voltage Magnitude at Bus i and Bus j

" Provide transmission facilities for all supplies and loads.

Gij → Conductance in the Line i-j " Plan transmission, reactive power and FACTS expansion and ensure that resources for future investment are generated.

δi ,δj → Voltage Angle in the Bus i and Bus j nl → Total Numbers of Transmission Lines

" Plan and commission own ancillary services.

4.1.2 Voltage Deviation Minimization 4. OPF Problem Formulation OPF is a nonlinear optimization problem the objective functions (f (x, u)) optimized using equality constraints (g (x, u)) and inequality constraints (h(x, u)), that is used to find the best control variables (u) and state variables (x).

The general form of OPF problem can be expressed as follows:

The voltage gap between the reference voltage and load bus voltage is less means the voltage deviation get minimized. It can be mathematically expressed as.

FVD =Min VD=∑NL đ?‘–=1(Vi – Vi ref)

(6)

Minimize: f (x, u)

(1)

Subject to: g (x, u) = 0

(2)

Where, �ir�� is specified reference voltage at bus i, which is taken as 1.0 p.u.

h(x, u) ≤ 0

(3)

NL- no. of load buses.

4.1 Problem Objectives

4.1.3 Problem Constraints

Generation Cost Minimization

The list of equality constraints and inequality constraints are below.

Minimization of generation cost (FG) in a power generation is expressed with the cost coefficients are ai, bi and ci,

Equality Constraints

FG =Min Gcost= ∑NG đ?‘–=1(aiPgi ² + biPgi + ci )

Equality constraints of the given objective functions are

(4) PGi–PDi=

Bij sin(δi − δj)]

4.1.1 Real Power Loss Minimization Due to the transaction between generator node and demand node, the real power and reactive power losses produced in the transmission lines. Our aim is to minimize the losses in the power system network. The objective is to minimize the real power loss (FPL) in the transmission line is expressed as FPL= Min Ploss = ∑đ?‘›đ?‘™ đ?‘–=1 Gij (Vi² + Vj² − 2ViVj cos(δi – δj )

Vi

(5)

QGi–QDi=

Vi

Bij sin(δi − δj)]

∑đ?‘ đ??ľ j=1 Vj[Gij cos(δi − δ NBj = 1 j) + (7) ∑đ?‘ đ??ľ j=1 Vj[Gij cos(δi − δ NBj = 1 j) + (8)

PGi, QGi→ real power & reactive power generations at bus i.

PDj,QDi→ real power and reactive power demands at bus i.

578

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 Gij →Conductance in between the line i-j

Voltage Level at a load bus is maintained within a specific upper and lower limit (0.9-1.1)pu, determined by the operator.

Bij → Susceptance in between the line i-j i → 1 to NB, NB →total numbers of bus.

Vimin ≤ Vi ≤ Vimax ;

Inequality Constraints

The control variables used in the OPF problem is generator real power settings (PGi) and voltage settings(VGi), transformer tap settings (Ti),reactive power compensation setting(Qci). đ?‘‰PQđ?‘–đ?‘– voltage at PQ bus, đ?‘†đ??żđ?‘˜ is kth line apparent power. max and min represents maximum and minimum control variables value. Total Numbers of Generators (NG), Transformers (NT), Switchable VAR Sources (NC), and PQ Buses (NPQ).

Inequality constraints of the given objective functions are

min max PGi ≤ PGi ≤ PGi , (9)

i= 1,2,‌.,NG

min max VGi ≤ VGi ≤ VGi , (10)

i= 1,2,‌.,NG

Timin ≤ Ti ≤ Timax , (11)

i= 1,2,‌.,NT

Qmin ci

≤ Q ci ≤

Qmax ci

, i= 1,2,‌.,NC

i=1,2,‌.NPQ

(20)

4.1.4 Line Loading (LL) Line loading minimization is to optimize the power flow of each line within a limit and minimize the line overloading objective function. It is used to minimize the power flow gap between actual values and limit value and expressed as:

(12)

min max VPQi ≤ VPQi ≤ VPQi , i= 1,2,‌.,NPQ

(13)

max Qmin Gi ≤ Q Gi ≤ Q Gi ,

i= 1,2,‌.,NG

(14)

max min SLK ≤ SLK ≤ SLK ,

i= 1,2,‌.,NE

(15)

2 Min LL = ∑NL đ?‘–=1(Pij(t) − Pijmax)

The real power flow in a transmission lines is maintained below limit.

(21)

Here NL total number of lines LL- Line loading

Pijmin ≤ Pijmax ;

i=1,2,‌.NB; j=1,2,‌.NB;

Pij Power flow in each lines

(18)

Pijmax Maximum power flow limit in each line Where, Pij real power flow at branch i-j. , đ?‘ƒđ?‘–j max maximum power flow limit(MW)

Pij = Vi [Gij(Vi – Vjcosϴij) - BijVjsinϴij]

(19)

4.1.5 N-1 Contingency Analysis in Power System Using Severity Index (SI) Severity Index used to find out the worst line outage based on the N-1contingency analysis, that can be expressed as

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 ovl

SI =

∑

k=1

(

Pk Pkmax

)

5.1.2 Social Hierarchy

(22)

While modeling the GWO social hierarchy, the fittest solution in the grey wolves is alpha (ι). The second best solution is beta (β), the third best is delta (δ) and the rest is omega (ω) wolves. In the GWO algorithm the hunting mechanism is done by ι, β, and δ wolves, the remaining ω wolves followed by these three wolves.

Where Pk = Power flow in line k (MW) Pkmax = Power flowmax limit in line k (MW) Ovl is the set of overloaded lines, m as a weight coefficient.

5.1.3 Encircling Prey The position vector of prey Xp , position vector of grey wolf X and the coefficient vectors A and C and current iteration t now the mathematical model of grey wolves encircling prey during the hunt can be written as

5. Proposed Approach for Congestion Management Here the two methods used to solve the CM problem that is conventional method and non-conventional method.

The MATLAB used for conventional method and the intelligent technique like GWO used to optimize the OPF problem.

D= ǀ C.Xp (t)-X(t) ǀ

(23)

X(t+1)=ǀ Xp – A.D ǀ

(24)

5.1 Grey Wolf Optimizer (GWO)

The A and C can be calculated as;

5.1.1 Source of Inspiration

A = 2a.r1-a

(25)

GWO is a typical swarm-intelligence algorithm which is inspired from the leadership hierarchy and hunting mechanism of grey wolves in nature14. In the hierarchy of GWO, alpha (��) is considered the most dominating member among the group leader and decision maker.

The rest of the subordinates to đ?›źđ?›źare beta (đ?›˝đ?›˝) and delta (đ?›żđ?›ż) which help to control the majority of wolves in the hierarchy that are considered as omega (đ?œ”đ?œ”). The đ?œ”đ?œ”wolves are of lowest ranking in the hierarchy.

C = 2.r2

(26)

The mathematical model of hunting mechanism of grey wolves consists of the following:

Dι = ǀ C1.Xι – X ǀ

(27)

Dβ = ǀ C2.Xβ – X ǀ

(28)

Dδ = ǀ C3.Xδ – X ǀ

(29)

X1 = Xι – A1.( Dι )

(30)

X2 = Xβ – A2.( Dβ )

(31)

X3 = Xδ – A3.( Dδ )

(32)

1. Tracking, chasing, and approaching the prey.

2. Pursuing, encircling, and harassing the prey until it stops moving.

3. Attacking the prey.

Where a values in the iterations are normally decreased from 2 to 0, random vectors r1 and r2 are in [0, 1].

5.1.4 Hunting Grey wolfs hunting behavior is modeled with ι, β, and δ wolves knows the knowledge about the prey position and updated their position, the equations are shown below.

X (t+1) =

580

(đ?‘‹1+đ?‘‹2+đ?‘‹3) 3

(33)

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 5.1.5 Attacking the Prey ALGORITHM 1: GWO based mutation process In GWO algorithm when the hunting process finished by attack the prey. It is stated mathematically to decrease the vector value from 2 to 0. If |A| <1 the grey wolves force to attack the prey.

Initialize

Max

L Population

parameter a , Z and X ,

size,

iteration

Set t : 0 (counter initialization)

5.1.6 Search for the Prey (Exploration)

for  j  1 : j  b do

The grey wolves are search for a prey based on the position of α, β, and δ. They diverged from each other wolves to search for the prey and converged to attack the prey. If |A| >1 grey wolves force to search the better prey..

Develop an arbitrary initial population X j v 

 

Evaluate the fitness function f X j

5.1.7 Grey Wolf Optimizer In GWO the value of (a) decreases linearly from 2 to 0 .By update the value of (a) in a search space and update equation as follows:

End for

a=2(1- t2 /T2)

repeat

Assign X   , X    , the first and second best solutions

(34)

for  j  1 : j  L do

Where T indicates the maximum number of iterations and t is the current iteration. Using this exponential decay function, the numbers of iterations used for exploration and exploitation are 70% and 30%, respectively.

Updating the search agent in population Minimize the parameter a from 2 to 0 Update Z and X Calculate the fitness function of each search agent

The GWO parameters taken in the problem is population size (N) 25, Maximum iteration (T) 100 and total number of runs 1.

f X j 

6. The Pseudo Code of GWO Algorithm 1. Generate initial search agents Xi (i=1, 2,…., n) 2. Initialize the vector’s a, A and C 3. Estimate the fitness value of each hunt agent Xα =the best hunt agent Xβ =the second best hunt agent Xδ =the third best hunt agent 4. Iter=1 5. repeat 6. for i=1: Xs (grey wolf pack size) Renew the location of the current hunt agent using Equation (7).

End for 7. Estimate the fitness value of all hunt agents 8. Update the value of Xα, Xβ, Xδ 9. Update the vectors a, A and C 10. Iter=Iter+1 11. until Iter>= maximum number of iterations {Stopping criteria} 12. output Xα, End

End for Update the vectors X   and X    set t

 t 1 until

t  Max

iteration



Generate the best solution X  

7. Results and Discussion

581

7.1 Experimental Setup The implementation of the proposed congestion management system, which is based on rescheduling strategy, is established in the operational platform of MATLAB. The investigation takes place in IEEE benchmark test bus systems like IEEE 14 bus system and IEEE 30 bus system. The system comprises loads, capacitor banks, transmission lines, and generators.

Three GENCOs are connected in IEEE 14 bus system,

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 and six GENCOs are connected in IEEE 30 bus system.

Consequently, Table I and II summarize the generation limits as well as cost coefficients of both IEEE 14 bus system and IEEE 30 bus system. Further, the performance of proposed GWO rescheduling approach is compared to other existing approaches like PSO [32], GA [33], ABC [34], FF [35], and Proposed GWO [36] respectively in terms of various analysis such as cost analysis, congestion analysis and convergence analysis.

Methods PSO[32] GA [33] ABC[34] FF[35] GWO[36]

Congestion cost ($) 14.49477

Compensation cost ($) 809.0968

Final cost ($) 22.58574

14.47597

824.9463

22.72544

9.395873

1119.105

20.58692

9.396742

1116.117

20.55791

2.548434

1206.484

14.61327

strategy has drastically minimized the final rescheduling cost when compared to other models, which is showing its performance level over other models. It is reviewed that the proposed GWO rescheduling strategy is 35.71%, 35.31% 28.93% and 29.03%, better than FF based rescheduling strategy, ABC based rescheduling strategy, GA based rescheduling strategy and PSO based rescheduling strategy, respectively.

In the same way, Table IV reviews the congestion cost, compensation cost and final cost that sustained by proposed GWO rescheduling strategy over other conventional algorithms of IEEE 30 bus system. It is observed that the proposed GWO rescheduling strategy is 2.18%, 1.46%, 4.15%, and 2.20% superior to FF-based rescheduling strategy, GA-based rescheduling strategy and PSO-based rescheduling strategy respectively.

Compensa tion cost ($)

Final cost ($)

PSO[32]

Cong estio n cost ($) 33

365.8715

36.65871

GA [33]

33

578.7387

38.78739

ABC[34]

33

285.8715

35.85871

FF[35]

33

327.8771

36.27877

GWO[36]

33

376.504

34.76504

Pimin (MW)

Pimax (MW)

ai ($/MWhr)

bi ($/MWhr)

ci ($/hr)

1 2 3

10 20 20

160 80 50

0.005 0.005 0.005

2.450 3.510 3.890

105.00 44.100 40.600

Table-III Cost analysis of Proposed GWO based rescheduling strategy over existing models of IEEE-14 bus system

Table-I Generation limits and cost coefficients of IEEE-14 bus system Methods

Generator number

Generat or number

Pimin (MW)

Pimax (MW)

ai ($/MWhr )

bi ($/M Whr)

ci ($/hr)

1

50

200

0.00375

2.00

0

2 3 4 5 6

20 15 10 10 12

80 50 35 30 40

0.01750 0.06250 0.00834 0.02500 0.02500

1.75 1.00 3.25 3.00 3.00

0 0 0 0 0

Table-IV Cost analysis of Proposed GWO based rescheduling strategy over existing models

7.2 Cost Analysis

The related relationship among each rescheduling costs like congestion cost, compensation cost and final cost under the performance of proposed GWO rescheduling strategy over the other conventional strategies are summarized in Table III and IV, respectively. Table III specifies the attained congestion cost, compensation cost and final cost of proposed GWO rescheduling strategy over other existing methods of IEEE 14 bus system. From the analysis, it is observed that the proposed GWO

7.3 Convergence Analysis Fig.1 illustrates the convergence analysis of offered finest congestion management system over other existing models of both IEEE bus systems. All approaches are analyzed by specifying the capability of reducing cost function in correspondence with count of iterations. In IEEE 14 bus system, the rescheduling cost incurred by proposed GWO is tremendously lower than the conventional algorithms such as PSO, GA, ABC, FF respectively. Primarily, the cost function is identified to be at the topmost level, and then it gets minimized as the number of iterations increases.

582

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 The same minimization of cost is also observed in IEEE 30 bus system, which shows the betterment of the offered model over other models in terms of minimized rescheduling cost. More particularly, the rescheduling strategy with diminished cost is witnessed at the final iteration (100th iteration). From the analysis on IEEE 14 bus system, it is observed that the proposed GWO recognition system is 38.36%, 30.24%, 29.20%, 27.92%, better than FF, ABC, GA, and PSO, respectively. While analyzing the IEEE 30 bus system, it is reviewed that the recognition cost incurred by GWO algorithm is 0.81%, 1.08%, 0.27%, and 1.83% better than other existing approaches like conventional FF, ABC, GA, and PSO respectively. From the overall analysis, the effectiveness of the proposed GWO is abundantly surpassing the other conventional algorithms in terms of minimum rescheduling cost. (a) IEEE 14 bus system

7.4 Congestion Analysis Fig.2 illustrates the congestion analysis of the developed congestion management system as well as existing systems of both IEEE 14 bus system and IEEE 30 bus system. This analysis reviews how the congestion management techniques work in terms of minimizing congestion.

(b) IEEE 30 bus system Fig.2 Congestion analysis of Grey Wolf Optimization with other Conventional Methods

(a) IEEE 14 bus system

(b) IEEE 30 bus system Fig.1 Convergence Analysis Demonstration of Grey Wolf Optimization with other Conventional Methods

Fig.2(a) illustrates the performance of PSO, GA, ABC, FF and proposed GWO technique performed on IEEE 14 bus system to lessen the congestion that happened in buses.

At first, there are two congested buses available below the minimum margin. From the illustration, the performance of PSO and GA are not so effective in decreasing congestion. In contrast to this, the proposed strategy performed the congestion management in an effective way, by which it minimizes the congested bus from two to one. Correspondingly, the capability of decreasing congestion by PSO, GA, ABC, FF, and proposed GWO technique in IEEE 30 bus system is illustrated in Fig. 2(b) respectively. The efficiency of the proposed strategy is proved over other techniques in correspondence with reduced congestion in bus.

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 7.5 Statistical analysis In this section, the performance of proposed GWO is compared to other stochastic algorithms like PSO, GA, ABC, and FF. Usually, the performance of such algorithms depends on initialization, and hence it is more difficult to finalize the efficiency of the algorithms. A common way to analyze the algorithms is utilizing statistical tests on the gained results.

the performance of the rescheduling strategies are illustrated in Fig. . For the purpose of analysis, certain parameters are concerned, and they include best case, worst case, mean performance, median performance as well as standard deviation among the mean and distinct performances.

7.6 Best Solution Generation

The best solution generation of both IEEE 14 bus system and IEEE 30 bus system by all the algorithms like PSO, GA, ABC, FF and proposed GWO is summarized in Table II and Table-V respectively. From Table II, it is observed that the proposed approach has attained the three optimal best generators like 160, 80 and 44.73 respectively. Similarly, From Table VI , the approach has attained six optimal generators of IEEE 30 bus system like 50, 20, 15, 35, 10 and 12 respectively.

GWO [36]

PSO [32]

GA [33]

ABC [34]

FF [35]

118.5098

119.4853

159.2605

156.0871

160

37.6382

40.23428

64.90504

69.56678

80

29.62553

30.14488

39.98064

37.71193

44.72549

(a) IEEE 14 bus system Table â&#x20AC;&#x201C;V Best solution generation of proposed generator rescheduling strategy of IEEE 14 bus system

PSO [32] 50 20 15 10 30 12 (b) IEEE 30 bus system

GA [33] 77.57261 28.24541 41.28962 19.84808 13.43874 21.77339

ABC [34] 50 20 15 10 10 12

FF [35] 50 20 15.00109 17.60708 11.67345 14.61927

GWO [36] 50 20 15 35 10 12

Table-VI Best solution generation of proposed generator rescheduling strategy of IEEE 30 bus system

Fig.3 Performance percentage from statistical analysis (best case, worst case and mean) of Fig.3 shows the statistical information on the diminished rescheduling cost attained from proposed GWO-based rescheduling approach over other existing rescheduling algorithms of both IEEE 14 bus system and IEEE 30 bus system respectively, and the graphical representation of

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 8. Conclusion and Future Work

9. References

In a deregulated power systems congestion management is one of the major technical issue. The OPF based congestion management is considered here and the results are compared with both conventional and nonconventional methods (GWO algorithm).

Conventional methods not provide the optimized results.

The GWO algorithm (non-conventional method) give the good results on the basis of cost analysis, convergence analysis, congestion analysis, statistical analysis, best solution generation. Thus, it is concluded that the performance of the GWO-based rescheduling strategy is superior to the existing conventional methods by minimized rescheduling cost in computation. By removing congestion from deregulated power system by minimizing cost of rescheduling of generator the society get constant voltage, stable system and continuous interrupted power.

The efficiency of the system is increases, so the production of product also increases. In future the congestion management will be done with different recent intelligent techniques in a higher order IEEE test bus systems.

[1] J.P. Walters and D.W. Smith, `The energy policy act of 1992 - A watershed for competition in the wholesale power market', Yale Journal ofRegulation, Vol. 10, 1993, pp.447-482.

[2] M.C. Hoffman, `The future ofelectricity provision', Regulation, Vol .3, 1994, pp.55-62 .

[3] J.C. Moorhouse, `Competitive markets for electricity generation' available from :http://www .cato.org/pubs/journal/cj l4n3-3 .html, Washington, DC, USA, Cato Institute, 15pp,1998.

[4] S. Hao and A. Papalexopoulos, `Reactive power pricing and management', IEEE Transactions Power Systems, Vol. 12, 1997, pp.95-104.

[5] N.S . Rau, `The need for capacity markets in the deregulated electrical industry - a review', Proceedings of the IEEE Power Engineering Society, Winter Meeting, New York, 1, 1999,pp.411-415 .

[6] DOE, Maintaining reliability in a competitive U.S . electricity industry, Final report ofthe task force on electric system reliability, United States Department of Energy, 1998 .

[7] C.-C. Liu and R. Christie, Energy Management System, in Encyclopaedia ofComputer Science and Technology (ed. A. Kent, J.G . Williams, C.M. Hall and R. Kent), 26, Supplement 11, 1992,pp.177-194.

[8] F.C . Schweppe, M.C . Caraminis, R.D . Tabors and R.E . Bohn, Spot Pricing of Electricity, Kluwer Academic Publishers, 1998 .

[9] J.A . Momoh, R.J . Kosselar, M.S . Bond, B. Stott, D. Sun, Papalexpoulos and P. Ristanovic `Challenges to optimal power flow', IEEE Transactions on Power Systems, Vol. 12, 1997, pp.444-454 .

[10] L. Philipson and H.L . Willis, Understanding Electric Utilities and De-regulation, Marcel Dekker Inc., 1998 .

[11] Power System Restructuring and Deregulation Edited by Loi Lei Lai Copyright Š 2001 John Wiley & Sons Ltd

585

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 [12] Mojtaba Khanabadi, Hassan Ghasemi, Meysam Doostizadeh, Optimal Transmission Switching Considering Voltage Security and N-1 Contingency Analysis, IEEE Transactions on Power Systems 28(1) (2013).

[13] Kanwardeep Singh, Narayana Prasad Padhy, Jaydev Sharma, Influence of Price Responsive Demand Shifting Bidding on Congestion and LMP in Pool-Based Day-Ahead Electricity Markets, IEEE Transactions on Power Systems 26(2) (2011).

[14] Hajforoosh S., Nabavi S.M.H., Masoum M.A.S., Coordinated Aggregated-Based Particle Swarm Optimization Algorithm for Congestion Management in Restructured Power Market by Placement and Sizing of Unified Power Flow Controller, IET Science, Measurement & Technology 6(4) (2012), 267–278.

[15] Tiwari P.K., Sood Y.R., Efficient and Optimal Approach for Location and Parameter Setting of Multiple Unified Power Flow Controllers for a Deregulated Power Sector, IET Generation, Transmission & Distribution 6(10) (2012), 958-967.

[16] Jagabondhu Hazra, Avinash K. Sinha, Congestion Management Using Multiobjective Particle Swarm Optimization, IEEE Transactions on Power Systems 22(4) (2007)..

[17] Masoud Esmaili, Nima Amjady, Heidar Ali Shayanfar, Multi-Objective Congestion Management

by Modified Augmented e-Constraint Method, Applied Energy 88 (2011), 755–766.

[18] Visalakshi S., Baskar S., Decentralized Congestion Management Using Modified NSGA-II, Arabian Journal for Science and Engineering 36(5) (2011), 827-840.

[19] Vijayakumar K., Multi-objective Optimization Methods for Congestion Management in Deregulated Power Systems, Journal of Electrical and Computer Engineering (2012).

[20] Kessel P., Glavitsch H., Estimating the Voltage Stability of a Power System, IEEE Transactions on Power Delivery 1(3) (1986), 346–354.

[21] Zimmerman R., Murillo Sanchez C.E., Gan D., Matpower 3.0: A Matlab Power System Simulation Package, Cornell University Press (1997).

586

[22] Gao B., Morrison G.K., Kundur P., Voltage Stability Evaluation Using Modal Analysis, IEEE Transactions on Power Systems, 7(4) (1992), 1529– 42.

[23] Yujiao Zeng, Yanguang Sun, Application of Hybrid MOPSO Algorithm to Optimal Reactive Power Dispatch Problem Considering Voltage Stability, Journal of Electrical and Computer Engineering (2014).

[24] Federico Milano, Luigi Vanfretti, Juan Carlos Morataya, An Open Source Power System Virtual Laboratory: The PSAT Case and Experience, IEEE Transactions on education 51(1) (2008).

[25] Seyedali Mirjalili, Seyed Mohammad Mirjalili, Andrew Lewis, Grey Wolf Optimizer, Advances in Engineering Software 69 (2014), 46–61.

[26] Nitin Mittal, Urvinder Singh, Balwinder Singh Sohi, Modified Grey Wolf Optimizer for Global Engineering Optimization, Applied Computational Intelligence and Soft Computing (2016).

[27] Rozenberg, G., Bck, T., Kok, J., 2011,”Handbook of Natural Computing in Springer Publishing Company 1st Ed. [28] Liu.J, Tusi K.C. 2006, “Toward nature-inspired computing,” University of Michigan Press, Aaa Arbor.

[29] Zhang J., 2009, “Advances in Fuzzy Method for Natural Computing,” IEEE Ninth International Conference on Hybrid Intelligent Systems 2p18-23 [30] Shadbolt, N., 2004. Nature-inspired computing,” IEEE journal on Intelligent Systems 19(1), p. 2-3.

[31] Souza, J.G., Costa J.A.F., 2009, “ Unsupervised data clustering and image segmentation using natural computing techniques, ‘IEEE International Conference on System, Man and Cybernetics p.

5045- 5050.

[32] Rechenberg,I.,1973 Evolution strategies :Optimierung Technisher System each Prinzipien des Biologischen Evolution Fromman Hozlboog Verlag, Stuttgart, (German) [33] Holland, J.H.,1975, “Adaptation in natural and artificial systems,” University of Michigan Press, Aaa Arbor.

[34] Bongard, J.,2009, “Biologically Inspired Computing ,” IEEE Computer Journal 42940,p 95-98.

[35] Forbes, N., 2000, “Biologically Inspired Computing,” Computing in Science & Engineering 2(6), p. 83-87.

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018 [36] David, E.G. 1989, “Genetic Algorithm in Search Optimization and Machine Learning, ” Addison Wesley, p 41 n, [37] Storn, R. 1996. "On the usage of differential evolution for function optimization," Biennial Conference of the North American Fuzzy Information Processing Society (NAFIPS),p 519 [39] Md Sarwar and Anwar Shahzad Siddiqui, "An efficient particle swarm optimizer for congestion management in deregulated electricity market ", Journal of Electrical Systems and Information Technology, vol.

2, no. 3, pp.269–282,December 2015.

[40] Sadhan Gope, Arup Kumar Goswami, Prashant Kumar Tiwari and Subhasish Deb, "Rescheduling of real power for congestion management with integration of pumped storage hydro unit using firefly algorithm", International Journal of Electrical Power & Energy Systems, vol. 83, pp. 434-442, December 2016.

[41] Sumit Verma and V. Mukherjee, "Firefly algorithm for congestion management in deregulated environment", Engineering Science and Technology, an International Journal, vol.19, no.3, pp. 1254-1265, September 2016.

[42] J. Jeslin Drusila Nesamalar, P. Venkatesh and S. Charles Raja, "Energy management by generator rescheduling in congestive deregulated power system", Applied Energy, vol. 171, pp. 357-371, June 2016.

[43] S. Verma and V. Mukherjee, "Optimal real power rescheduling of generators for congestion management using a novel ant lion optimiser," IET Generation, Transmission & Distribution, vol. 10, no. 10, pp. 25482561, 2016.

[44] Mccomb, K, et al. Female lions can identify potentially infanticidal males from their roars. Proc. R. Soc. Lond. Ser B: Biol. Sci. 1993;252 (1333)59–64. [[46] S.B., Hrdy, 7 Empathy, polyandry, and the myth of the coy female, Conceptual Issues in Evolutionary Biology, 2006: p. 131.

587

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.8 NO.12 DECEMBER 2018

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