Minimization of Climatic Vulnerabilities on Mini-hydro Power Plants: Fuzzy AHP, Fuzzy ANP Techniques and Neuro-Genetic Model Approach

111 Pages·2016·3.69 MB·English

by  Mrinmoy Majumder (auth.)

SPRINGER BRIEFS IN ENERGY
Mrinmoy Majumder
Minimization of
Climatic Vulnerabilities
on Mini-hydro Power
Plants
Fuzzy AHP, Fuzzy ANP
Techniques and Neuro-
Genetic Model Approach
123
SpringerBriefs in Energy
More information about this series at http://www.springer.com/series/8903
Mrinmoy Majumder
Minimization of Climatic
Vulnerabilities on
Mini-hydro Power Plants
Fuzzy AHP, Fuzzy ANP Techniques
and Neuro-Genetic Model Approach
123
Mrinmoy Majumder
National Institute ofTechnology Agartala
Agartala
India
ISSN 2191-5520 ISSN 2191-5539 (electronic)
SpringerBriefs inEnergy
ISBN978-981-287-313-2 ISBN978-981-287-314-9 (eBook)
DOI 10.1007/978-981-287-314-9
LibraryofCongressControlNumber:2016933318
©TheAuthor(s)2016
Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpart
of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations,
recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission
orinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilar
methodologynowknownorhereafterdeveloped.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this
publicationdoesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfrom
therelevantprotectivelawsandregulationsandthereforefreeforgeneraluse.
The publisher, the authors and the editors are safe to assume that the advice and information in this
book are believed to be true and accurate at the date of publication. Neither the publisher nor the
authorsortheeditorsgiveawarranty,expressorimplied,withrespecttothematerialcontainedhereinor
foranyerrorsoromissionsthatmayhavebeenmade.
Printedonacid-freepaper
ThisSpringerimprintispublishedbySpringerNature
TheregisteredcompanyisSpringerScience+BusinessMediaSingaporePteLtd.
Preface
Climate change has an impact on water-based energy power plants. Although
variousprocedureshavebeenadoptedtomitigatethevulnerabilities,yetchangesin
theclimaticpattern makehydroelectric powerplants vulnerable.Thepresentstudy
proposes that instead of the implementation of sophisticated and expensive but
ineffective mitigation measures, it is better to change the way energy is produced
from the power plant. This work implements an objective and cognitive tool to
estimate the impact of changing the parameters in such a manner that the effect of
climatic changes is minimum.
The technological advancements of Multi Criteria Decision Making (MCDM)
methods and a new variant of Artificial Neural Networks, Group Method of Date
Handling were utilized toforge a relationshipbetween theinputsand outputs. The
inputsarethecorrelated factors,whiletheoutputsarethenonlinearfunctionofthe
inputparameters,whicharebeneficialandnon-beneficialtoclimaticvulnerabilities.
The weight of importance is also a variable in the output function so that the
sensitivity of each parameter is encoded in the output function.
Chapter1givesanintroductiontotheproblemfacedbyhydropowerplants.The
main objective is proposed and brief discussions of the novel methodology are
presented.
Chapter 2 provides an opportunity to know about the basics of hydro power
plants, while Chap. 3 is a discussion of the popular climatic parameters and their
impactson naturalresources. Chapter 5 gives themethodology adopted to achieve
the study objective. In this regard, it is noted that for the first time multi-criteria
decision making and group method of data handling is applied in a cascade con-
nection to solve the problem. This indicator for representation of plant efficiency
under changed climate scenario has not been applied elsewhere.
Chapter6istheresultsanddiscussionsectionwheretheresultsaregivenandthe
possible causes for the results are depicted. The scientific benefits and limitations
of the study are discussed. The results from the application of the proposed pro-
cedure on Gumti Hydro Power Plant are also summarized.
v
vi Preface
One of the major results in this study is the identification of the priority
parameter that influences the performance efficiency of hydropower plants and is
the most sensitive to climatic vulnerabilities. The optimal ratio of the related
parameter for which climatic impacts on hydropower plants will be reduced is
another important output that was successfully derived from this investigation. In
the last chapter of the book some ideas for further research are discussed. A few
solutions to limitations such as dependency on methods are also explored.
Acknowledgements
This book is an endeavour to provide optimal opportunities to mitigate the impact
of climate change on the energy sector. The author conveys his heartiest gratitude
andrecognitiontothepeoplewhoareselflesslyworkingtosavemankindfromthe
disasters of climate change.
Heoffershisappreciationtohisfamily,friendsandcolleagueswhohavebytheir
criticism, suggestions and infinite patience, during the preparation of the manu-
scripts, enriched and enhanced the quality of this humble creation.
The author also offers his cognizance to all the publishers from whom many
relevantfactsandideasweredevelopedandretrieved.Theauthorhastriedhisbest
to cite the contributions taken from these publishers. If some of the acknowl-
edgements have beeninadvertently overlooked, please notify themistake so that it
can be rectified.
Last but not least, the author thanks Springer International Publishers and their
staffforacceptingthismanuscriptandfortheirwholeheartedcooperationduringthe
preparation of the book. He also thanks the anonymous reviewers who tediously
went through the draft and enriched the work with their constructive opinions.
The success of this book will depend on the successful implementation of the
solutions proposed in this work, and any queries in this regard will always be
obliged.
Agartala Mrinmoy Majumder
vii
Contents
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Methods and Materials. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Brief Methodology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Case Study Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2 Hydropower Plant. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1 Types of Hydropower Plant . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1.1 Impoundment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1.2 Diversion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.3 Pumped Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.4 Large Hydropower. . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.5 Small Hydropower. . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.6 Micro Hydropower . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.2 Strength and Weakness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3 Climatic Vulnerabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3 Climate Change and Its Impacts. . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.1 Impact on Global Water Scenario . . . . . . . . . . . . . . . . . . . . . . 13
3.2 Impact on Global Energy Scenario. . . . . . . . . . . . . . . . . . . . . . 16
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
4 Multi Criteria Decision Making and Group Method
of Data Handling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.1 Multi Criteria Decision Making Methods . . . . . . . . . . . . . . . . . 19
4.1.1 Application of MCDM in Climate Change
and Hydro Energy Research. . . . . . . . . . . . . . . . . . . . . 20
4.2 Group Method of Data Handling. . . . . . . . . . . . . . . . . . . . . . . 23
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
ix
x Contents
5 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
5.1 Application of MCDM Methods . . . . . . . . . . . . . . . . . . . . . . . 25
5.2 Development of the Weight Function. . . . . . . . . . . . . . . . . . . . 26
5.3 Application of GMDH as an Optimizer . . . . . . . . . . . . . . . . . . 27
5.4 Case Study: Gumati Hydro Power Plant (GHPP). . . . . . . . . . . . 29
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
6 Results and Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
6.1 Discussions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
6.2 Scientific Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
6.3 Limitations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
7 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
7.1 Drawbacks of the Study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
7.2 Future Scope. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105