Renewables in Future Power Systems: Implications of Technological Learning and Uncertainty

304 Pages·2014·8.466 MB·English

by  Fabian Wagner (auth.)

Green Energy and Technology
Fabian Wagner
Renewables
in Future Power
Systems
Implications of Technological Learning
and Uncertainty
Green Energy and Technology
Forfurthervolumes:
http://www.springer.com/series/8059
Fabian Wagner
Renewables in Future
Power Systems
Implications of Technological
Learning and Uncertainty
ABC
FabianWagner
FacultyofBusinessAdministration
andEconomics
UniversityofDuisburg-Essen
Essen
Germany
Dissertation in fulfillment of the requirements for a Doctoral degree in Business Sciences
(Dr.rer.pol.)fromtheFacultyforBusinessandEconomicsofDuisburg-EssenUniversity
(FakultätfürWirtschaftswissenschaften,UniversitätDuisburg-Essen).
Submittedby:FabianWagner,borninVillingen
Dateoftheoralexamination:August7,2013
Firstreviewer:Prof.Dr.ChristophWeber;Secondreviewer:Prof.Dr.VolkerClausen
ISSN1865-3529 ISSN1865-3537 (electronic)
ISBN978-3-319-05779-8 ISBN978-3-319-05780-4 (eBook)
DOI10.1007/978-3-319-05780-4
SpringerChamHeidelbergNewYorkDordrechtLondon
LibraryofCongressControlNumber:2014935085
(cid:2)c SpringerInternationalPublishingSwitzerland2014
Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof
thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation,
broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation
storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology
nowknownorhereafterdeveloped.Exemptedfromthislegalreservationarebriefexcerptsinconnection
with reviews or scholarly analysis or material supplied specifically for the purpose of being entered
and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of
this publication or parts thereof is permitted only under the provisions of the Copyright Law of the
Publisher’slocation,initscurrentversion,andpermissionforusemustalwaysbeobtainedfromSpringer.
PermissionsforusemaybeobtainedthroughRightsLinkattheCopyrightClearanceCenter.Violations
areliabletoprosecutionundertherespectiveCopyrightLaw.
Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication
doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant
protectivelawsandregulationsandthereforefreeforgeneraluse.
Whiletheadviceandinformationinthisbookarebelievedtobetrueandaccurateatthedateofpub-
lication,neithertheauthorsnortheeditorsnorthepublishercanacceptanylegalresponsibilityforany
errorsoromissionsthatmaybemade.Thepublishermakesnowarranty,expressorimplied,withrespect
tothematerialcontainedherein.
Printedonacid-freepaper
SpringerispartofSpringerScience+BusinessMedia(www.springer.com)
Foreword
The world energy markets have undergone profound changes over the last
decade. The record high prices for oil and other fossil energy carriers in
2008 were followed by a dramatic decline as a consequence of the global
financial and economic crisis. For oil, a rapid recoveryof the prices could be
observed, whereas shale gas then turned out to be a game changer for the
U.S. gas market and beyond. In parallel, the discussions on climate change
intensified, yet a global long term agreementhas not yet been concluded nor
seemstobewithinimmediatereach.Despitethislackofinternationalaccord,
the relevance of renewables has increased considerably around the world. A
majorimpedimentforaglobalclimatechangemitigationstrategyis,however,
the still considerable uncertainty with respect to the future technical and
economic potentials of renewable energies.
This is the starting point for Fabian Wagner’s excellent research work.
He focused on the future role of renewables in global energy supply and
developedacomprehensiveapproachtoidentifyoptimalstrategiesforthis.He
tackles the three major challenges for renewable energy development within
one integrated model: the site-specific potentials of renewables in different
regionsoftheworld,theimplicationsofintermittencyforsolarandwindand
the already mentioned uncertainty on future technological learning.
This is not just a book about a large numerical model. It also gives de-
tailedinsights in the potentials ofrenewablesandin the analytics ofoptimal
strategychoiceunder uncertainty.FabianWagnergatheredhere allavailable
knowledgetosketchabroadpicture ofthe pathforwardtowardsaneconom-
icallyefficientgreenhousegasreduction.Hecombinedrigorousmathematical
model formulations with his striking ability to describe key developments in
a clear language and with appealing graphs. He supported his results with
impressive sensitivity analyses leaving almost no questions unanswered.
This book offers answersto the readers.The most importantone is about
the role renewables will play in the future - despite the challenges they will
need to face. In a carbon-constrained world there is a huge need for renew-
able, which are expected to dominate world energy supply by the end of
VI Foreword
the century, though this may not happen as rapidly as one would argue in
Germanyorinotherpartoftheworld.Thereasonsforthisneedcanbefound
in Fabian’s analysis.
It has been a great pleasure for me to work together with Fabian at his
PhD. I full-heartily hope that this book - containing the result of his efforts
- will find many readers who do agree with me on the intellectual rigor and
the high quality of the research.
Essen, February 2014 Prof. Christoph Weber
Preface
Renewable powergenerationtechnologies,apartfromhydro,accountforless
than 5% of global production today. From a cost perspective they can, bar-
ring a few exceptions, not compete with fossil- or fissile-based generation
technologies.However,severalfuturedevelopments arelikely to resultin im-
provedrelativecostcompetitivenessforrenewables.Theyincludesystemand
operating cost reductions, increasing costs for carbon dioxide emissions and
increasing fossil fuel prices. Yet, whether the magnitude of those trends will
be sufficient to render renewable technologies more competitive than con-
ventional ones and, if so, which technologies will be the winners, is highly
uncertain.
I experienced first-handhow relevant this topic is for playersin the power
industry when working for a wind turbine component manufacturer. Both
owners and management were aware that in case governmental support for
wind power ceased to exist, the thriving market would collapse. Although
supportschemesarefairlypredictable inthe short-term,inthe mid- to long-
termsubsidiescanbeexpectedtobedirectedtowardsthosetechnologieswith
the best prospects for reaching competitiveness at comparatively low costs
to society.
The high degree of complexity associated with efforts to assess the future
prospects of renewable technologies based on fundamental drivers were the
mainmotivations to approachthis topic using methods fromOperationsRe-
search in a level of detail, which is generally possible in an academic rather
thaninanindustrysetting.Apartfromitsmethodologicalcontributions,this
work therefore also aspires to produce practically relevantinsights regarding
the long-term competitiveness of renewable power.
ThecontentofthisbookderivesfrommydoctoralthesisworkattheChair
for Management Science and Energy Economics (EWL) of Duisburg-Essen
University between 2008 and 2013.
I would like to thank two persons in particular. My advisor,
Prof. Dr. Christoph Weber, and my wife, Alesia Wagner. Without their sup-
port, inspiration and encouragement this book would have never seen the
VIII Preface
lightofday.Iwouldalsoliketothankalargegroupofpeople,whosupported
me in variousways,including Prof.Dr. Volker Clausen,my colleaguesatthe
EWLandmyparents,RitaandOtmarWagner,aswellasmyparents-in-law,
Margarita and Vasili Staravoitov.
Essen, 2013 Fabian Wagner
Contents
Foreword ................................................ V
Preface.................................................. VII
List of Abbreviations..................................... XV
1 Introduction ......................................... 1
2 Renewables in Power Generation: Status Quo .......... 3
2.1 Global Power Generation Landscape ..................... 3
2.2 Properties of Renewable Technologies .................... 5
2.2.1 Generation Costs................................ 7
2.2.2 Potential ....................................... 10
2.2.3 Intermittency ................................... 11
2.3 Drivers of Future Technology Competitiveness ............ 14
2.4 Research Question..................................... 16
References ................................................ 18
3 Methods for Energy System Modeling ................. 21
3.1 General Aspects....................................... 21
3.2 Equilibrium Models.................................... 23
3.2.1 Background .................................... 23
3.2.2 Energy System Applications ...................... 24
3.3 Mathematical Programming ............................ 26
3.3.1 Linear and Integer Programming .................. 27
3.3.2 Nonlinear Programming.......................... 28
3.4 Solution Methods for Mathematical Programs............. 29
3.4.1 Analytical Approaches ........................... 29
3.4.2 Numerical Approaches ........................... 32
3.5 Risk and Uncertainty .................................. 34
3.5.1 General Aspects................................. 35
3.5.2 Model-Endogenous Representation of Uncertainty ... 37
References ................................................ 40
X Contents
4 Technological Change and the Experience Curve........ 43
4.1 Technological Change .................................. 43
4.2 Experience Curves..................................... 46
4.2.1 Basic Concept: The One-Factor Experience Curve ... 46
4.2.2 Drivers of Cost Reductions ....................... 49
4.2.3 Reasons for Differences in Empirical
Learning Rates.................................. 52
4.2.4 Concepts with Several Explanatory Variables ....... 54
4.2.5 Experience Curves as Forecasting Tool ............. 55
4.3 Learning Rates for Power Generation Technologies......... 57
4.4 Endogenous Technological Change in E3 Models........... 62
4.4.1 Implementation Methods ......................... 63
4.4.2 Dealing with Non-convexity in Bottom-Up Models... 66
4.5 Implications .......................................... 68
References ................................................ 69
5 Optimal Investment Strategy for Competing Learning
Technologies: An Analytical Approach ................. 75
5.1 Objective and Approach................................ 75
5.2 Basic Deterministic Model.............................. 79
5.2.1 Setup and Description ........................... 79
5.2.2 Solution........................................ 83
5.2.3 Investment Decision Rule......................... 87
5.3 Deterministic Model with Capacity Endowment ........... 88
5.3.1 Setup and Description ........................... 88
5.3.2 Solution........................................ 90
5.3.3 Investment Decision Rule......................... 91
5.4 Dynamic Model with Uncertainty........................ 93
5.4.1 Setup and Description ........................... 93
5.4.2 Solution........................................ 96
5.4.3 Investment Decision Rule......................... 106
5.5 Pure versus Mixed Investment Strategies ................. 111
5.5.1 Solution for Mixed Strategies ..................... 112
5.5.2 Global Optimality of Pure Strategies............... 115
5.6 Model Application: Offshore Wind and PV ............... 124
5.7 Key Findings and Implications .......................... 127
References ................................................ 128
6 Optimal Future Deployment of Renewable Power
Technologies: A System Model Approach............... 131
6.1 Objective and Approach................................ 131
6.2 Model Description..................................... 134
6.2.1 Objective Function .............................. 137
6.2.2 Power Generation, Consumption and Trade......... 140
6.2.3 Energy Storage ................................. 144