# Energy, the economy and the future: Growth, forecasts and the future Source page: https://www.materialinsights.org/learn/energy/energy-economy-society/p4/ [Understanding Energy](https://www.materialinsights.org/learn/energy/) / [Module 14: Energy, the economy and the future](https://www.materialinsights.org/learn/energy/energy-economy-society/) Part 4 of 4 ## Growth, forecasts and the future Investors and planners live on projections. Smil offers two tools for judging them: an understanding of how real systems grow, which is almost never exponentially for long, and a long record of energy forecasts that went wrong. Together they suggest how to use scenarios without being fooled by them. ### 4.1 Real growth follows S-curves, not endless exponentials Smil's book Growth starts with the mathematics of how things grow. Linear growth adds the same amount each period: a farm adding 100 tonnes of grain a year. Exponential growth adds the same percentage, so the amount added keeps rising: savings earning 7% a year. A handy rule gives the doubling time of exponential growth: divide 70 by the annual percentage rate. At 7% a year a quantity doubles in about ten years; at 2%, in about 35. Exponential growth cannot last in any finite system. Sooner or later it runs into limits of resources, space, markets or energy. So most real growth is S-shaped. It starts slowly, speeds up, then slows and levels off near a ceiling. The logistic curve, first described by the Belgian mathematician Pierre-François Verhulst in the 1830s, is the classic form, and related curves describe similar paths. Smil finds the pattern everywhere: in the growth of organisms, the size of machines, the spread of new technologies, and the output of energy sources and industries. The S-curve has two lessons for energy. The first is Smil's: if every energy conversion follows a logistic path, the shift from fossil fuels will not be exceptionally fast overall, because each new technology must pass through slow early and late phases. The second cuts the other way. In the steep middle of an S-curve, growth looks impossibly fast to anyone used to linear thinking, and forecasters who draw straight lines are repeatedly surprised. Solar power in the 2020s is in that steep phase. The skill is to ask where on its curve a technology sits, and what sets its ceiling. For solar the ceiling is not the sun but the grid's ability to absorb midday power, storage, land and the share of energy use that can be electrified. For an Indian electricity market growing 6% or more a year, demand itself doubles in about 12 years, which raises the ceiling for every source. Data Three ways to grow | Pattern | What is constant | Example | Long-run fate | |---|---|---|---| | Linear | the amount added each period | a fixed 100 t more grain each year | can continue but becomes a shrinking percentage | | Exponential | the percentage added each period | 7% a year doubles in about 10 years | always ends in a finite system | | Logistic (S-curve) | nothing: slow, fast, then slow | spread of a new technology | levels off near a ceiling set by limits | Source: Smil, Growth: From Microorganisms to Megacities (2019), via Smil Mastery Course, M15 'Growth trajectories: linear, exponential, logistic' Worked example #### Solar and the rule of 70 Ember reports world solar generation of 2,778 TWh in 2025, up 30% in a year. At 30% a year the rule of 70 gives a doubling time of a little over two years. If that rate held for ten more years, solar would grow almost fourteenfold to about 38,000 TWh, more than the whole world's electricity generation in 2025, about 31,700 TWh. That cannot happen while solar remains a midday source, so the growth rate must fall. The question is not whether solar's curve bends, but at what share of electricity it bends and how much storage moves that point. - Smil, Growth: From Microorganisms to Megacities (2019) · via Smil Mastery Course, M15 'Growth trajectories: linear, exponential, logistic' - Ember, Global Electricity Review 2026 (April 2026) · 2025 data, https://ember-energy.org/latest-insights/global-electricity-review-2026/ and https://ember-energy.org/chapter/2025-in-review/ ### 4.2 Long-range energy forecasts have a poor record Smil's Energy at the Crossroads has a whole chapter titled 'Against Forecasting'. He reviews decades of long-range energy projections and finds that most missed badly, whatever the authority of their authors. In the 1950s and 1960s leading scientists foresaw a world powered by cheap nuclear electricity, with fast breeder reactors taking over by the end of the century. A celebrated 1976 forecast of 'soft energy' for the United States missed its target for 2000 by around 90%. Oil prices were expected to keep rising after 1980 and instead collapsed. Even population projections, among the most reliable of all, shift: the UN's 1991 projection for 2025 was cut by about 600 million people in its 2004 revision. The main reason forecasts fail is that they are unrealistically static. They extend current trends, but trends weaken, deepen or reverse, sometimes abruptly, when prices, technologies, politics or wars change. Single numbers make the problem worse: a forecast of so many gigawatts in 2050 hides huge uncertainty behind false precision. The errors are not all in one direction. Through the 2000s and 2010s, many official projections, including the IEA's, badly underestimated the growth of solar power, because they assumed cost declines would slow and policies would stay modest. The IEA itself now shows how much its baseline has moved. Its 2025 Current Policies Scenario, which assumes no new policies at all, still has cumulative solar and wind generation to 2040 almost four times what its 2015 current policies case projected, and coal supply about 23% lower. The world changed faster in solar than the forecasters assumed, and more slowly in oil than many advocates hoped. This record does not mean projections are useless. It means they should be read as conditional stories rather than predictions, and judged by how well they expose the assumptions that matter. Data Some famous energy forecasting misses | Forecast | Made | What happened | |---|---|---| | Nuclear power will be very cheap and breeder reactors will dominate by 2000 | 1950s to 1960s | costly reactors, breeders abandoned commercially | | Soft energy will supply a large share of US energy by 2000 | 1976 | missed by around 90% | | Oil prices will keep rising after 1980 | around 1980 | prices collapsed in the mid-1980s | | UN projection of world population in 2025 | 1991 | cut by about 600 million in 2004 | | Solar will remain a small, expensive niche | 2000s to 2010s | solar overtook wind in 2025 and keeps growing about 30% a year | Source: Smil, Energy at the Crossroads: Global Perspectives and Uncertainties (2003), via Smil Mastery Course, M16 'Against forecasting' Case #### How the IEA's own baseline moved in a decade An analysis of the World Energy Outlook 2025 by ACCR compared its Current Policies Scenario with the equivalent cases from 2015 and 2019. Cumulative solar and wind generation to 2040 is now 297% higher than in the 2015 version and 112% higher than in 2019. Cumulative coal supply to 2040 is 23% lower than in 2015, and total fossil supply 11% lower. Nothing in the 2025 case is new policy; the change comes from technology costs and policies that were adopted after 2015 and are now in force. A ten-year-old baseline would have badly misled an investor. - Smil, Energy at the Crossroads: Global Perspectives and Uncertainties (2003) · via Smil Mastery Course, M16 'Against forecasting' - Smil, Energy Myths and Realities: Bringing Science to the Energy Policy Debate (2010) · via Smil Mastery Course, M16 'Against forecasting' - Smil, Global Catastrophes and Trends: The Next Fifty Years (2008) · via Smil Mastery Course, M16 'Against forecasting' - ACCR, Investor bulletin: IEA World Energy Outlook 2025 (13 November 2025) · comparison of WEO 2025 scenarios with the 2015 and 2019 editions, storage capacity by scenario, https://www.accr.org.au/downloads/13112025-investor-bulletin-weo-2025.pdf ### 4.3 Use scenarios to map constraints and choices, not to predict Smil's own practice is to avoid point forecasts. Instead he sets out the constraints that bound what is realistically possible: the physics of energy conversion, the scale of the existing system, the lifetimes of its assets, the materials required and the costs involved. Within those bounds he is willing to argue for normative goals, what we ought to aim for, while refusing to pretend he knows the date and size of the outcome. For an investor this suggests a practical method. First, use several scenarios rather than one, and look for investments that make sense in most of them. Grid expansion, energy efficiency, storage, efficient cooling and clean industrial heat look sound in almost every IEA case. In its 2025 Outlook, battery storage grows from about 77 GW today to about 1,400 GW by 2035 even in the Current Policies case, about 1,700 GW in the Stated Policies case and about 2,900 GW in the net-zero case. An eighteen-fold rise in the most conservative case is a strong signal. Second, identify the signposts that tell you which path the world is on. For India these include the share of electric two-wheelers and cars in sales, the start and price of the carbon market, the pace of grid and storage tenders, coal plant running hours and the growth rate of electricity demand. Third, translate every claim into physical quantities and check them against history. How many gigawatts a year, how many tonnes, how many kilometres of line? If an investment depends on a build rate many times anything seen before, it needs a very good reason. Fourth, respect discontinuities. Wars, pandemics, price shocks and sudden policy shifts have changed energy paths more than steady trends have. They cannot be predicted, but portfolios can be built to survive them. That combination of humility about prediction and rigour about constraints is the most useful thing Smil's work offers anyone who has to commit capital to the energy future. Value chain Questions to ask of any energy projection - **Is this projection useful?** - **Scale** - **How big is the thing today in absolute terms?** - **What share of the relevant market is that?** - **Pace** - **Where is it on its S-curve?** - **Is the implied build rate unprecedented?** - **Constraints** - **Materials, land, grids, skills** - **Lifetimes of the assets it must replace** - **Assumptions** - **Demand growth, costs, policy** - **What if each is wrong by half?** - **Robustness** - **Does the investment work across scenarios?** - **Can it survive a shock?** Source: Smil, Energy at the Crossroads: Global Perspectives and Uncertainties (2003), via Smil Mastery Course, M16 'Against forecasting' Common misreading #### A precise number is not a confident number A projection that India will have exactly so many gigawatts of solar in 2040 sounds authoritative, but the precision comes from the model, not from knowledge of the future. Smil's review shows that ranges and scenarios are more honest than single values, and that the most useful part of any outlook is its stated assumptions. When reading a forecast, look first for what it assumes about demand growth, costs and policy, then ask what happens to its conclusions if each assumption is wrong by half. - Smil, Energy at the Crossroads: Global Perspectives and Uncertainties (2003) · via Smil Mastery Course, M16 'Against forecasting' - Smil, Global Catastrophes and Trends: The Next Fifty Years (2008) · via Smil Mastery Course, M16 'Fatal discontinuities' - ACCR, Investor bulletin: IEA World Energy Outlook 2025 (13 November 2025) · comparison of WEO 2025 scenarios with the 2015 and 2019 editions, storage capacity by scenario, https://www.accr.org.au/downloads/13112025-investor-bulletin-weo-2025.pdf - IEA, World Energy Outlook 2025 (2025) · Overview and key findings, https://www.iea.org/reports/world-energy-outlook-2025/overview-and-key-findings ### Check your understanding Using the rule of 70, roughly how long does a quantity growing at 7% a year take to double? 70 divided by 7 is 10. What does Smil see as the main reason long-range energy forecasts fail? Forecasts are unrealistically static, and single numbers hide large uncertainty. In the IEA's 2025 Outlook, battery storage capacity by 2035 ranges from about 1,400 GW to 2,900 GW across scenarios, from about 77 GW today. What is the most sensible reading for an investor? Even the most conservative case implies an eighteen-fold rise, a signal that holds across very different policy paths. [← Part 3: Energy, war and security](https://www.materialinsights.org/learn/energy/energy-economy-society/p3/)[Mark read · Wrap-up →](https://www.materialinsights.org/learn/energy/energy-economy-society/review/) ## Other sections - [Module overview](https://www.materialinsights.org/learn/energy/energy-economy-society/index.md) - [Energy and the economy](https://www.materialinsights.org/learn/energy/energy-economy-society/p1/index.md) - [Energy and human welfare](https://www.materialinsights.org/learn/energy/energy-economy-society/p2/index.md) - [Energy, war and security](https://www.materialinsights.org/learn/energy/energy-economy-society/p3/index.md) - [Key terms, quiz and sources](https://www.materialinsights.org/learn/energy/energy-economy-society/review/index.md)