Analysis of institutional adaptability to redress electricity infrastructure vulnerability due to climate change

Transcription

1 Analysis of institutional adaptability to redress electricity infrastructure vulnerability due to climate change Final Report John Foster, William Paul Bell, Phillip Wild, Deepak Sharma, Suwin Sandu, Craig Froome, Liam Wagner, Suchi Misra and Ravindra Bagia

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3 Analysis of institutional adaptability to redress electricity infrastructure vulnerability due to climate change The University of Queensland and University of Technology, Sydney Authors John Foster The University of Queensland William Paul Bell The University of Queensland Phillip Wild The University of Queensland Deepak Sharma University of Technology Sydney Suwin Sandu University of Technology Sydney Craig Froome The University of Queensland Liam Wagner The University of Queensland Suchi Misra University of Technology Sydney Ravindra Bagia University of Technology Sydney

4 Published by the National Climate Change Adaptation Research Facility 2013 ISBN: NCCARF Publication 114/13 Australian copyright law applies. For permission to reproduce any part of this document, please approach the authors. Please cite this report as: Foster, J, Bell, WP, Wild, P, Sharma, D, Sandu, S, Froome, C, Wagner, L, Misra, S & Bagia, R 2013, Analysis of institutional adaptability to redress electricity infrastructure vulnerability due to climate change, National Climate Change Adaptation Research Facility, Gold Coast, 345 pp. Acknowledgement This work was carried out with financial support from the Australian Government (Department of Climate Change and Energy Efficiency) and the National Climate Change Adaptation Research Facility (NCCARF). The role of NCCARF is to lead the research community in a national interdisciplinary effort to generate the information needed by decision-makers in government, business and in vulnerable sectors and communities to manage the risk of climate change impacts. Disclaimer The views expressed herein are not necessarily the views of the Commonwealth or NCCARF, and neither the Commonwealth nor NCCARF accept responsibility for information or advice contained herein. The University of Queensland through the Energy Economics and Management Group (EEMG) and University of Technology, Sydney through the Centre for Energy Policy (CEP) have exercised due care and skill in the preparation and compilation of the information and data set out in this publication. Notwithstanding, EEMG and CEP, their employees and advisers disclaim all liability, including liability for negligence, for any loss, damage, injury, expense or cost incurred by any person as a result of accessing, using or relying upon any of the information or data set out in this publication to the maximum extent permitted by law. Cover Image Craig Froome

5 Contents 1. Introduction Chapter outline Selecting emission and climate change scenarios: Review Projecting change in temperature using SRESs and GCMs Selecting among the GCMs and SRESs for this project Distinguishing between a weather profile and a climate change baseline Selecting a weather profile year for this project s baseline Projected change in temperature from 1990 to Projected change in downward solar radiation from 1990 to Projected change in wind speed from 1990 to 2030 by season Projected change in relative humidity from 1990 to Projected change in rainfall from 1990 to Projected change in sea level, temperature and acidity Extreme weather events Conclusion Selecting emission and climate change scenarios: Research Selecting the baseline weather year Methodology Results Conclusion Further Research Selecting the global climate model and emissions scenario Methodology Results Discussion Conclusion Further research Discussion Conclusion The impact of climate change on electricity demand: Review Demand profiles Short-run and long-run drivers for electricity demand Weather and other short-run drivers for electricity demand Analysis of institutional adaptability i

6 4.4 Climate and population as long-run drivers for electricity demand The link between economic growth and growth in demand for electricity Smart meters as long run drivers for reducing electricity demand Energy efficiency as a long run driver for reducing electricity demand Higher prices and acclimatisation as long run drivers for demand Conclusion The impact of climate change on electricity demand: Research Gross and net demand difference requiring non-scheduled generation modelling Methodology Results Discussion Conclusion Further research Modelling demand for the baseline weather year Methodology Results Discussion Conclusion Further research The effect of climate change on electricity demand by node Methodology Results Discussion Conclusion Further research Discussion Conclusion The impact of climate change on generation and transmission: Review Transmission and distribution Coal Gas Diesel Biomass and Biogas Solar Wind ii Analysis of institutional adaptability

7 6.8 Storage Hydro Geothermal, wave, off-shore wind, power-to-gas and other options Off-shore wind and wave power Solar thermal heating and cooling and power-to-gas Lifecycle carbon footprint of generating technologies and transmission Portfolio of energy sources and baseload as a source of maladaptation Conclusion The impact of climate change on generation and transmission: Research Validating the model by comparing projections based on actual and projected demand Methodology Results Discussion Conclusion Wholesale spot prices Methodology Results Discussion Conclusion Energy generated by type of generator Methodology Results Discussion Conclusion Further Research Carbon emissions Methodology Results Discussion Conclusion Further Research Transmission line congestion Methodology Results Analysis of institutional adaptability iii

8 7.5.3 Discussion Conclusion Further Research Discussion Conclusion The effects of changes in water availability on electricity demand-supply Introduction The relationship between climate change, water availability and the electricity sector Climate change and electricity demand: nature of impacts Climate change and electricity supply: nature of impacts Climate, water and electricity linkages Methodological framework Review of methodologies Modelling approach Scenario descriptions Climate change scenario assumptions Assessment of the impacts of climate change on electricity demandsupply Impacts of climate change on electricity demand Impacts of climate change (and water availability) on electricity supply Assessment of the adaptability of existing institutional arrangements to climate change Institutional arrangements in the National Electricity Market Description of institutional arrangement scenarios Assessment of alternative institutional arrangements Assessing the current institutional arrangements for the development of electricity infrastructure to inform more flexible arrangements for effective adaptation Feed-in tariffs incorporating a renewable energy bonus Carbon pollution reduction scheme Mineral resource rent tax supplementing the CPRS Renewable energy targets Smart Grids Institutional complexity and the NEM grid as a natural monopoly Privatisation induced maladaptation and alternatives Further criticisms of the CPRS iv Analysis of institutional adaptability

9 9.9 Further alternatives or compliments to the CPRS Climate Change Levy in the UK Renewable Energy Sources Act in Germany Discussion Institutional fragmentation, both economically and politically Distorted transmission and distribution investment deferment mechanisms Demand side management A smart grid road map for Australia Air conditioners requiring special treatment Addressing energy poverty Changing remuneration calculations for network service providers Lacking mechanisms to develop a diversified energy portfolio Modified RET and reverse auctions for cost effective diversification Power Purchase Agreements: a barrier to a diversified energy portfolio Connecting to the grid a further barrier to a diversified portfolio Feed-in tariff reverse auction candidates Optimal portfolio of renewable energy to reduce overall costs Failing to model and to treat the NEM as a national node based entity rather than state based Misinformed policy Provision of node based data Locational Marginal Pricing Company boundaries between NSPs are weakness in the network Summary Conclusion APPENDIX A Selecting global climate models for this project B Node diagrams of the Australian National Electricity Market C Australian National Electricity Market Model C.1 Outline of ANEM model C.2 Principal features of the ANEM model C.2.1 Transmission grid characteristics in the ANEM model C.2.2 Demand-side agents in the ANEM model: LSEs C.2.3 Supply-side agents in the ANEM model: generators Analysis of institutional adaptability v

10 C.2.4 Passive hedging strategy incorporated in the ANEM model C.3 DC OPF solution algorithm used in the ANEM model C.4 Practical implementation considerations D Validating the ANEM model for this project D.1 Methodology D.1.1 ANEM performance metrics D.1.2 Calculation of performance metrics D.2 Results D.2.1 ANEM simulation results for in the absence of a carbon price D.2.2 ANEM simulation results for for a carbon price of $23/tC D.3 Discussion D.3.1 ANEM simulation results for without a carbon price D.3.2 ANEM simulation results for for a carbon price of $23/tC E Wholesale spot prices E.1 Background E.2 Methodology E.3.1 Performance metrics used E.3.2 Calculation of performance metrics E.4 Results E.4.1 E.4.2 Impact of climate change on wholesale spot prices for the period to without a carbon price Impact of climate change on wholesale spot prices for the period to in the presence of a carbon price of $23/tC F Energy generated by type of generator F.1 Methodology F.2 Results F.2.1 F.2.2 Impact of climate change on generation dispatch patterns for the period to in the absence of a carbon price Impact of climate change on generation dispatch patterns for the period to in the presence of a carbon price of $23/tC G Carbon emissions by state and fuel type G.1 Methodology G.2 Results G.2.1 Impact of climate change on carbon emissions for the period to in the absence of a carbon price vi Analysis of institutional adaptability

11 G.2.2 Impact of climate change on carbon emissions for the period to in the presence of a carbon price of $23/tC H Transmission branch utilisation and congestion H.1 Methodology H.2 Results H.2.1 H.2.2 Impact of climate change on transmission branch utilisation and congestion rates for the period to in the absence of a carbon price Impact of climate change on transmission branch utilisation and congestion for the period to in the presence of a carbon price of $23/tC References Analysis of institutional adaptability vii

12 Figures Figure 2-1 A comparison of daily extreme maximum temperature from 2008 to Figure 2-2 A comparison of daily extreme mean temperature from 2008 to Figure 2-3 Predicted national annual temperature change from a 1990 baseline to Figure 2-4 Predicted annual solar radiation change from a 1990 baseline to Figure 2-5 Predicted seasonal wind speed change from 1990 to 2030 for SRES A1B 20 Figure 2-6 Predicted change in relative humidity from a 1990 baseline to Figure 2-7 Predicted change in rainfall from a 1990 baseline to Figure 4-1 Examples of the NSW intraday demand for a typical summer and winter day Figure 4-2 Relationship between electricity demand and temperature at different time41 Figure 4-3 Electricity consumption, TWh, to Figure 4-4 Intensity of Australian energy consumption Figure 4-5 Shares of energy consumption and economic output Figure 4-6 National Ownership of Air Conditioners by State Figure 5-1 Unitised power curve for generic wind generator Figure 5-2 NEM s daily average non-scheduled solar PV generation for Figure 5-3 NEM s daily average non-scheduled wind generation (SGU) Figure 5-4 NEM s daily average net demand for Figure 5-5 NEM's daily average gross demand for Figure 5-6 Comparing daily average gross and net demand for 2007 & Figure 5-7 Distribution by time of day of the maximum peak loads from 2007 to 2011 at each node in the NEM Figure 5-8 Distribution by year of the maximum peak loads from 2007 to 2011 at each node in the NEM Figure 5-9 Comparing normalised direct solar intensity to the highest net peak demand day in at 5 nodes in the NEM Figure 5-10 Diffusion of innovation Figure 5-11 PRMSE versus percentage of total demand in for each node Figure 6-1 Life-cycle SO 2 and NO x emissions of power-generating technologies Figure 6-2 Average daily solar exposure - Annual Figure 6-3 Summer load shaving profile Figure 6-4 Mean wind speed in m/s at 80m above ground level Figure 6-5 Average Sport Price in South Australia per MWh Figure 6-6 Interconnectors on the NEM Figure 6-7 NEM s main hub targeted by political lobbying and conflict of interest Figure 6-8 NEM s topology under NEMLink Figure 6-9 MUREI s life-cycle CO 2 emissions of power generating technologies Figure 6-10 IEA s life-cycle CO 2 emission of power-generating technologies Figure 6-11 Meeting demand with and without baseload Figure 8-1 Linkages between water and electricity industries Figure 8-2 Overall methodological framework Figure 8-3 Comparison between actual and estimated annual electricity demand for NEM Figure 8-4 Comparison between actual and estimated intraday electricity demand viii Analysis of institutional adaptability

13 Figure 8-5 Existing generation capacities and interstate transmissions capabilities considered in this study Figure 8-6 Stylised Reference Energy System (for a typical state; NSW) used in this study Figure 8-7 Temporal resolution for the analysis in TIMES Figure 8-8 Comparison between actual and estimates of water volume in NEM storages Figure 8-9 Scenarios included in this study Figure 8-10 Impact of changes in temperature on load duration curves for NEM states Figure 8-11 Differences in monthly maximum demand between the two climate change scenarios Figure 8-12 Electricity generation profile under the two climate scenarios Figure 8-13 Changes in electricity generation capacity under the two climate scenarios Figure 8-14 Carbon emissions under the two climate scenarios Figure 8-15 Carbon intensity under the two climate scenarios Figure 8-16 Electricity generation mix by fuel type Figure 8-17 Changes in electricity generation capacity under alternative institutional paradigm Figure 8-18 Carbon emissions under the three institutional scenarios Figure 10-1 Ownership patterns in the NEM by indicative market share Figure 10-2 Shifting from baseload coal and intermediate or peaking gas to dispatchable and variable renewables Figure A-1 Australian Climate Futures Grids Figure B-1 Interconnectors on the NEM Figure B-2 Stylised topology of QLD transmission lines and LSE Figure B-3 Stylised topology of NSW transmission lines and LSE Figure B-4 Stylised topology of VIC transmission lines and LSE Figure B-5 Stylised topology of SA transmission lines and LSE Figure B-6 Stylised topology of TAS transmission lines and LSE Figure E-1 Average spot price levels by state for to for $0/tC Figure E-2 Average nodal price levels of Victorian nodes 28, 33, 34 and 35 for to for $0/tC Figure E-3 Annual spot price volatility for to for $0/tC Figure E-4 Average spot price levels by state for to for $23/tC Figure E-5 Annual spot price volatility by state for to for $23/tC Figure F-1 Production intensity rate by state for to for $0/tC0 2 : all generation Figure F-2 Amended production intensity rate by state for to for $0/tC0 2 : all generation Figure F-3 Production intensity rate by state for to for $0/tC0 2 : coal generation Figure F-4 Amended production intensity rate by state for to for $0/tC0 2 : coal generation Figure F-5 Production intensity rate by state for to for $0/tC02: gas generation Analysis of institutional adaptability ix

14 Tables Table 2-1 The four Special Report on Emissions Scenario families Table 2-2 The six SRESs & projected global average surface warming from 1990 to Table 2-3 Comparing environment variables used in climate change studies Table 2-4 Fire danger rating Table 3-1 Seasonal change in wind speed (m/s) from 1990 to 2035 for the GCM CSIRO-Mk3.5 and emission scenario A1FI Table 4-1 Effect of temperature change on peak demand for electricity in four capital cities Table 4-2 Projected increase in peak demand for a one degree increase in temperature Table 4-3 Comparing base temperature in degrees Celsius for cities and states Table 4-4 Population projection assumptions and increase from 2006 to Table 4-5 Uneven projected population growth from 2006 to 2030 across the NEM Table 4-6 Uneven projected household growth from 2006 to 2030 across the NEM Table 4-7 Projected household growth above population growth from 2006 to Table 5-1 Matching the NEM nodes and weather stations that provide half hourly solar data Table 5-2 Errors in fitting the models for each node for the baseline weather year Table 5-3 Per cent change in demand and total cost from 2009 to 2030 by state Table 5-4 Per cent change in demand and total cost from 2009 to 2030 by demand centre Table 5-5 Sensitivity analysis of population and climate change futures Table 6-1 Renewable energy target legislated by the Australian Government Table 6-2 Correlation of wind and demand Table 6-3 South Australian wholesale prices Table 8-1 Electricity consumption by various water sources Table 8-2 Physical characteristics of thermal power stations Table 8-3 Select summary statistics of the annual electricity demand models Table 8-4 Adjusted-R 2 for hourly demand models for NEM states Table 8-5 Select summary statistics of the water model Table 8-6 Scenario assumptions, x Analysis of institutional adaptability

15 Table 8-7 Annual and peak electricity demand in Table 8-8 Electricity generation in NEM under the two climate scenarios Table 8-9 Scenarios descriptions for electricity supply modelling Table 8-10 Percentage share of ownership in the electricity generation capacities Table 9-1 International Corruption Perception Index for Table 9-2 South Korea's Smart Grid Roadmap Table 9-3 Size of the South Korean transmission system Table 9-4 Size of the South Korean distribution system Table 9-5 Distribution and transmission companies operating in the NEM Table 9-6 International fragmentation comparison - raw data Table 9-7 International fragmentation comparison per political entity Table A-1 Selecting global climate models for this project Table C-1 Minimum stable operating capacity limits for coal plant, assumed operating time and start-up cost status Table C-2 Minimum stable operating capacity limits for baseload and intermediate gas plant, assumed operating time and start-up cost status Table E-1 Annual capacity factors for Victorian hydro generation plant and Mortlake power station Table E-2 Average spot price levels and percentage growth by state relative to ($0/tC0 2 ) outcomes Table E average spot price levels and percentage change by state following introduction of a carbon price of $23/tC Table E-4 Percentage change in wholesale price from ($0/tC0 2 ) levels for to Table E-5 Carbon pass-through outcomes: to Table F-1 Production intensity rate outcomes by state for the period to : OCGT generation Table F-2 Production intensity rate outcomes by state for the period to : hydro generation Table F-3 ($23/tC0 2 ) and ($0/tC0 2 ) production intensity rates outcomes by state and fuel type for the benchmark year Table F-4 Percentage change between the ($23/tC0 2 ) and ($0/tC0 2 ) production intensity rate outcomes by state for the period to : all generation Table F-5 Percentage change between the ($23/tC0 2 ) and ($0/tC0 2 ) production intensity rate outcomes by state for the period to : coal generation Analysis of institutional adaptability xi

16 Table F-6 Percentage change between the ($23/tC0 2 ) and ($0/tC0 2 ) production intensity rate outcomes by state for the period to : gas generation Table F-7 Percentage change between the ($23/tC0 2 ) and ($0/tC0 2 ) production intensity rates outcomes by state for the period to : hydro generation Table G-1 Percentage change in carbon emissions by state from levels for the period to Table G-2 ($23/tC0 2 ) and ($0/tC0 2 ) carbon emission outcomes by state and fuel type for the benchmark year Table G-3 Percentage change between the ($23/tC0 2 ) and ($0/tC0 2 ) carbon emissions outcomes by state and for all sources of generation for the period to Table H-1 Percentage change in transmission branch utilisation rates relative to for the period to Table H-2 Proportion of time transmission branches are congested over the period to Table H-3 Percentage change between the ($23/tC0 2 ) and ($0/tC0 2 ) transmission branch utilisation rate outcomes for the period to Table H-4 Percentage change in transmission branch utilisation rates relative to for the period to for a carbon price of $23/tC0 2 : additional transmission lines Table H-5 Percentage change between the ($23/tC0 2 ) and ($0/tC0 2 ) branch congestion outcomes for the period to xii Analysis of institutional adaptability

17 Abbreviations A1B A1FI A1T AAP ABC ABS AC ACCC AEMC AEMO AER ANEM APVA ARENA ASEFS AWEFS B1 BAU BoM BTEX CAES CCGT CCL CCS CDD CEC CER CEO CFL CHP CIA CMIP CoAG CPRS CSG Balanced energy sources rapid economic growth SRES Fossil Intensive rapid economic growth SRES Non-fossil energy sources Australian Associated Press Australian Broadcasting Corporation Australian Bureau of Statistics Alternating Current Australian Competition and Consumer Commission Australian Energy Market Commission Australian Energy Market Operator Australian Energy Regulator Australian National Electricity Market Australian Photo Voltaic Association Australian Renewable Energy Agency Australian Solar Energy Forecasting System Australian Wind Energy Forecasting System Sustainable energy sources rapid economic growth Business-As-Usual Bureau of Metrology Benzene, Toluene, Ethyl-benzene and Xylene Compressed Air Energy Storage Combined Cycle Gas Turbine Climate Change LEvy Carbon Capture and Storage Cooling Degree Days Californian Energy Commission Certified Emissions Reduction Chief Executive Officer Compact Fluorescent Lights Combined heat and power Central Intelligence Agency Coupled Model Intercomparison Project Council of Australian Governments Carbon Pollution Reduction Scheme Coal Seam Gas Analysis of institutional adaptability xiii

18 CSIRO CSIRO-Mk3.5 CST DC DC OPF DSM DRET E3 EEG EV Enel EPA EPRI ESCO ETS EUAA FACTS FFDI GCM GDP GFC GHG GIS GL GSP HDD HTS HVDC IEA IGCC INL IPCC KEPCO KSGI kv LMP Commonwealth Scientific and Industrial Research Organisation GCM from the CSIRO used for the worst case (hottest) in this project Concentrated Solar Thermal Direct Current Direct Current Optimal Power Flow Demand Side Management Department of Resources, Energy and Tourism Equipment Energy Efficiency Erneuerbare-Energien-Gesetz (Germany s Renewable Energy Sources Act) Electrical Vehicle Ente Nazionale per l'energia elettrica Environment Protection Agency Energy Power Research Institute Energy Services Companies Emissions Trading Scheme Energy Users Association of Australia Flexible AC transmission systems Forest Fire Danger Index Global Climate Model Gross Domestic Product Global Financial Crisis Greenhouse Gas Geographic Information System Gigalitre Gross State Product Heating Degree Days High Temperature Superconductor High Voltage Direct Current International Energy Association Integrated Gasification Combined Cycle Idaho National Laboratory Intergovernmental Panel on Climate Change Korean Electric Power Corporation Korea Smart Grid Institute Kilovolts Locational Marginal Pricing xiv Analysis of institutional adaptability

19 LP Linear Programming LSE Load Serving Entity LTS Low Temperature Superconductor MCE Ministerial Council on Energy MEPS Minimum Energy Performance Standards MESSAGE Model for Energy Supply Strategy Alternatives and their General Environmental impact MRI Meteorological Research Institute (Japan) MRI-CGCM2.3.2 GCM from the MRI used for the most likely case in this project MIROC3.2 GCM used for the best case (coolest) in this project MRRT Mineral Resource Rent Tax NSP Network Service Provider(s) MUERI Melbourne University Energy Research Institute MVA Megavoltamperes MW Megawatt NBN National Broadband Network NCCARF National Climate Change Adaption Research Foundation NEM National Electricity Market NEMLink A proposal to enable large-scale inter-regional power transfers NEMMCO National Electricity Market Management Company NFEE National Framework for Energy Efficiency NGCC Natural Gas Combined Cycle NGCP National Grid Corporation of the Philippines NGF National Generators Forum NPV Net Present Value NSW New South Wales NT Northern Territory NWC National Water Commission NWI National Water Initiative OCGT Open Cycle Gas Turbine OECD Organisation for Economic Co-operation and Development PPP Purchasing Power Parity PRMSE Percentage of RMSE Prosumer Producer and Consumer PU Per unit PV Photo Voltaic R&D Research & Development Analysis of institutional adaptability xv

20 REN21 Renewable Energy Policy Network of the 21 st century RET Renewable Energy Targets RIT-T Regulatory Investment Tests for Transmission RMSE Square root of the mean of the square of the error RPA Renewable Portfolio Agreement SA Southern Australia SA2 Statistical Areas Level 2 SCQP Strictly Convex Quadratic Programming SEQ South East Queensland Series A Higher growth ABS (2008) population projection Series B Most likely ABS (2008) population projection Series C Lower growth ABS (2008) population projection Series I Lower growth ABS (2010) number of households projection Series II Most likely ABS (2010) number of households projection Series III Higher growth ABS (2010) number of households projection SGA Smart Grid Australia SGU Small Generation Unit SI Standard International SOE State Owned Enterprise SRES Special Report on Emission Scenarios STC Standard Testing Conditions SVC Static var compensators QLD Queensland QNI QLD-NSW interconnector TAS Tasmania TI Transparency International TNSP Transmission Network Service Provider(s) TOU Time of Use TOS Time of Supply UK United Kingdom US United States VIC Victoria VO&M Variable Operation & Maintenance VTT Valtion Teknillinen Tutkimuskeskus WA Western Australia WCRP World Climate Research Program WEC World Energy Council xvi Analysis of institutional adaptability

21 Acknowledgements We thank Professor John Clarke and Dr Leanne Webb of the Tailored Project Services of the CSIRO Division of Marine and Atmospheric Research for the global climate projections developed specifically for the National Electricity Market (NEM) region and for constructive feedback on this book. We thank Warwick Johnston of Sunwiz for his advice regarding solar PV. We thank Lynette Molyneaux of UQ for numerous engaging discussions during the project, which helped crystallise many ideas expressed in this book. We thank two anonymous reviewers for their profuse and constructive feedback during the development of this book. We thank UniQuest for the coordination of the project amongst NCCARF, The University of Queensland (UQ) and the University of Technology, Sydney (UTS). We thank the modelling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the World Climate Research Program s (WCRP) Working Group on Coupled Modelling for their roles in making available the WCRP CMIP3 (Coupled Model Inter-comparison Project) multi-model dataset. Support of this dataset is provided by the Office of Science, US Government Department of Energy. Analysis of institutional adaptability xvii

22 xviii Analysis of institutional adaptability

23 Preface The project that culminated in this book came about as part of the Federal Government s recognition of the need for adaptation by human systems to address the physical changes induced by climate change. The Federal Government, through the Department of Climate Change and Energy Efficiency and the National Climate Change Adaptation Research Facility (NCCARF), funded this project. There is a growing concern about the readiness of infrastructures in Australia both in adapting to and mitigating the effects of climate change. The electricity industry is vulnerable to the physical effects of climate change, including altered water availability on a seasonal or annual basis, changes to the incidence of extreme weather conditions such as storms, and changed average temperatures. This industry sector is also affected by policies directed to reducing its contribution to the chemical drivers of anthropogenic climate change (greenhouse gases or GHGs). For instance, the carbon intensive energy generation fleet is Australia s largest manmade cause of climate change. So, the electricity industry is faced with a significant challenge: to increase its resilience to climate change impacts while ceasing to be a major source of GHGs that contribute to climate change. This challenge requires consideration of (a) how greater climate resilience can be achieved while (b) transforming the generation portfolio from mostly fossil fuels to renewable energy sources or by employing cost effective carbon capturing technologies to offset the GHG emissions, created in the sector, until longerterm scalable practices are found. There has been a small, but gradual, improvement in the diversity of the generation portfolio with the increased penetration of solar PV and onshore wind generation. This book provides many recommendations to ease the transformation of the electricity industry to one with greater climate resilience and a low carbon future. These recommendations entail significant structural changes. Indeed, structural change has been going on in the electricity sector for some time with impacts on those working in the sector. However, these changes for the most part are due to the perceived costeffective advantages of privatised utilities over publically operated utilities rather than adaptation to climate change. The National Electricity Market (NEM) has undergone major restructuring over the last 20 years with the vertical separation of state monopolies into separate retail, distribution, transmission and generation components, as a prelude to deregulation and privatisation of these assets. This drive to privatise utilities has been an international phenomenon since the 1980s. However, the assumption that utility privatisation always delivers the best outcomes can be called into question from a number of directions: increasing inequity; inherent conflict between the profit maximising objectives of firms and climate change policy; and utility privatisations need not benefit the residential consumers. Climate change increases the number of heat stress days, which increases financial or physical stress for lower income earners via increased electricity demand for air Analysis of institutional adaptability 1

24 conditioning or non-use of air-conditioners, respectively. Additionally, there is the conflict of water usage during time of drought. Compounding these climate change induced stressors for low income earners, there is the looming privatisation of the electricity sector in Australia. The United States (US) has been the leading proponent of deregulation and privatisation. Yet it has experienced a large increase in income inequity (Weinberg 1996) to such an extent that there has been a 4% decline in the real mean incomes received by the lowest quintile of families from 1970 to 2011 (US Census Bureau 2013). Privatising the remainder of the electricity sector in Australia will move Australia closer to the socioeconomic structure of the US (Alvaredo et al. 2013). Privatisation of utilities has only provided, at best, modest gains for the residential consumer. However, within the industry there has been a major transfer of wealth from employees to management. The result in the US has been to exacerbate the hardship of low income earners who are more susceptible to stresses induced by climate change. Seen from a wider economic and social perspective, privatisation of utilities per se has not been a success. In addition, there is the inherent conflict between profit maximisation by companies and climate change policy. Placing a price on carbon has gone some way to address this conflict but the shift from a fixed carbon price aka carbon tax to a flexible carbon price aka emissions trading scheme (ETS), is detrimental to adaptation to climate change because the shift to an ETS introduces a new source of uncertainty. This ETS induced uncertainty amplifies the risk in making investment decisions for new generation plant hence delaying investment decisions, so stalling adaptation to climate change. The ETS also makes government revenue more uncertain, which curtails the government s ability to support innovation and commercialisation policies to foster adaptation to climate change. There are additional adjustments required to be made to price signals to enable demand side management (DSM) such as the introduction of time of use (TOU) billing and time of supply (TOS) payments for non-scheduled generators. TOU and TOS payments together provide appropriate price signals for the diffusion of energy storage technologies such as batteries into the NEM. The deployment of energy storage addresses two issues: intermittency and non-dispatchability, both associated with renewable energy such as solar PV and wind generation. Addressing these two issues allow greater cuts in fossil fuel generator GHG emissions to mitigate climate change. The eventual deployment of electric vehicles (EVs) with their large battery storage, could aid DSM if the appropriate TOU and TOS price signals are in place. Without these price signals, EVs will exacerbate the existing peak demand problem in the NEM. There is a further inherent conflict between profit maximising network service providers (NSP) and climate change policy, in the way profits are calculated as rate of return on capital expenditure. This calculation is at odds with DSM and is discussed further in this book. The Global Financial Crisis (GFC) has put to rest the concept that private ownership of utilities provides innately superior outcomes to government ownership with the US government effectively nationalising major parts of its economy to prevent economic collapse (Quiggin 2010). A more circumspect approach is to decide which parts of the 2 Analysis of institutional adaptability

25 economy should operate within the private or public sectors and this tends to change over time. So, the simplistic view that privatising the entire economy will take Australia to some economic optimum state is contrary to the evidence. In Victorian Britain, the private sector dominated in all aspects of production with limited regulation. The result was poor working conditions for the majority of the population and many negative externalities imposed upon the natural environment and social conditions. By the early 20 th century, the government had introduced regulatory structures to improve this situation that would eventually result in the mixed economy striking a balance between public and private ownership, which is the norm in advanced countries at present. We argue that this kind of regulatory maturity is now required in both the electricity and energy sector more widely. The approach in this book is to apply evidence based policy rather than policy based evidence. The latter approach relies on assuming the correctness of ideas or theories and finding evidence to support them. This approach has its appeal, of course, since reality is messy and difficult to interpret and there is always the issue of data accuracy and availability to test ideas or theories. From an historical perspective, the legacy of federation of Australia was to have a national regulatory and monopoly telecommunications system but separate state regulatory and state monopoly electrical systems. At the time of Federation, this decision seemed appropriate as the state based electricity systems were isolated islands. Of course, this is no longer the case. In contrast, South Korea has had a national monopoly transmission and distribution system since its occupation by the Japanese who saw the advantages in reduced coordination costs from amalgamating the NSPs. And, of course, they had the power to enforce an amalgamation. The South Korean national monopoly transmission and distribution company now serves 50 million people. In contrast, Australia has more than 15 distributions and transmission companies which serve less than 23 million people. The tumultuous history of Korea has resulted in an exceedingly simple socioeconomic structure that has allowed it to develop the most reliable electricity system in the world, even with few natural resources available domestically. In contrast, Australia is resources rich, which allows Australia to sustain an unnecessary and inefficient duplication of regulatory regimes and excessive coordination overheads adding to GHG emissions and so detrimentally contributing to accelerated climate change. Additionally, the relatively tranquil political history of Australia has provided little motivation for rationalising the national transmission and distribution systems. However, climate change impacts and mitigation issues and the political backlash over the recent rapid increase in electricity prices, mainly stemming from NSPs, may provide the catalyst for significant restructuring of these systems. In this book, we explore the stresses that are building up in the national energy system and in its core, the NEM, and offer a greater understanding of the options that are available to correct this deteriorating situation to better adapt to climate change. Professor John Foster The University of Queensland Analysis of institutional adaptability 3

26 A non-technical summary for policy makers John Foster and William Paul Bell, The University of Queensland This non-technical summary presents the findings and recommendations from the project called Analysis of institutional adaptability to redress electricity infrastructure vulnerability due to climate change. The objectives of the project are to examine the adaptive capacity of existing institutional arrangements in the National Electricity Market (NEM) to existing and predicted climate change conditions. Specifically the project: identifies climate change adaptation issues in the NEM; analyses climate change impacts on reliability in the NEM under alternative climate change scenarios to 2030, particularly what adaptation strategies the power generation and supply network infrastructure will need; and assesses the robustness of the institutional arrangements that supports effective adaptation. The project finds that four factors are hindering or required for adaptation to climate change: 1. fragmentation of the NEM, both politically and economically; 2. accelerated deterioration of the transmission and distribution infrastructure due to climate change requiring the deployment of technology to defer investment in transmission and distribution; 3. lacking mechanisms to develop a diversified portfolio of generation technology and energy sources to reduce supply risk; and 4. failure to model and treat the NEM as a national node based entity rather than state based. The project s findings are primarily to address climate change issues but if these four factors are addressed, the resilience of the NEM is improved to handle other adverse contingences. For instance, the two factors driving the largest increases in electricity prices are investment in transmission and distribution and fossil fuel prices. Peak demand drives the investment in transmission and distribution but peak demand is only for a relatively short period. Exacerbating this effect is increasing underutilisation of transmission and distribution driven by both solar photo voltaic (PV) uptake and climate change. Using demand side management (DSM) to shift demand to outside peak periods provides one method to defer investment in transmission and distribution. Recommendation 2 addresses investment deferment. The commodity boom has increased both price and price volatility of fossil fuels where the lack of diversity in generation makes electricity prices very sensitive to fossil fuel prices and disruptions in supply. A diversified portfolio of generation would ameliorate the price sensitivity and supply disruptions. Furthermore, long term electricity price rises are likely to ensue as the fossil fuels become depleted. A diversified portfolio of generation would also ready the NEM for this contingency. Recommendation 3 addresses diversified portfolios. This project makes four inter-related recommendations to address the four factors listed above. Chapter 10 discusses the justification for these recommendations in more detail. 4 Analysis of institutional adaptability

27 Recommendations to address four mal-adaptations to climate change 1 Institutional fragmentation, both economically and politically The research in Chapter 9, using an international comparison, found major political and economic fragmentation in the NEM hindering adaptation of climate change. Therefore, it is recommended that the transmission and distribution lines of the NEM be placed in one company and the State Governments in the NEM cede legislative power over all electrical matters to the Federal Government. This would assist climate change adaptation by easing the deployment of renewable generation to mitigate GHG emissions and contain costs, as discussed further in Chapter 10. This could be achieved by the Federal Government retaining a controlling interest in the lines monopoly company and managing the electricity market with the existing Australian Energy Market Commission (AEMC), Australian Energy Market Operator (AEMO) and Australian Energy Regulator (AER). The same lines monopoly company own and manage the gas pipe line infrastructure to coordinate the use of the two energy sources via power-to-gas and tri-generation. 2 Distorted transmission and distribution investment deferment mechanisms The research in Chapters 6 and 9 finds both the rapid rise in electricity prices over the last few years, mainly induced by NSPs building more infrastructures and the lack of progress in the NEM with implementing demand side management (DSM), need addressing. It is recommended that mechanisms to defer investment require both demand side management (DSM) and alignment of the business objectives, of the network service providers (NSP), with DSM. This would assist climate change adaptation directly by moderating the demand in electricity and the ensuing GHGs and indirectly by deferring investment in further distribution and transmission infrastructure. This could be achieved by DSM having both educational and incentive aspects. Incentives include price signals such as time of use (TOU) billing and time of supply (TOS) payments for non-scheduled generators. TOU and TOS payments together provide appropriate price signals for the diffusion of energy storage technologies such as batteries into the NEM. TOU and TOS require a national smart meter rollout with inhouse display and devices to automatically switch off air conditioners during critical peak periods if the customer wishes to save on critical peak pricing; thus, reducing GHG emissions and slowing the rate of climate change. A single monopoly NSP reduces coordination costs and enables monopoly buying power for smart meters. Addressing poverty will aid acceptance of smart meters. Addressing energy poverty requires policies to target the misaligned benefits in the landlord-tenant relationship, emanating from energy efficiency equipment, solar PV or tri-generation. Policies include subsidising loans to encourage landlords to install such equipment, splitting the benefit of the equipment and introducing loss of capital tax free gains for non-compliant landlords. The current remuneration for NSP is based on capital expenditure, so encourages the building of more network infrastructures which is at odds with DSM. To address this problem, it is recommended to include a business objective for the NSP to increase utilisation of exiting network infrastructure. Multiple business objectives are more easily handled by government owned enterprises. Analysis of institutional adaptability 5

28 3 Lacking mechanisms to develop a diversified energy portfolio From our research and from international experiences, the current practices and structures in Australia provide little incentive for transforming energy generation from fossil fuels to renewables. It is recommended that the government change policy to introduce renewable energy targets for specific generation technologies as they become ready for commercialisation with designated timeframes. In conjunction, the use of feed-in tariff reverse auctions to cost effectively diversify the energy portfolio is recommended. By nationalising the retail sector, conflict of interest in dual retailgenerator companies will be removed and the risk in forming power purchase agreements will be minimised. It is also recommended to streamline the grid connection process for distributed energy generators. These changes would assist climate change adaptation in the sector by cost effectively introducing renewable energy. Chapter 10 discusses these changes in more detail. 4 Failure to model and to treat the NEM as a national node based entity rather than state based Our research found a requirement to improve electricity demand forecasts. To address this requirement, AEMO should produce node based half hourly data for scheduled and non-scheduled generation by node and provide Geographic Information System (GIS) files of the distribution areas. This would assist climate change adaptation as it would improve the ability to plan and make more climate resilient investments. There is variation in each node s expected population growth, climate change, weather and demand and supply response to changes in environment. Failing to acknowledge these differences could misinform policy. Introducing node based price signals would promote more appropriate investment decisions required in Recommendation 2. Recommendation 1 would help transform the NEM s focus from state to a national node basis and thus enable more coordinated climate change adaptation by maximising the use of the renewable resources across the NEM. 6 Analysis of institutional adaptability