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Global Futures Report 2013 - Scenarios, Models, and Variables Influencing Renewable Energy Futures

69 Annex 3 – SCENARIOS, MODELS, AND VARIABLES INFLUENCING RENEWABLE ENERGY FUTURES When experts were asked about the future of renewable energy, many replied that the future depends on policies, financing, business conditions, energy market regulation, cost reductions, social issues, and other factors that are outlined throughout this report. Far fewer replied that technology development itself was a key factor. Their views also depended on the kinds of comparisons that are being made between renewables and conventional energy technologies, including cost comparisons. (For more on cost-competitiveness with conventional energy, see “Great Debate 1” on page 12 and “Great Debates 1–3” in Annex 4.) At least 18 “key variables” emerged from interviews and scenarios, presented in the following section. Experts considered many of these variables when thinking about renewable energy futures in interviews. Scenario models incorporate many or all of these vari- ables as either (exogenous) inputs or as internal (endogenous) vari- ables. Scenario outcomes depend on how these variables are used, or what values are assumed for them if treated as inputs. Most scenarios consider variables such as economic growth (GDP), energy intensity and demand, fuel costs, carbon prices, technology costs, and degree of policy action. These variables could be consid- ered the drivers for renewable energy and other energy technolo- gies, and may be modeled based on storylines of socio-economic conditions, expectations about technological change, policy drivers, projected growth rates, or other considerations. Scenarios can be categorized as either descriptive or normative. Under descriptive studies, “forecasts” predict likely futures from current trends, using extrapolation and modeling; “exploratory sce- narios” emphasize the drivers of possible futures, without specify- ing a predetermined end state; and “technical scenarios” explore technology possibilities and configurations, emphasizing feasibility and implications of different options. Under normative studies, “visions” elaborate desirable and plausible futures, emphasizing benefits; “backcasts” start with a predeter- mined end point—a desirable (or constrained) future—and then investigate pathways and technology configurations leading there; and “roadmaps” prescribe sequences of policies and measures. The scenarios covered in this report are a mixture of these types. As noted in Box 2 on page 16, many high-renewables scenarios are backcasts based on future carbon-related constraints. Scenarios are an important tool for dealing with complexity and uncertainty about the future. They allow exploration of alternative futures and can provide insights to policymakers and the public alike. However, scenarios are not predictions. Rather, they can be seen as “if … then” queries: If policies accelerate the growth of renewables, what is the difference between situations with and without poli- cies? If renewables costs decline, how will markets shift investment patterns? If CO2 emissions should be stabilized, what combinations of technologies will achieve stabilization? These questions must be answered under sets of conditions and/or interrelationships for population, economic growth, energy demand, technology changes, technology and fuel costs, environmental emissions, and structural changes in the economy. Modeling tools are commonly used to carry out scenario analysis, with a range of software tools available. Categories of models include techno-economic, partial and general equilibrium, simula- tion, optimization, and end-use accounting. The entire economy may be modeled, or just the energy system or energy demand. The IEA World Energy Model, used for the World Energy Outlook, has been refined for two decades and comprises 16,000 equations defining interrelationships among energy, economy, technology, investment, resources, and environment. In general, the model and modeling approach have a significant impact on both data require- ments and results. Variables Influencing Renewable Energy Futures 1. Population growth and demographics. Population affects energy demand and economic output and thus energy use. The United Nations projects a global population of 9 billion by 2050. Demographic changes also affect needed infrastructure and energy services. 2. Gross domestic product (GDP) and energy intensity of GDP. Economic output affects energy demand. The energy intensity of GDP reflects the structure of the economy, in terms of energy- intensive activities vs. low-energy activities (i.e., manufacturing vs. service). 3. Energy efficiency and per-capita energy consumption. How much additional energy efficiency is possible, and how much can be achieved in practice? Some scenarios show large energy efficiency gains that reduce total energy consumption by substantial amounts, relative to a baseline case without energy efficiency gains. (See Box 2 on page 16.) 4. Renewable energy technology costs. How will costs decline over time? Many policy-intensive scenarios show continued cost reductions through 2050. Some scenarios include “learning curves” in their models, which project future cost reductions based on past history and cumulative technology production over time. (See also cost projections in Chapter 6.) 5. Policy action. There is wide recognition that policies have underpinned renewable energy development over the past decades, and that the need for policies will continue well into the future. Therefore, both the degree of policy action and the description of policies are central to scenarios. Reference scenarios typically envision low levels of policy action, while policy-driven scenarios envision full implementation of existing policies plus often stronger future policies. (See also “Great Debate 2” on page 13.)

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