SMART GRIDS: A PARADIGM SHIFT ON ENERGY GENERATION AND DISTRIBUTION WITH THE EMERGENCE OF A NEW ENERGY MANAGEMENT BUSINESS MODEL JESUS ALVARO CARDENAS International Business APPROVED: Leopoldo A. Gemoets, D.Sc., Chair Jose H. Ablanedo-Rosas, Ph.D Kallol K. Bagchi, Ph.D. Robert J. Sarfi. Ph.D. Bess Sirmon-Taylor, Ph.D. Interim Dean of the Graduate School Copyright by Jesus A. Cardenas 2014 SMART GRIDS: A PARADIGM SHIFT ON ENERGY GENERATION AND DISTRIBUTION WITH THE EMERGENCE OF A NEW ENERGY MANAGEMENT BUSINESS MODEL by JESUS ALVARO CARDENAS, BSEE, MBA, MSIE DISSERTATION Presented to the Faculty of the Graduate School ofThe University of Texas at El Paso in Partial Fulfillmentof the Requirements for the Degree of DOCTOR OF PHILOSOPHY International Business THE UNIVERSITY OF TEXAS AT EL PASO May 2014 All rights reservedINFORMATION TO ALL USERSThe quality of this reproduction is dependent upon the quality of the copy submitted.In the unlikely event that the author did not send a complete manuscriptand there are missing pages, these will be noted.Also,if material had to be removed, a note will indicate the deletion.Microform Edition ProQuest LLC.All rights reserved. This work is protected againstunauthorized copying under Title 17, United States CodeProQuest LLC.789 East Eisenhower ParkwayP.O. Box 1346Ann Arbor,MI 48106 - 1346UMI3623383Published by ProQuest LLC (2014).Copyright in the Dissertation held by the Author.UMI Number:3623383ivABSTRACT An energy and environmental crisis will emerge throughout the world if we continue with ourcurrentpracticesofgenerationanddistributionofelectricity.Apossiblesolutiontothis problemisbasedontheSmartgridconcept,whichisheavilyinfluencedbyInformationand CommunicationTechnology(ICT).Althoughtheelectricityindustryismostlyregulated,there areglobalmodelsusedasroadmapsforSmartGridsimplementationfocusingontechnologies and the basic generation-distribution-transmission model. This project aims to further enhance a businessmodelforafutureglobaldeployment.Ittakesintoconsiderationthemanyfactors interacting in this energy provision process, based on the diffusion of technologies and literature surveys on the available documents in the Internet as well as peer-reviewed publications. Tariffs andregulations,distributedenergygeneration,integrationofserviceproviders,consumers becoming producers, self-healing devices, and many other elements are shifting this industry into amajorchangetowardsliberalizationandderegulationofthissector,whichhasbeenheavily protected by the government due to the importance of electricity for consumers.WeproposeanEnergyManagementBusiness Modelcomposedbyfourbasicelements: Supply Chain, Information and Communication Technology (ICT), Stakeholders Response, and the resulting Green Efficient Energy (GEE). We support the developed model with an exhaustive literaturesurvey,diffusionanalysisofthedifferenttechnologiesundertheumbrellaofSmart Grids(SG),andtwosurveys:oneadministeredtopeersandprofessionals,andanotherfor expertsinthefield,basedontheSmartGridCarnegieMelonMaturityModel(CMUSEI SGMM).Thecontributionofthismodelisasimplepathtofollowforentitiesthatwantto achieve environmental friendly energy with the involvement of technology and all stakeholders. vTABLE OF CONTENTS ABSTRACT ............................................................................................................................. ivTABLE OF CONTENTS ...........................................................................................................vLIST OF TABLES .....................................................................................................................xLIST OF FIGURES ............................................................................................................... xiiiCHAPTER 1: INTRODUCTION ..............................................................................................11.1 Background Information ..........................................................................................11.2 The Birth of a New Model .......................................................................................41.3 The Most Important Elements .................................................................................51.4 The Enhanced Energy Management Business Model .............................................61.5 Research Question And Objectives .........................................................................81.6 Contributions of This Dissertation ...........................................................................9CHAPTER 2: COMPREHENSIVE RESEARCH IN SMART GRID ....................................102.1 Background Information ........................................................................................102.2 Theoretical Background .........................................................................................122.2.1Smart Grid Concept Defined ........................................................................122.2.2SWOT Analysis ............................................................................................132.3 Methodology For Taxonomy Research .................................................................172.3.1Google Scholar Research Results .................................................................182.3.2Preliminary Conclusions of Google Research ..............................................242.4 Literature Survey Using ISI Web of Science .........................................................252.4.1Hypotheses H2 ..............................................................................................262.4.2Research Purposes ........................................................................................282.4.3Research Methodology .................................................................................322.4.3.1 Classification by Research Categories ...........................................332.4.3.2 Classification by Research Focus ...................................................352.4.3.3 Classification by Data Collection Method .....................................362.4.3.4 Classification by Data Analysis Technique ...................................382.4.3.5 Classification by Discipline ...........................................................392.4.3.6 Taxonomy of Papers Purpose .......................................................41vi2.4.3.7 Smart Grid Technologies ...............................................................442.4.3.8 Originating Countries .....................................................................452.4.4Further Analysis and Prognosis ....................................................................522.4.4.1 ICT Related Papers .........................................................................572.4.4.2 Physical Infrastructure Related Papers ...........................................582.4.4.3 Economics Related Papers .............................................................592.4.4.4 Environmental Related Papers .......................................................612.4.5Hypotheses H2 Results .................................................................................622.5 Data Oriented Analysis ..........................................................................................632.5.1Word Mining .................................................................................................632.5.2Bass Diffusion Model ..................................................................................672.5.3Author-oriented analysis ...............................................................................702.6 Gap Analysis of Literature and Investments ..........................................................752.6.1Background Information ...............................................................................752.6.2Hypotheses H3 ..............................................................................................762.6.3US Government ............................................................................................762.6.4Private Sector ................................................................................................812.6.5Academic Sector ...........................................................................................822.6.6Methodology .................................................................................................832.6.7Results ...........................................................................................................852.6.8Gaps Conclusions ........................................................................................872.7 Conclusions and Graphical View ...........................................................................872.7.1Conclusions ...................................................................................................872.7.2Graphical View .............................................................................................91CHAPTER 3: DIFFUSION OF TECHNOLOGIES AND RISKS ..........................................933.1 Generation and Consumption Information ............................................................933.1.1Hypotheses H4 ..............................................................................................943.1.2Private Investments on Energy .....................................................................953.1.3Sources of Consumption and Generation Statistics ......................................973.1.4Global Trends on Energy Use and Availability ..........................................1023.1.5Global Trends on Generation and Sources .................................................1063.1.6Global Sources of Generation Capacity versus Production ........................109vii3.1.7Diffusion of Renewable Generation ...........................................................1143.1.7.1 Wind Generated Electricity in the US ..........................................1153.1.7.2 Solar Generated Electricity in the US ..........................................1173.1.8Global Prognosis .........................................................................................1183.2 Advanced Metering Infrastructure Background ..................................................1233.2.1Hypotheses H5 ............................................................................................1253.2.2Implementation Progress ............................................................................1263.2.3Bass Diffusion Model for AMI/AMR .......................................................1273.2.3.1 Geographical Clusters of States ...................................................1273.2.3.2 Utility Company Ownership ........................................................1353.2.3.3 Urban Concentration Analysis .....................................................1373.2.4Hypotheses H5s Results ............................................................................1393.2.5Findings and Prognosis for AMI.................................................................1393.3 Electric Vehicles Background Information .........................................................1393.3.1Implementation Progress ............................................................................1403.3.2Hypotheses H6 ............................................................................................1413.3.3Deployment of Electric Vehicles in the US ................................................1413.3.4Findings and Prognosis for Electric Vehicles .............................................1493.4 Cyber Risks Background Information .................................................................1503.4.1Security Breaches Measures and Research Focus ......................................1523.4.2Types of Cybersecurity Risks .....................................................................1533.4.3Hypotheses H7 ............................................................................................1543.4.4Methodology ...............................................................................................1543.4.5Hypotheses Results .....................................................................................1623.4.6Conclusions .................................................................................................1623.5 Adding All Diffusions Together ..........................................................................1633.5.1Distributed Generation Diffusion ...............................................................1633.5.2Smart Meters Diffusion ...............................................................................1643.5.3Electric Vehicles Diffusion .........................................................................1653.5.4Cyber Attacks Diffusion .............................................................................1663.5.5All the Prior Diffusions Together ...............................................................1673.5.6Conclusions .................................................................................................168viiiCHAPTER 4: ROLE OF CONSUMERS IN THE NEW BUSINESS MODEL ...................1694.1 Background Information ......................................................................................1694.2 Literature Review.................................................................................................1704.3 Model Development .............................................................................................1744.3.1Background Information .............................................................................1744.3.2United Kingdom Road Map ........................................................................1754.3.3German E-energy Road Map ......................................................................1764.3.4United States Road Map for Smart Grids ...................................................1784.3.5China Strong Smart Grid ............................................................................1794.3.6Masdar: The Sustainable City .....................................................................1804.3.7Texas Smart Grid Investment Model ..........................................................1824.3.8Ontario Smart Grid Model ..........................................................................1834.3.9Developing our Own Model .......................................................................1844.4 First Survey ..........................................................................................................1874.4.1Survey for Smart Energy Perception ..........................................................1874.4.2Survey Methodology ...................................................................................1894.4.3Data Analysis ..............................................................................................1904.4.3.1 Gender of Respondents ................................................................1904.4.3.2 Education Level ............................................................................1914.4.3.3 Household Income ........................................................................1914.4.3.4 What is important for the consumer? ...........................................1924.4.3.5 What is everyones role? ..............................................................1934.4.3.6 Importance to Society ...................................................................1964.4.3.7 Important for the individual .........................................................1974.4.3.8 Interviewees Own Definition ......................................................1974.4.3.9 Cost of Energy ..............................................................................1984.4.3.10 Location ......................................................................................1984.4.4PLS-SEM Model for the First Survey ........................................................1994.4.5Conclusions and Next Steps........................................................................2034.5 Proposed Business Model Development and Validation .....................................2044.5.1New Business Model First Draft .................................................................2054.5.2Questions Development, Grouping and Analysis .......................................2054.5.2.1 Development of Questions ...........................................................205ix4.5.2.2 Survey Preparation .......................................................................2064.5.3Hypotheses H8 ............................................................................................2074.5.4PLS Model for the Second Survey..............................................................2094.5.5Responders Statistic Analysis ....................................................................2114.5.6PLS Model Results .....................................................................................2164.5.7Hypotheses H8s Results ............................................................................2204.5.8Conclusions and Next Steps........................................................................2214.6 Cost of Smart Energy ...........................................................................................2214.6.1Hypotheses H9 ............................................................................................2234.6.2Electricity Consumption .............................................................................2254.6.3Generation and Costs by Sources ...............................................................2274.6.4 Deregulation Status .....................................................................................2304.6.5Competition by State...................................................................................2314.6.6Urban Concentration ...................................................................................2324.6.7Methodology ...............................................................................................2334.6.8Hypotheses H9 Results ...............................................................................2384.6.9Conclusions .................................................................................................238CHAPTER 5: CONCLUSIONS AND FUTURE RESEARCH ............................................2415.1 Global Position Of Smart Grid Distribution Literature .......................................2415.2 Diffusion Models for ICT Enhanced Technologies .............................................2415.3 Enhanced Business Model ...................................................................................2435.4 General Conclusions ............................................................................................2445.5 Next Steps and Further Research .........................................................................244REFERENCES ......................................................................................................................246APPENDIX ............................................................................................................................337VITA ......................................................................................................................................344 xLIST OF TABLES Table 2.1: Results of Hypotheses H1 ............................................................................................ 25Table 2.2: General classification of this paper .............................................................................. 34Table 2.3: Disciplines and Descriptions (Chicco, 2010) .............................................................. 39Table 2.4: Row & Column Percentages for Research Classification versus Focus ...................... 47Table 2.5: Row & Column Percentages for Data Collection versus Papers Focus ..................... 48Table 2.6: Row & Column Percentages for Data Analysis vs. Papers Focus ............................. 48Table 2.7: Row & Column Percentages for Conference papers SG technologies vs. Purpose ... 49Table 2.8: Row & Column Percentage for Journal Papers SG technologies vs. Purpose ........... 50Table 2.9: Row & Column Percentages for Country vs. Papers Purpose ................................... 51Table 2.10: Row & Column Percentages for Country vs. SG Technology .................................. 52Table 2.11: Regression statistics for relationship of Journal and Conferences papers ................ 54Table 2.12: Category mixes related to SGD techs ........................................................................ 56Table 2.13: Hypotheses H2 results ............................................................................................... 63Table 2.14: Top 25 words on number of mentions in the past 5 years ......................................... 64Table 2.15: Top 20 SGD Technologies mentions in the past 6 years ........................................... 65Table 2.16: Bass Diffusion Model results for SGD technologies ............................................... 69Table 2.17: Distribution of top 20 countries of origin of SGD papers authors ........................... 71Table 2.18: Distribution of papers by number of authors ............................................................. 71Table 2.19: Comparison of Journal and Conference papers by country of authors ...................... 72Table 2.20: Distribution of authors by Country and writing order ............................................... 73Table 2.21: Distribution of top 20 most prolific writers of SGD papers ...................................... 74Table 2.22: Type of publication of most prolific authors (co-authors)......................................... 74Table 2.23: DoE distribution on selected categories .................................................................... 84Table 2.24: EPRI distribution on selected categories ................................................................... 85Table 2.25: Academic Research distribution by categories .......................................................... 85Table 2.26: Comparisons between DoE, EPRI and the Literature Survey ................................... 86Table 2.27: Gap from the average of DoE and EPRI versus Literature survey ............................ 86Table 2.28: Correlation results for comparison groups ................................................................ 86Table 2.29: Hypotheses H3 results ............................................................................................... 87Table 3.1: Consumption and generation regression lines statistics ............................................. 98Table 3.2: Sensitivity analysis for the crossing-point year ........................................................... 99Table 3.3: Consumptions sensitivity analyses ........................................................................... 101Table 3.4: Generation sources sensitivity analysis ..................................................................... 102Table 3.5: Regression statistics for Generation and Imports ...................................................... 103Table 3.6: Regression lines for Energy use and availability ....................................................... 105Table 3.7: Sensitivity analysis for crossing line year for use and available energy ................... 106Table 3.8: Capacity factors ......................................................................................................... 108Table 3.9: Hydro capacity (KWh) .............................................................................................. 109Table 3.10: Hydro production (KWh) ........................................................................................ 110Table 3.11: Nuclear Capacity (KWh) ......................................................................................... 110Table 3.12: Nuclear Production (KWh) ...................................................................................... 111Table 3.13: Solar Capacity (KWh) ............................................................................................. 111Table 3.14: Solar Production (KWh) .......................................................................................... 112Table 3.15: Thermal Capacity (KWh) ........................................................................................ 112xiTable 3.16: Thermal Production (KWh) ..................................................................................... 113Table 3.17: Wind Capacity (KWh) ............................................................................................. 113Table 3.18: Wind Production (KWh) .......................................................................................... 114Table 3.19: Evolution of Sources of Electricity Generation in the US ....................................... 114Table 3.20: Diffusion Indexes for Wind Electricity Generation in the US by States ................. 115Table 3.21: t-test for top 10 States using Wind generated Electricity ........................................ 116Table 3.22: Diffusion Indexes for Solar Electricity Generation in the US by States ................. 118Table 3.23: t-test for top 10 States using Solar generated Electricity ......................................... 118Table 3.24: Hypotheses H4 Results ............................................................................................ 123Table 3.25: Regional Clustering for the US................................................................................ 124Table 3.26: Ownership of the utility Company .......................................................................... 125Table 3.27: Urban concentration indexes for the US .................................................................. 127Table 3.28: Cluster Totals for Diffusion ..................................................................................... 129Table 3.29: t-test Results for Clusters ......................................................................................... 129Table 3.30: Average statistics by States Clusters ...................................................................... 130Table 3.31: Standard Deviation statistics by States Clusters..................................................... 130Table 3.32: Standard Deviation t-test for States Clusters .......................................................... 130Table 3.33: Diffusion Results by States Division...................................................................... 131Table 3.34: t-test Results for Divisions ....................................................................................... 132Table 3.35: Average statistics by States Clusters ...................................................................... 132Table 3.36: Standard Deviation statistics by States Divisions .................................................. 133Table 3.37: Statistics from the Individual States ........................................................................ 133Table 3.38: Standard Deviation t-test for States Divisions ....................................................... 134Table 3.39: Top 10 States Diffusion Statistics ............................................................................ 134Table 3.40: Diffusion Statistics by Company Ownership .......................................................... 135Table 3.41: Diffusion Statistics for Ownership Categories ........................................................ 136Table 3.42: Diffusion Statistics for Urban Concentration .......................................................... 138Table 3.43: Hypotheses H5s Results ......................................................................................... 139Table 3.44: Regression results for gasoline price vs PHEV sales .............................................. 142Table 3.45: Average tax credits vs. PHEVs sold in the US ........................................................ 144Table 3.46: Regression results for PHEV price vs sales ............................................................. 146Table 3.47: Registered PHEVs vs. charging stations per state ................................................... 147Table 3.48: PEV Sales in 2013, Battery Size and Miles Run in One Charge ............................. 148Table 3.49: Hypotheses H6 Results ............................................................................................ 149Table 3.50: Categories of Security Breaches (Source: Privacy Rights Clearinghouse) ............. 155Table 3.51: Breaches Victims Categories .................................................................................. 156Table 3.52: Number of Breaches versus Type of Attack ............................................................ 158Table 3.53: Number of Victims by Type of Attack versus Breach ............................................ 158Table 3.54: Number of Breaches and Victims per State ............................................................. 159Table 3.55: Detail of Victims per Type of Breach ...................................................................... 160Table 3.56: Types of Breaches versus Victimized Areas ........................................................... 161Table 3.57: Breached Victims versus Victimized Sector ........................................................... 161Table 3.58: Hypotheses H7s Results ......................................................................................... 162Table 3.59: Diffusion Results for Homes with Solar/Wind Energy ........................................... 163Table 3.60: Diffusion Comparison of SG Technologies ............................................................ 167Table 4.1: Elements of smart use of energy ................................................................................ 174xiiTable 4.2: Statistics from Question # 4 ....................................................................................... 192Table 4.3: Row and Columns Percentages of Bucket Assignments ........................................... 194Table 4.4: ANOVA analyses for Buckets Ranks ...................................................................... 195Table 4.5: Statistics from Society Responsibilitys Question ..................................................... 196Table 4.6: Word mining of individual inputs .............................................................................. 198Table 4.7: Residence States of the Survey Respondents ............................................................ 199Table 4.8: Elements, Questions and Definitions ......................................................................... 200Table 4.9: Loading and Cross-loading ........................................................................................ 201Table 4.10: Latent Variables Coefficients .................................................................................. 201Table 4.11: Correlations among I vs. Square root of AVE ......................................................... 202Table 4.12: P-Values for Models Correlations .......................................................................... 202Table 4.13: SGMM Surveys Questions ..................................................................................... 206Table 4.14: Our Surveys Questions ........................................................................................... 206Table 4.15: Elements and Questions for the PLS Analysis ........................................................ 210Table 4.16: Means and t-tests for Questions not used in the Model ........................................... 211Table 4.17: Gender Differences on SG Technology (Means & Std. Dev.) ................................ 212Table 4.18: Occupation Driven Differences on SG Technology (Means & Std. Dev.) ............. 212Table 4.19: Year of Experience Driven Differences on SG Technology (Means & Std. Dev.) . 213Table 4.20: Education Driven Differences on SG Technology (Means & Std. Dev.) ................ 214Table 4.21: Location Driven Differences on SG Technology (Means & Std. Dev.) .................. 215Table 4.22: Surveys Sample Analysis ....................................................................................... 215Table 4.23: Model Fit Results ..................................................................................................... 216Table 4.24: Loading and Cross-loading Results ......................................................................... 217Table 4.25: Models Path Coefficients ....................................................................................... 218Table 4.26: Models Path Coefficients p-values ......................................................................... 218Table 4.27: Models Correlations of I vs. Square root of AVEs ................................................ 219Table 4.28: Models Correlations p-values ................................................................................. 219Table 4.29: Models Latent Variable coefficients ...................................................................... 220Table 4.30: Hypotheses H8s Results ......................................................................................... 220Table 4.31: Sources of Electricity Generation by Census Division ............................................ 227Table 4.32: Sources of Electricity Generation per State ............................................................. 228Table 4.33: Generation Costs for Sources of Electricity ............................................................ 229Table 4.34: States with Electricity Deregulation Status ............................................................. 231Table 4.35: Competition by State and Ownership of Utility Companies ................................... 232Table 4.36: Competition compared to Deregulation Status ........................................................ 233Table 4.37: Cost per Energy generation Mix by State ................................................................ 234Table 4.38: 27 Regulated Entities Regression Results with R2=0.794 ....................................... 234Table 4.39: Regulated formerly Deregulated Entities Regression Results ................................. 235Table 4.40: 16 Deregulated Entities Regression Results with R2=0.765 .................................... 235Table 4.41: Hypotheses H9s Results ......................................................................................... 238Table 4.42: Percentages of Tariff vs. Regulation Status ............................................................. 239 xiiiLIST OF FIGURES Figure 2.1: SWOT Analysis .......................................................................................................... 15Figure 2.2: Log trend line of SG articles ...................................................................................... 18Figure 2.3: Selected articles by categories .................................................................................... 19Figure 2.4: Growth of SG by discipline ........................................................................................ 20Figure 2.5: Time series for SG technologies (Cardenas et al., 2011) ........................................... 20Figure 2.6: SG technologies per country ...................................................................................... 21Figure 2.7: SG technologies by state ............................................................................................ 23Figure 2.8:Normalized articles mentions of technology per state ............................................. 23Figure 2.9: Distribution of Research Papers ................................................................................. 34Figure 2.10: Primary purpose of papers ........................................................................................ 36Figure 2.11: Analyzed papers by research purpose ...................................................................... 36Figure 2.12: Research by collection approach .............................................................................. 37Figure 2.13: Papers by data collection categories & time ............................................................ 37Figure 2.14: Data analysis techniques used .................................................................................. 38Figure 2.15: Data analysis techniques evolution in time .............................................................. 39Figure 2.16: Distribution of papers by category ........................................................................... 40Figure 2.17: Number of papers by type in time ............................................................................ 40Figure 2.18: Categories of papers by topics.................................................................................. 42Figure 2.19: Categories by time .................................................................................................... 43Figure 2.20: Distribution of SGD technologies ............................................................................ 44Figure 2.21: Trend of SGD technologies in time .......................................................................... 45Figure 2.22: Distribution of papers by country ............................................................................. 46Figure 2.23: Trends of Papers by First Authors Country and Year ............................................. 46Figure 2.24: Conference papers by continent and year ................................................................. 52Figure 2.25: Journal papers by continent and year ....................................................................... 53Figure 2.26: Conference papers topics by continent and Chiccos categories ............................ 54Figure 2.27: Journal papers topics by continent and Chiccos categories ................................... 55Figure 2.28: Category mixes versus time ..................................................................................... 56Figure 2.29: ICT Papers by year & country .................................................................................. 57Figure 2.30: ICT Papers by SG Technology and Country ............................................................ 57Figure 2.31: Physical Infrastructure Papers by Country and Year ............................................... 58Figure 2.32: Physical Infrastructure Papers by SG Technology and Country .............................. 59Figure 2.33: Economics Related Papers by Country and Year ..................................................... 60Figure 2.34: Economics related papers by SG Technology and Country ..................................... 60Figure 2.35: Environmental Related Papers by Country and Year ............................................... 61Figure 2.36: Environmental Related Papers by SG Technology and Country ............................. 62Figure 2.37: Text Mining Cloud ................................................................................................... 70Figure 2.38: Distribution of papers by number of authors ........................................................... 72Figure 2.39: DOE recovery awards .............................................................................................. 78Figure 2.40: EPRI funded projects................................................................................................ 81Figure 2.41: Academics distribution of Literature ........................................................................ 83Figure 2.42: Number of Papers per Technology in the Preliminary Model Graph ...................... 92Figure 3.1: Private investment in Energys sector around the world ............................................ 96Figure 3.2: Evolution of consumption and generation of electricity ............................................ 98xivFigure 3.3: Projected lines of consumption and generation until 2035 ........................................ 99Figure 3.4: Evolution of the crossing point from the sensitivity analysis .................................. 100Figure 3.5: Other uses of electricity to consider (source: UN data) ........................................... 103Figure 3.6: Importations of electricity and current trend ............................................................ 104Figure 3.7: Trend of global use and availability of electricity (source: UN data) ...................... 104Figure 3.8: Projected lines of use and availability of energy (source: UN data) ........................ 105Figure 3.9: Growth of electricity capacity assuming 6870 hours per year (source: UN data) ... 107Figure 3.10: Sources of production of electricity (source: UN data) .......................................... 107Figure 3.11: Capacity percentage -Production vs. installed capacity (source: UN data) ........... 108Figure 3.12: Diffusion of Wind Generation by State .................................................................. 116Figure 3.13: Diffusion of Solar Generation by State .................................................................. 117Figure 3.14: Energy generation using coal (source: World Bank database) ............................... 119Figure 3.15: Electricity generated using hydro power (source: World Bank database) ............. 119Figure 3.16: Electricity generated with natural gas (source: World Bank database) .................. 120Figure 3.17: Electricity generated using nuclear plants (source: World Bank database) ........... 120Figure 3.18: Electricity generated burning oil (source: World Bank database) ......................... 121Figure 3.19: Global energy generation sources (source: World Bank database) ........................ 121Figure 3.20: Worldwide top electricity generation producers .................................................... 122Figure 3.21: Diffusion Speeds of AMI for different states clusters ............................................ 128Figure 3.22: Diffusion Curves by Cluster of States by Division ................................................ 131Figure 3.23: Diffusion curves for the Top Ten States ................................................................ 135Figure 3.24: Diffusion Speeds of AMI for different states clusters ............................................ 136Figure 3.25: Diffusion curves by Utility Company Ownership .................................................. 137Figure 3.26: Diffusion Speeds for AMI depending on Urban Concentration............................. 138Figure 3.27: Electric vehicles produced in the U.S. ................................................................... 142Figure 3.28: Average Gasoline Prices (Source: eia.gov) ............................................................ 143Figure 3.29: Hybrid vehicles breakdown by brand ..................................................................... 144Figure 3.30: Number of PHEVs sold versus average price ........................................................ 145Figure 3.31: Plug-in Electric vehicles breakdown in the U.S. .................................................... 147Figure 3.32: Types of Cyber Attacks based on Chen et al. (2012) ............................................. 153Figure 3.33: Number of Breaches per Year ................................................................................ 156Figure 3.34: Number of Breaches Victims per Year .................................................................. 156Figure 3.35: Number of Breaches per Categories and Groups of Victims ................................. 157Figure 3.36: Number of Breached Victims by Group ................................................................. 157Figure 3.37: Diffusion of Wind and Solar Generated Electricity by Households ...................... 164Figure 3.38: Smart Meters Diffusion by Census Division and Total US ................................... 165Figure 3.39: Electric Vehicles Diffusion in the US .................................................................... 166Figure 3.40: Cyber Attacks Diffusion in the US......................................................................... 167Figure 3.41: Smart grid Technologies Diffusion Comparison.................................................... 168Figure 4.1: What is the smart grid? (Source: http://www.smartgrid.gov/the_smart_grid) ......... 170Figure 4.2: Environmental Performance Index (Esty et al., 2006) ............................................. 173Figure 4.3: ENSG Road Map for UK Smart Grid Deployment .................................................. 175Figure 4.4: The European Unions Smart Grid vision (source: VDE, 2010) ............................. 177Figure 4.5: NIST Smart Grid Framework 1.0 ............................................................................. 178Figure 4.6: Comparison of China and US/EU Smart Grids (source: Jiandong, 2011) ............... 179Figure 4.7: Masdar: The Sustainable City (source: http://masdarcity.ae/en/) ............................ 180xvFigure 4.8 Masdar City Energy (source: http://masdarcity.ae/en/) ............................................. 181Figure 4.9: Texas Smart Grid Investment Model (Source: SGRC) ............................................ 182Figure 4.10: Ontario Smart Grid (source: http://ieso-public.sharepoint.com) ............................ 183Figure 4.11: Enhanced Model by Blocks related to PDCA Cycle .............................................. 186Figure 4.12: Proposed Enhanced Model ..................................................................................... 187Figure 4.13: Comparison of 2010 Census results and survey respondents................................. 190Figure 4.14: Comparison of Educational Level of the Respondents vs. 2010 Census ............... 191Figure 4.15: Household income comparison of 2010 census and survey respondents ............... 192Figure 4.16: Survey smart grid focus importance evaluation .................................................... 193Figure 4.17: Who is responsible for smart grids technologies? ................................................ 194Figure 4.18: What is important for the society? ......................................................................... 196Figure 4.19: Personal importance responses ............................................................................... 197Figure 4.20: Range on cost of energy responses......................................................................... 198Figure 4.21: Smart Use of Energy Survey Model....................................................................... 200Figure 4.22: First PLS Model with Results ................................................................................ 203Figure 4.23: Detailed Enhanced Energy Management Business Model ..................................... 205Figure 4.24: Second PLS Model with Results ............................................................................ 219Figure 4.25: Total Electricity Consumption by Census Division ............................................... 225Figure 4.26: Total Electricity Revenue by Census Division ....................................................... 226Figure 4.27: Cost of Electricity per Census Division ................................................................. 226Figure 4.28: Regression Predicted Values for the Regulated Entities ........................................ 236Figure 4.29: Regression Predicted Values for the Formerly Deregulated Entities ..................... 237Figure 4.30: Regression Predicted Values for the Deregulated Entities ..................................... 237Figure 5.1: Diffusion of Smart Grid Distribution Technologies in the US ................................ 2421CHAPTER 1: INTRODUCTION 1.1 BACKGROUND INFORMATION Inthepastonehundredyears,countriesaroundtheworldhavebeeninvestingin monolithictransmission,distributionandgenerationinfrastructurestosupportgrowing electricity needs usually referenced in the sequence of the value chain, generation, transmission and distribution. Unfortunately, these infrastructures have not been robust enough, as there is an estimatedgloballossofenergyrangingfrom10to52%,mostlyduetodistributionlossesand theftswhichdependontheadvancementoftheavailabletechnologyandimplementedtheft controlsineverycountry(Najjaretal.,2012).TheselossesintheUSaresmallerthanmany othercountries,forinstancein1995theywere7.2%,with40%ofthelossescomingfrom transformers and 60% from the lines (Hong & Burke, 2010).Considering some of the concerns that have an environmental impact, the transportation and energy generation sectors are the top contributors of CO2 to the atmosphere, with 20% and 40% of the emissions respectively (Lo & Ansari, 2012). These sectors mostly depend on burning hydrocarbon based fuels that create emissions which then affect the environment. There is an old initiativetowardthegenerationofenergyusingrenewableresourcesbutithasnotreachedthe rightpriceyet,butatthesametime,consumersarebuyingmoredevicesformodernworld needs, namely consumer electronics, which only increases the demand of energy and, as a result of this process, more energy needs to be generated, hence more harm to our environment.Bytheyear2030,theconsumptionofelectricitythroughouttheworldisexpectedto increase76%(Ramchurnetal.,2012).Inordertosatisfythisrequiredelectricitydemand,the actual generation processes need to increase, thus increasing the emission of CO2 and SOx to the atmosphere.Toovercomethischallenge,manycountriesarewritingdirectivesandgoalsto 2reducecontaminationintheshortterm.Battaglinietal.(2009)refersspecificallytothemany environmental protection requirements set forth by the European Community.Toaddresstheseenvironmental concerns, there is an ongoing integration and growth of newcleanersourcesofenergysuchaswind,photovoltaic,naturalgas,nuclear,andothers. Renewable resources have been growing as well, including nuclear generation which has reached 6%oftheworldstotalproducedenergy.However,followingtheincidentprovokedbythe tsunami in the Fukushima nuclear plant in Japan on March 11, 2011, the reaction of the Federal Republic of Germany was to immediately close 8 nuclear sites and schedule the closure of the 9 remaining plants in 10 years (Rmer et al., 2012). The rest of the world is also taking precautions toreduceoreveneliminatenuclearenergygeneration,unlessabreakthroughtechnologyis discovered. Withthetaskofreducingglobalcontamination,scientistsandengineersfacethe challenge of reducing contamination and making better use of the currently generated electricity viareductionoflossesinherenttothedistributionandtransmissionprocessesofthetraditional grid.OnepossiblesolutiontothisproblemistheSmartGrid,whichisbasedonrecent technologies:TheSmartgridischaracterizedby:theefficientdistributionofenergywiththe inclusionofstateofcomputerpower,theuseofrenewableresourcestogenerateelectricity, participationoftheconsumersintheprocessbygeneratingand/orconservingenergy,low latencyfeedbacktoconsumersandutilitycompaniesaboutreal-timeconsumptionviasmart meters to be able to take advantage of smart rates, the use of electric vehicles batteries to store and distribute energy at homes, and distributed energy resources, among others. AlltheseSmartGridelementsarebeingdevelopedandevenimplementedinsome countries, while developing countries are waiting to see the results before following those steps. 3TheUnitedStatesseemstobetheleaderinthiseffortwiththesupportoftheElectricPower ResearchInstitute(EPRI),NationalInstituteofStandardsandTechnology(NIST),Department ofEnergy(DoE),NationalRuralElectricCooperativeAssociation(NRECA),EdisonElectric Institute (EEI), and the American Public Power Association (APPA) (Lo & Ansari, 2012).Other national governments are promoting efforts for the implementation of Smart Grids in the near future. For instance, Korea launched the K-grid project in 2002 (Son & Chung, 2009), India created the Indian Smart Grid Task Force (Mukhopadhyay et al., 2012), and China formed the Strong and Smart Grid (SSGC) (Uslar et al., 2012).There are important efforts in the promotion of Smart Grids in Europe, where one of the biggestconcernsseemstobetheimplementationofadvancedmetersandgreenenergy.The US, being leader in developing smart grids appropriated $4.5 billion of the American Recovery and Reinvestment Act (ARRA) to the Department of Energy (DOE) and the Office of Electricity DeliveryandEnergyReliability(OE)fordeploymentofprogramssuchasSmartGrid InvestmentGrant(SGIG)andtheSmartGridDemonstration(SGDP)ProgramTheElectric PowerResearchInstitute(EPRI)hasalsobeenworkingonthiseffortwiththeIntelliGrid Program which focuses on standards, interoperability and cyber security. WhenweconsidertheglobalamountofmoniesinvestedonSmartGridresearch,the majoritycomesfromtheUnitedStates,with31%asreportedbyBloombergNewEnergy Finance(BNEF).AlthoughtheUSistheleader,analystspredictthatChinawillovertakethis leadershippositionbecausetheSmartGridprogramlaunchedbytheObamaadministration comestoanendintheyear2015.Atthesametime,Chinaiscontinuouslygrowing,withan investment of $3.2 billion compared to the US that has already spent $4.3 billion in 2012.4TheSmartGridbringsatwo-waycommunicationandflowofenergy,insteadofthe traditionalone-wayflowfromtraditionalelectricity(Ramchurnetal.,2012)andinformation systems(Fadlullahetal.,2012).TheUSgovernmenthasinvested$3.4billiondollarsingrants for the investigation of Smart Grids (Gngr et al., 2011). As ICT has been evolving from wire-line to wireless media, there are important proposals abouttheconceptofZigBeesmartenergywithwirelesscommunicationstoremotelycontrol devices. The utility company or the consumer will be able to remotely turn appliances, or other devices,onoroffdependingontheirneedsandbasedonthecostofenergyorpresent environmental conditions.With all these technologies under the umbrella of Smart Grids, we chose to focus only on energydistributionfortheliteraturesurveyinchapter2.Distributionisacurrentfast-growing area and very visible to consumers, utility companies, and governments who are trying to involve thegeneralpublicinthisdiscussion.Ifdistributionisenhanced,theexpectedresultisenergy conservationtoavoidunnecessaryinvestmentsinnewlargegeneratingplantsbyreducing energy consumption.1.2 THE BIRTH OF A NEW MODEL ThroughthisdissertationwedevelopedtheadventofanewdecentralizedEnergy Management Business Model that is changing the role of the consumer, utilities and government with the emergence of new and advanced technology.The elements of the model are analyzed andmeasuredinregardstotheirimpactsontheimplementationofICTintheenergy managementsystems.Prioreffortshavetriedtofocusonconsumersparticipationviasmart houses(Tanakaetal.,2012)interconnectedwithcontrolsystemsthatincludedistributed generators and storage. In order to understand the growth of renewable resources generation, and 5inawaythediffusionofdistributedgeneration(DG),weresearchandanalyzeallsourcesof electricity generation in chapter 3. Anothercomponentofthemodel alsoincludesthevehicle-to-grid(V2G)asasourceof energy, where the battery pack is charged while being connected to the grid, and later, the battery will become a major source of energy (Khayyam et al., 2012; Erol-Kantarci & Mouftah, 2011).Chapter 5 presents the diffusion of electric vehicles for both Plug-In Hybrid (PHVE) and Plug-in Electric Vehicles (PEV). Although EVs are not considered commonly as sources of energy, their roleinthefutureseemstobecriticaltoachievetheenvironmentalgoalsbecauseoneofthe major sources of contamination are the emissions of the fuel vehicles on the road. A factor that needs to be carefully considered is the timing and places for charging batteries of these cars, or the suburbs will collapse at the evening hours when most people go home and plug the car to the grid.TherearemanystudiesusingParticleSwarmOptimization(PSO)asastrategyforthe battery charging process during the night (Celli et al., 2012; Sousa et al., 2012; Silva et al., 2012) Other scholars focus on the outcome of their own models, environmental protection being oneofthemostmentioned,(Lo&Ansari,2012),energyconservation(Feng&Yuexia,2011), andsocialparticipationviaconsumerswhoexploreenergyresourcespossibilities(Aliprantiset al.,2010).Basedonthepriormodels,wedevelopedourownenergymanagementmodelthat includessomeoftheabovementionedelementsthatarefurtheranalyzedinthefollowing chapters. 1.3 THE MOST IMPORTANT ELEMENTS Based on the literature review and analysis detailed in chapter 2, we consider information and Communication technology (ICT) as the main element of the model because it is the driver 6ofthemodel.Withoutcontemporaryadvancesintechnology,itwouldbeverydifficulttolook for the levels of efficiency that we can achieve nowadays.For instance, we can have a blackout and the backup source can be activated without our human senses perceiving it; also, informing consumersabouttheinstantaneouspriceofelectricity throughout the day could not be possible without computerized networks reaching every home and maintaining two-way communication.This communication has a potential issue, namely cybersecurity because with all meters connectedtohugenetworks,itwouldbeverydifficulttodeveloprobustenoughsystemsto preventattacks,andwhatismorecriticalandvulnerablefortheenergysectoristhefalsedata injection,aspresentedinChapter3.Althoughthesetypesofattacksarenotfrequent,the potential capability of detection is low, increasing the vulnerability of all energy systems, which nowrequireacomputerizedsystemtomonitortherequestsand,comparedtonormal consumption patterns, they can detect these types of breaches. From the different technologies under the umbrella of Smart Grids (SG), we specifically focusonthemostvisibleelementforSGintegration,thatis,theAdvancedMetering Infrastructure(AMI),orsmartmetersastheyarecalledinEurope.Theirdiffusioncanbe representativeoftheSGprogress,soweanalyzedthemusingtheBassDiffusionmodelin Chapter3.AsanewbusinessmodelwasproposedbyLehr(2013)withfocusontheutility companies, the analysis is conducted by region, division, ownership, and urban concentration of the population to better understand the trends and develop our prognosis. 1.4 THE ENHANCED ENERGY MANAGEMENT BUSINESS MODELThisdissertationcontributestotheInternationalBusinessliteraturebyproposingan enhancement to some of the Energy Management Business Models that present the relationships 7among the selected elements to determine if they are strongly influenced among themselves. The extensiveliteraturesurveyextendstheacademicknowledgeontheareaswhereliteratureis focusing and those areas that are being neglected at this time. The Model is presented in detail in Chapter4ofthisdissertationandissupportedbytwomodelsthataresimilarandgroundedin theory.Wehaveconductedalsotwosurveysthatbackupthemodel,asboththestructural equationmodeling(SEM)andPartialLeastSquares(PSL)modelssupportourproposal.In general,ourmodelseemstocoverthekeyrequirementsforaSmartGridmodel,anditis supported by other research and our primary data. Theenhancedmodelthatweproposeinthisdissertationintroduceshowdistributed generationandpossiblytheelectricvehiclewillprovideelectricitythatwillbestoredin distributedstoragetousethisenergywhennecessary,notasgenerated.Oncetheenergyis stored, it can be automatically distributed with ICT devices communicating through networks to theconsumersthatrequireit.Consumersingeneralwillhavetheabilityofrespondingtothe tariffinformation,sotheycanincreaseordecreaseconsumptionbasedonthereal-timecostof thisservice.Byreducingpeaksandoptimizingconsumption,weexpectefficientand environmental friendly energy. There are some new models but they are unilateral, with the utility company making all decisions,andconsumersjustacceptingthem.Theenhancedmodelforeseesdecentralized generation where consumers are important actors in the process. Another figure that might come forward very strongly is the service providers who will do the distribution of the available stored energy in a free market. The consumers will also have an important role on the demand response area, as they will decide when to use energy and when not.8Theinvolvementofallstakeholdersintheprocesswillcertainlyhelpforbetterresults. Utility companies have traditionally made most decisions along with the regulating bodies, while theconsumerperceptionandopportunitieshavenotbeenexploredyet.Allowingtwo-way communicationwiththeconsumeropensupahorizonofpossibilitiestomakethedistribution process more efficient. Tovalidatetheproposedenhancedmodelweusedtheliteraturesurveytoshowhow theseelementsarethemostimportantonesforpublishedresearchesatthistime.The relationshipsamongtheelementsweremodeledandvalidatedwithasurveyconductedto specialists in the field who show that the storage element is the only one that they do not see as importantbecauseweareintheprocessofdesigningbetterbatteries,andthisistheAchilles heel.Weknowthatatthistimethereisnogoodoptionasofyet.Thepracticalproofofthe modelisnotpartofthedissertation,becauseitwouldhavetobeimplementedandwedonot have the resources. This is a conceptual enhanced model. 1.5 RESEARCH QUESTION AND OBJECTIVES Withtheproposedmodelweaimtoanswerthefollowingproblemstatement:Howcan we,asaglobalsociety,preparefortheimminentparadigmshifttowardsdistributedgeneration anddistributionautomationwithICTandothertechnologies,whichintroduceanewbusiness model where consumers might also be producers, whereby millions of connections can make our systemsvulnerable,andtheeconomicsseemunfeasible?Inordertoanswerthisquestion,we divide the dissertation into three major blocks to achieve the following objectives: Understand the global position of Smart Grid based on peer-reviewed publications Study diffusion models and risks for technologies enhanced with ICT 9Analyze and design a business model with consumers being also producers of energy. 1.6 CONTRIBUTIONS OF THIS DISSERTATION Thisdissertationbringsforthcontributionstothebusinessadministration,information systemsandenergyareas.TheSmartGridisatopicthatrecentlyappearedandalongwiththe InformationandCommunicationTechnology(ICT)isprovokingmajorchangesinthe distributionofelectricitythroughouttheworld.Beingsuchanewtopic,therearenotmany studies focusing on this area and this dissertation contributes with studies never done before. The major contributions in this dissertation are: AFadorfashionstudyforpeer-reviewedliterature,fromInternet&WebofScience about Smart Grid, applied to this area for the first time. Anexhaustiveliteraturesurveywasconductedon966papersaboutSmartGridto classify them into six categories set by Chicco and the different technologies. A model was developed for Green Efficient Energy based on global Roadmaps. Theperspectivesofgovernment,practitionersandacademicsonregardstoSmartGrids were compared with a novel simple classification method. Diffusion curves for Solar, Wind, Electric Vehicles and Cyber breaches for the first time. Partial least Squares (PLS) models were developed to support the proposed model. First evaluation of Smart Grid by 184 professionals not involved in the specific field, but responding as consumers of electricity. A snapshot of the opinion of 32 specialists in the field about the elements in the model A proposed energy management model validated with a survey using questions from the Carnegie Melon Smart Grid Maturity model for utilities. 10CHAPTER 2: COMPREHENSIVE RESEARCH IN SMART GRID2.1 BACKGROUND INFORMATIONItisprojectedthatoilandgasreserves will be depleted by 2060-2065 (Klimenko et al., 2008). Needless to say, in the face of dwindling carbon based fuel reserves and fears associated with energy independence, there is considerable attention being paid to energy conservation.Whiletherearenumerousinitiativestoconserveenergy,oneofthemorepromising approachesofachievingenergyefficiencyisasuiteofintelligenttechnologiesheldunderthe umbrellaofaSmartGrid.TheSmartGridreliesonintelligentsystemstomakereal-time decisionsthatcansaveenergywithoutinconveniencingtheconsumer.Makingthesmartgrid successfulwillrequireacreativeandmultidisciplinaryapproachfromareassuchaspowerand systemsengineering,security,businessintelligence,socialnetworking,mathematicalresearch, and others. (He, 2010) In1940,10%oftheenergyconsumptionintheUSwasusedtogenerateelectricity;in 2003 it was 40% (US DoE, 2003), and in 2012 the level still remains around 40%, according to the DoE website (http://www.eia.gov). The largest man-made contributing factor that harms the environmentistheenergyproductionprocessesthatuseCO2emissions(Jiangetal.,2009). Amongthisandotherfactors,wearefacingglobalwarming,whichisexpectedtoincrease5 degrees in global temperature by the end of the 21st century, which has not occurred in 70 million years (Klimenko et al., 2009). Forthepast25yearstheconstructionoftransmissionfacilitiesintheUnitedStateshas decreased as energy demand increased, resulting in grid congestion. To prevent this situation, the DepartmentofEnergy(DoE)isworkingontheimplementationofsmartgrids,following 11President Bushs signing of the project Grid 2030 in 2003 (US DoE, 2003).Smart grids seem to be the future for energy conservation, as they are expected to save 10% of the energy used in the US by focusing on providing the required amount at the right time. The smart grid concept also includes other technologies, including: Demand Response (DR) to manage consumption responding to supply conditions Electric Vehicle (EV)/ Plug-in hybrid electric vehicle (PHEV)DistributionAutomation(DA) intelligentcontroloverelectricalpowergriddistribution levelCommunity Energy Storage (CES) presenting an alternative to store energy at suburbs AdvancedMeteringInfrastructure(AMI)systemsthatcollectandanalyzeenergy consumption data. The nomenclature of smart meters was included in this category as it is the name used at Europe. Distributed Storage (DS) as a smart way to reserve the available energy DistributedGeneration(DG)lookingforabetterwaytogeneratedecentralized electricity. AlthoughSmartGridsareverypopular,therearestillsomeunansweredquestionsabout future uses, as its strengths and weaknesses are not recognized because their anticipated benefits have not been fully received yet. The purpose of this chapter is twofold:Clearly define what is expected from the use of smart grids; this can be accomplished by conducting a SWOT analysis using the available information; andInvestigatewhetherthemultipletechnologiesundertheumbrellaofthesmartgrid conceptarebeingacceptedandpromotedworldwideinwhatjurisdictionsandunder what study areas. 12ThefirstpartofthechapterwillresearchdefinitionsanddevelopaSWOTmodel.The secondpartofthepaperusesabibliographicanalysistoidentifymentionsofsmartgridsin worldwide literature, applying the Management Fashion Theory (Abrahamson, 1991). 2.2 THEORETICAL BACKGROUND2.2.1Smart Grid Concept DefinedThelargestmachinewithmultipleinterconnectionsintheworldistheUSpowergrid, whichincludesover9,200generatorsand300,000milesoftransmissionlines.TheUSpower grid generates more than 1,000,000 megawatts (He, 2010). Modernizing and further developing this huge machine will require a clear focus on the goals of the project.To better understand SG, we define the concept as an approach to modernize electrical distribution that would transform the way that a utility interacted with its customers in order to provide a higher level of service and reliability, put the customer in control of their energy costs, and to achieve energy conservation and sustainability goals (Sarfi et al., 2010, p.200). Afterconductingthoroughresearch,wecandefineSmartgridsasefficientwaysto conserveenergyandpreventwaste;theyoughttobeaccommodating,asthefutureofenergy might not be based on hydrocarbons but other sources of energy. Motivating users to do energy required activities at the proper time can be accomplished with smart grids. SGs shall be quality focused to do things correctly every time. The opportunistic concept of the vision means that it willtakeadvantageofanyopportunity that might arise and integrate it as a plug and play. The resilientrequirementofthemodeliscritical,asthesmartgridshallbepreparedtoresistany cyber-attack.Greenisthenamegiventoanyenvironmentalactivityandthevisionofasmart gridshallbeenvironmentallycompliant.Andfinally,themodelhastobeintelligent,whichis 13indeed the toughest requirement, as it is expected that the grid shall have enough information and programming that it would react smartly to any behavior (He, 2010) The architecture of a smart grid is very important but its decision making mechanisms are equally critical for they: Shall be flexible to accommodate needs of different utilities, Shall extend to the ever changing requirements, Shall be open to interoperate with other different providers, Shall handle and degrade faulty conditions such as noisy data (Davidson et al., 2010). Lessessential,butcertainlydesirable,areextendedcapabilitiessuchasutilizingall availabledatawithinautilitytoinfluenceoperation,andallowingutilitiesthemselvestoselect the level of automation for a given situation or scenario.Theareasofapplicationofsmartgridsinclude:smartmetersintegration,demand management,smartintegrationofgeneratedenergy,administrationofstorageandrenewable resources,usingsystemsthatcontinuouslyprovideandusedatafromanenergynetwork (Davidson et al., 2010) 2.2.2SWOT AnalysisStrengths: Self-healingsystemsaredesirabletopreventdependenceonhumaninterventionatcritical moments; by providing the systems with enough data, they can make smart decisions at the right moment: artificial intelligence (AI). With the tremendous growth of digital technologies, providing information faster and with fewer 14errors in communication, the smart grid will utilize a digital platform (Jiang et al., 2009) Demand and load management are critical parts of the concept, as they helps to optimize delivery and consumption by reducing customer demands at peak hours (Liu, 2010)Thesmartgridshallnothaveacentralvulnerablesystemthatcoulddeactivatethewhole network using decentralized control schemes (Jiang et al., 2009) One of SGs most important features is that it can be customized to specific needs/wants (Jiang et al., 2009) Thefutureofhydrocarbonresourcesislookingweaker,Therefore,somegenerationshaveto consider the integration of intermittent renewable resources, such as wind, solar, etc. (Liu, 2009)Smartsub-stationsoughttobeautonomousandhaveenoughinformationanddatatooptimize their continuous operation (Jiang et al., 2009) Another important feature of SG is that, due to the system transparency, we are able to see what is happening at all times in real-time (Liu, 2009) Weaknesses: Cyber security anticipates compromises of adjacent systems. This has been a major concern area addressed by IT under SG (Overman & Sackman, 2010) Asmartgridcontainssomanysensorsanddevicesthatitincreasesthesystemcomplexityfor maintenance and repairs (Overman & Sackman, 2010) There could be failures in communications link, sensor and/or actuator, unplanned control center systemfailure,andnonexistent,late,orimpropercommandsbyuntrainedand/ordistracted control room personnel (Overman & Sackman, 2010) AsmoremodernandstateoftheartdevicesareintegratedintotheSG,therearepossible compatibility issues (Bull, 2010) 15Opportunities: Cyber security controls will become more critical in future systems (Overman & Sackman, 2010) Balancing demand and generation using SGD can achieve optimal flow (Davidson et al, 2010) Aninformationsecurityactivedefensemodelwillnotonlyprotectbutalsodefendthesystem from attacks and unexpected responses (Zhang, 2010) SG can have decentralized storage areas to achieve the desired system balance (Slootweg, 2009) Threats: Communication channels in the future may be more dedicated (Jiang et al, 2009), creating a need for dedicated conduits for SG, affecting cost and reliability of the system. Duetothecomplexityofgrid,itmightnotbeeasytoprovidetechnicalsupportfromasingle source (Bull, 2010) As web applications are preferred targets of hackers (Bull, 2010), the SG might be attacked until its vulnerabilities are found. New regulations may have an impact on the grid as well (US DoE, 2003) Figure 2.1: SWOT Analysis 162.2.3 Hypotheses H1 Inthisglobalenvironmentthatwelivein,weareseeingthatsomeconceptsrelatedto conservationandbetterutilizationofenergyareinvogue.Weexpectthatworldwideliterature should also reflect this emphasis on Smart Grid Distribution (SGD), as this is one of the goals of thisdissertationtoachieve.Therefore,wepresentourfirsthypothesiswhichclaimsthatthere shall be an upward trend in scholarly literature about this subject. H1a: Smart Grids research shows growth of published papers in global literature. There is a possibility of SG becoming just a fad. To understand if it is indeed a fad or if it is becoming a fashion or a concept that will persist for a long time we will use the methodology used by Ponzi and Koening to analyze the lifecycle and diffusion of new concepts. Specifically, we will utilize bibliometric techniques (Ponzi & Koening, 2002). The lifecycle of a fad is shown asaquicklyincreasingconceptinpopularitythatpeaksanddisappearsveryquickly,whilea fashion grows more slowly, matures and stays atop for a while and begins to come down slowly (Abrahamson,1991).ItisourexpectationthatSGhasnotreachedthematuritytobegin declining, so we propose our second hypothesis: H1b: Smart Grid Distribution has not reached the maturity stage of its global lifecycle.Aspresentedinthepapersintroduction,therearemanydifferenttechnologiesthatare correlatedtothemainconceptofSG.Entitiesarepushingtechnologiesaccordingtotheir strategicplansandneeds;therefore,iftheyhaveadifferenttechnologicalneed,theirdefinition and interpretation of SG is going to vary as well. Thus our third hypothesis proposes that:H1c: There is a different emphasis on Smart Grid Distribution technologies literature based on the number of articles published by regulatory jurisdiction. 17As we conduct bibliometric studies, we shall propose a null hypothesis that the number of articles mentioning every technology is going to be equal for all countries and states. So our final hypothesis claims that: H1d: All technologies under the SG umbrella are equally mentioned in the literature 2.3 METHODOLOGY FOR TAXONOMY RESEARCHWe counted the number of articles containing the words smart grid, eliminating those papers with citations only to ensure the selected articles are referring to the concept and are not only references. The research was conducted using Google Scholar for all papers published from January 1st. 2001 until December 31st. 2010. Once the information was retrieved, we developed charts with the annual counts of articles over this period on a yearly basis to see if the shape of the chart shows a fad, a fashion or a growing concept and so support hypotheses 1a and 1b. InordertocorrelatethemainareasofstudyofSG,weonlyconsideredthefollowing disciplines:engineering,business,physics,chemistry,environmentalandsocialsciences.Itis ourexpectationthattheengineering,physicsandchemistrystudyareasrepresentthetechnical aspectbehindSG,whilethebusiness,environmentalandsocialsciencesprovidetheplanning aspectas they refer to goals, strategies, and non-technical implementation plans. TechnologiesundertheconceptofSGarealsoseparatedtosupporthypotheses1cand 1d, because these technologies will show if there is a different perception in regards to SG at the different jurisdictions. We used only some of the technologies, DA, DR, EV/PHEV, AMI along withsmartmeters,DS,etc.Wewillfinallyprobecountriesandevenstatestocorrelate technology to every jurisdictions perception. 182.3.1Google Scholar Research Results ResearchingGoogleScholarforworldwidearticlescontainingSGandtheabove mentionedtechnologies,wewereabletofind5,125articleswritteninthetenyearperiod.The trendchartshowsexponentialgrowththatcanbebetterseenusingalogscaleasshownin Figure 2.2. The number of articles written about smart grids has been increasing exponentially, and there are no signs of decrement.Based upon these findings we can support both hypothesis 1a and 1b, as we see a rapid growth of worldwide articles without showing signs of stagnation or decrement that may signal the smart grid concept being a fad. The trend is still going up or it is about to reach its maturity level before stabilizing and then going down. To better understand the studyareasthatarepromotingthisgrowth,wecategorizedofarticlesbasedontheirareaof specialization. Figure 2.2: Log trend line of SG articles Theareawiththehighestnumberofmentionsisengineering,astheknow-howabout technical achievement of SG is being developed. Far in second place is the business area which accounts only for 20% of the engineering articles, as shown in Figure 2.3 19 Figure 2.3: Selected articles by categories Tohaveabetterviewofthegrowth,anddetermine if the technologies are beginning to slow down and become stagnant, we calculated the percentage increments on a yearly basis per category. The chart shows that the social sciences, environmental and business areas are growing atslowerratesthantheothersciences.Thismightbeasignofthemgettingclosertoreaching maturity.Inotherwords,wemightsaythatthefoundationforSGinthesocial,environmental and business areas has been set and the maturity phase will begin with smaller growth and even decreaseintheupcomingyears.ThiscanbeseeninFigure2.4,associalandenvironmental sciences are decreasing in growth.The previous charts support hypothesis 1a and 1b in that the overall trend in worldwide literature is still growing. The SG concept has not reached maturity, as there are no signs of stagnation or decrements in growth. In the business, environmental and social sciences, the trend seems to be slowing down and even reaching maturity, but this is still to be shown. On the other hand, engineering, physics and chemistry disciplines are still growing rapidly in literature about the concept and details on how to build and improve SG. 20 Figure 2.4: Growth of SG by discipline

Figure 2.5: Time series for SG technologies (Cardenas et al., 2011) FocusingonthetechnologiesundertheSGumbrella,wedidthetimestudyshownin Figure2.5.Thisstudyintroducesdistributionautomationasthefirsttechnologythatwas mentionedinSGliterature,whileCESisthelasttechnologyappearinginthepapers.All 21technologiesareshowingimportantincrementsinthepastyears,andnoneofthemaregiving signsofslowingdownyet.Thelinesareshowingexponentialgrowthinmostinstances,such thatwecanconclude,lookingatFigure2.5,thatDemandResponse(DR)isthetermmore commonlyassociatedwithSGinthereviewedliterature.Thisisnotpeculiar,asthesmartness conceptislinkedtorespondingintelligentlytothedemandandsupplyenergylevels.The2nd technologyinnumberofmentionswasAMI,betterknownassmartmetering,whichhasbeen highly accelerated in the past 2 years.

Figure 2.6: SG technologies per country WeaskedourselvesiftheSGconcept,technologiesandtrendsarethesameallaround theworld;sowetookliteratureanddataminedthedefinitionconceptsfromFigure2.5and related them to the countries that are implementing it. The results show that the United States is numberoneinSGmentionsinliterature.ThesecondplaceisalmostatiebetweentheUnited KingdomandChina.Afterthegeneralinterestondemandresponse,theUKfocusesonsmart 22metering while Chinas main interest revolves around electric vehicles. Germany and Canada are closeinfourthandfifthplacewithsmartmeteringastheirkeyinterestafterDR.Manyother important points can be noted by looking at Figure 2.6. We support hypothesis 1c and reject hypothesis 1d because we can see that every country has a different perception of what SG is, and not all the concepts are mentioned equally. Because thecountrywiththemostarticlesrelatedtoSGistheUnitedStates,wefurtherresearchedand subdivided the papers into the different technologies under the SG umbrella per state. There have beensomesuccessfulimplementationsofSGtechnologiesatsomestates,sodataminingby states we found some interesting facts shown in Figure 2.7. California and Pennsylvania are the leadersinregardstotechnicalpapersaboutsmartgridimplementation,followedcloselyby TexasandIllinois.ItisinterestingtonotethatNewJerseyispayingmoreattentiontosmart metering than demand response as all other states do. In the US, we can also support hypothesis 1c for every states perception in regard to SG, which are different and their levels are not equalthus rejecting hypothesis 1d. The technologies mentioned for the US and the world follow the same path: demand response is number one at the selected countries and even states in America. Second and third place are also the same for smart metering and electric vehicles. For a better idea on the perceptions at every state, we normalized theresultsandcalculatedthepercentageofwrittenarticlesperstateandtechnologytoconfirm the interest of every state in regard to the SG technologies. The results are shown in Figure 2.8. For demand response, the average percentage of mentions was 36%, with California and NewJerseybeingtheleastinterestedinthisareawith23and22%ofarticlesalthoughtheir interestwasbiasedtowardsmartmetering.Smartmeteringandelectricvehiclesaretiedin second place in regards to mentions in the literature for the selected states. Electric vehicles are 23receivinganimportantpushfromColoradowhile smart meters have spread support throughout the states. On distribution generation Texas and Florida are the least interested states while New Jersey is the one showing the most interest. Figure 2.7: SG technologies by state Figure 2.8:Normalized articles mentions of technology per state 242.3.2Preliminary Conclusions of Google Research Based on the research conducted using Google Scholar, in the period from 2001 to 2010, wecanconcludethattheSGconcepthasbeengrowingrapidlyaroundtheworld.Theconcept hasnotreachedtheexpectedmaturitylevel,butbecausethebibliometricstudyshowsthatSG has experienced growth in the past but is beginning to slow down now, we doubt that it is a fad. UntilthenumberofSGpapersstabilizesordecreasesinnumber,wemightbeableto conclude if it is a fashion, as we expect the number of articles to reduce slowly until it goes to a minimal level; a fad would grow quickly, reach its peak, and then diminish rapidly. Thus we do notexpectSGtobeafad(Cardenasetal.,2011).DissectingtheSGconceptintothedifferent technologies related to the SG concept, we are able to see that the individual components are also growing and none of them has reached the maturity stage yet; although the growth has taken over 7 years, so we do not expect them to be fads either.Withthebusiness,socialscienceandenvironmentaldisciplinesshowingincreasesof around100%inthepastyear,wecaninferthatthesestudyareasseemtobeslowingdown comparedtotheengineering,physicsandchemistryareaswithyearlygrowthsfrom271to 715%. Worldwide,wefoundthatdemandresponseistheconceptmorecloselyrelatedtoSG followedverycloselybysmartmetersandelectricvehicles.Thisissurprisinggiventhat distribution was expected to be more related than electric vehicles, showing a global perspective of energy conservation, enhanced distribution, optimized generation, and intelligent consumption breakingawayfromthecurrentenergyschemestowardsagreenerenvironmentandsmarter systems driven by business intelligence.25Table 2.1: Results of Hypotheses H1 2.4 LITERATURE SURVEY USING ISI WEB OF SCIENCE In order to use a more rigorous method forpaperpublication,we analyzeandcountthe peer-reviewedarticlespublishedcontainingthewords:SmartGrid&Distribution.Two differentpublishingsourceswereused:conferenceandjournalpapers.Thisresearchwas conductedusingtheISIWebofScienceforseriousacademicpeer-reviewedpaperspublished fromJanuary1st.2008untilDecember31st.2013.Itisimportanttoemphasizethatthefirst mention of SG happened in 2008, for that reason we are analyzing up to 2013, to include more thanfiveyearsofinformation,anearlierversionofthisliteraturereviewwaspublishedbythe JournalofCleanerProduction(Cardenasetal.,2014).Inaperiodofoneyear,fromthetime whentheoriginalpaperwaswrittentothetimeoftheconclusionofthisdissertation,over150 papers were added to ISI listing. Therefore, we expect the same to happen in 2013, thus we are not worried about the lower number of conference papers in the past year. 262.4.1Hypotheses H2While the field holds many publications, in this section we are going to focus exclusively on peer-reviewed papers. We expect that the behavior of academic reviewed articles is going to be the same as the more general Internet listing site. Thus, we develop the following hypothesis: H2a: Peer-reviewed conference and journal papers about SG are still showing growth. Smart Grid literature has been mostly related to engineering, specifically focusing on its technical aspects. It is our expectation that most serious literature will be devoted to developing theories for its Smart Grid implementation. Because SG is such a new concept, new technologies and new operating philosophies have to be developed to achieve the expected results (Klein et al. 2011).Thus,throughthepeer-reviewliterature,wewillanalyzeifthetechnologyhasmatured enough to be at the theory building, testing or implementation stage. H2b: Smart Grid Distribution literature is more focused on theory building and testing than empirical implementation.IfthediffusionofSmartGridDistributionliteratureisreachingatleasttheearly majority,thereisgoingtobeenoughexamplesfromcaseorfieldstudiestobeanalyzedinthe articles and develop prognoses for future implementations. As technology evolves, the need for accurate operating information becomes paramount (Bank, 2012.) Due to the newness of SGD, it is our expectation that there are more case studies than sources of data at this time: H2c: The majority of peer-reviewed papers collect data from case studies rather than other research sources.In the early 70s Akao and others developed the Quality Function Deployment (Chan and Wu, 2002) This technique presents a sequence for planning the product or service all the way to processcontrol;basedonthistheory,weexpectstrategy(planning)bethefirstpartofthe 27implementationprocess,whilecontrolwillbethelastpart.BecauseSGDisanewtechnology, we expect most papers to be related to strategy instead of process controls, or quality focus. The next hypothesis proposes that:H2d: Strategic papers have a leadership role over quality focus on efficiency and control. Withthegreenrevolutionpushinthenewmillenniumandanincreaseonenergy demand,thenewenergyhastobegeneratedfromrenewablewind,solarandtidalresources (Ramchurn et al., 2012). If renewable energy is correlated to the SG concept, we expect that the generationofenergyusingrenewableresourceswillbecorrelatedtothenumberofpapers writtenonSGD.Thenamefortherenewablegenerationofenergyiscoinedunderdistributed generation(DG)ordistributedenergyresources(DER).Althoughthenecessaryinvestmentis high at first, the benefits are being studied throughout the world, such that we can expect that: H2e: Distributed Generation is steadily growing in importance throughout the world.The United States has been the leader on some technologies in the past. Recently, the US hasbeenthecreatorofprogramssuchasIntelli-Grid,Gridwise,ModernGridInitiative,and Smart2030,whichhavebeenpropelledbythestimulusplan(ARRA).Withthisinvestmentin SmartGrids,weexpecttheUStobetheleaderinthegenerationofliteraturefocusingon planning and strategies for the future. H2f: The US is the leader in peer-reviewed SGD literatureConsidering the country of origin of the writers, it is our expectation that most papers for bothconferencesandjournalswouldbefromtheUS,butwhatabouttheeconomicblocks?Is Americaaleaderinpeer-reviewedconferenceandjournalpaperswhencomparedagainstthe EuropeanorAsianblocks?BecauseAmericais verymuchrepresentedbytheUSandCanada, 28we expect that the leadership position might be challenged by the European Union or the Tigers of Asia, but America may still be the leader.H2g: America is the leader on SG conference papers in the worldH2h: America is the leader on SG journal papers in the worldConference papers are preliminary journal papers in nature, so we expect that the number of conference papers will predict the number of journal papers in that subject matter. Because the number of peer-reviewed conference papers is much higher than journal papers, that relationship might be linear:H2i: Journal papers follow a linear regression to the number of conference papers in the SG subject. 2.4.2Research PurposesFollowing the method used by Cardenas et al. (2014) and Gupta et al. (2006) the selected published papers are also classified into the three categories of research: theory building, theory verifying,andtheoryapplication.Theorybuildingisgoingtoincludethepublishedpapersthat present new theories or formulate existing ones; theory verifying include the research that prove previouslypresentedtheory,whiletheoryapplicationarepracticalpapersthatpresenthowthe technologies are implemented in the field. Inthecategoryoftheory-buildingauthorsdevelopnewrelationships,algorithms,or hypothesestobeconfirmedinfutureresearchpapers(Kleinbergetal.,2009).Althoughthis literaturesurveyiswrittenfromthesocialscienceperspectiveofInformationandDecision Sciences,thesepapersarerequiredtobeconceptualandalsocontainempiricaldatatosupport theauthor(s)hypothese