Small Is Profitable: The Hidden Economic Benefits of Distributed Generation (and Other Distributed Resources) Amory B. Lovins CEO (Research), Rocky Mountain Institute, www.rmi.org [also Chairman, Hypercar Inc., www.hypercar.com] Australian EcoGeneration Conference (by PictureTel), Sydney, 13 March 2002 Copyright © 2002 Rocky Mountain Institute. All rights reserved. “Hypercar” is a trademark of RMI. Noncommercial hard-copy distribution by AEA is permitted for its and participants’ internal use. The research reported here was supported by The Shell Sustainable Energy Initiative, The Energy Foundation, and The Pew Charitable Trusts, but the authors are solely responsible for its content. © 2001 Rocky Mountain Institute, www.rmi.org Main findings Approximately 130 distinct distributed benefits can collectively increase the economic value of distributed resources by typically an order of magnitude (~101) – Details are very site- and technology-specific – But increased value too small to tilt traditional commodity-cost-based investment decisions toward distributed/green resources seems rare – Some benefits aren’t reported or linked before – Capturing many benefits depends on policy – Described here for generation resources, but also applies to storage and efficiency © 2001 Rocky Mountain Institute, www.rmi.org Objectives • Comprehensively synthesize and rigour- ously analyze distributed benefits, quantifying each wherever possible • Write the standard practitioners’ primer • Create a pedagogy across disciplinary boundaries, especially between electric- al engineering and financial economics • Embed in historical context • Offer policy recommendations • Make widely available for faster learning • Preview highlights today; solicit your suggestions for improvement © 2001 Rocky Mountain Institute, www.rmi.org Seismic shift • 19/20th Centuries model: power plants have higher cost and outage rate than the grid, so both supply and demand must be aggregated through the grid • 21st Century model: power plants have lower cost and reliability than the grid, so affordable and reliable supply must originate at or near the customer © 2001 Rocky Mountain Institute, www.rmi.org Meanwhile, unnoticed... Central power plants, at least in the United States, stopped getting… – More efficient in the 1960s – Cheaper in the 1970s – Bigger in the 1980s – Bought in the 1990s Similar trends are now emerging in most of the world. © 2001 Rocky Mountain Institute, www.rmi.org Scale surprises: on the margin, distribu- ted resources are taking over the market • The disappointing cost, heat rate, risk, and reliability of large thermal stations were leading their orders to collapse… • …even before the “potential difference” between nuclear and combined-cycle costs stimulated restructuring that began to delaminate utilities… • …creating new market entrants, un- bundled prices, and increasing oppor- tunities for competition at all scales… • and launching the scale revolution © 2001 Rocky Mountain Institute, www.rmi.org Big units’ costs disappointed Capital-cost eco- nomies of unit (using Handy-Whitman scale steam plant cost deflator, so cost disappeared, then increases could come only from increased reversed; they intensity of input factors) were probably illusory anyhow above at most a few hundred MW Even the thermal efficiency of U.S. steam plants satu- rated around 1960 —supercritical units hit the wall Hirsh 1989 Hirsh © 2001 Rocky Mountain Institute, www.rmi.org Big steam units aged ungracefully Fossil-fueled steam units: median Equivalent Availability Factor vs. age, by size range, 1982–93 95 1 MW 90 100 MW 200 MW 85 300 MW 600 MW 1,000 MW EAF (%) 80 75 70 0 5 10 15 20 25 30 unit ageage (years) (years) RMI analysis by André Lehmann,Unit usingage (years) Markovian smoothing of 29 July 1994 NERC raw data on all 1,347– 1,527 U.S. steam units in the years shown; raw data kindly provided by Resource Insight, Inc. © 2001 Rocky Mountain Institute, www.rmi.org A 5-year rolling average reveals that U.S. fossil- fueled steam unit orders have been fading since the 1970s; their ordering rate, all 1/5 the former size, is now back to Victorian levels Maximum and average sizes of new generating units (fossil-fueled steam, all utilities, 5-year rolling average) by year of entry into service 1,400 200 1,200 1,000 150 800 100 600 400 50 200 0 0 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 Maximum new size Average new size Number of new units © 2001 Rocky Mountain Institute, www.rmi.org At first glance, it appears that the most recently ordered steam units have only retreated from the largest size range... 70% Previous trends toward ever-larger units reverse in currently planned units, with a marked step back from the most gigantic 60% ones. Is that all? 50% 40% 30% 20% 10% 0% Planne 1,000 d 1996- 1986- 2005 1995 1976- 10,000 1985 1966- 1975 1956- 100,000 1965 1946- 1,000,000 1955 1936- unit summer capacity (kWe); 1945 logarithmic scale; each label refers t the top -of-range of thesmallest of the three capacity categories Capacity distribution by date in-service (all U.S. utility-owned steam units) © 2001 Rocky Mountain Institute, www.rmi.org But make a few front bars transparent, and look what’s coming up in the garden ...new steam-unit size is shrinking 10 The striped columns show an emerging 70% The 1.01–2.15-GWe class new intermediate-size-class category crashes; the 0.46–1.0-GWe class below 1.0 GWe, of which the largest capacity share is in 46–100-MWe units; even the previously robust 216–460- 60% MWe class's share is declining. Next stop the 1940s' size distribution? 50% 40% 30% 20% 10% 0% Planned 1,000 1996- 1986- 2005 1995 1976- 10,000 1985 1966- 1975 1956- 100,000 1965 1946- 1,000,000 1955 1936- unit summer capacity (kWe); 1945 logarithmic scale; each label refers t the top -of-range of thesmallest of the three capacity categories Capacity distribution by date in-service (all U.S. utility-owned steam units) © 2001 Rocky Mountain Institute, www.rmi.org Since 1983, nonutility generation has come back, now making 27% of U.S. electricity The fall and rise of nonutility generation 100% 80% 60% 40% 20% 0% 1920 1925 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 Nonutility Investor-owned utilities Government and cooperatives To many, though, it’s invisible: many California authorities stated in summer 2000 that the state had added no capacity in the 1990s, but the actual additions, 4.5 GW, exceeded total nuclear capacity—it was just distributed and nonutility! © 2001 Rocky Mountain Institute, www.rmi.org What’s the right size for the job? Most customers want kW, not GW Average electricity consumption per U.S. household Three-fourths of U.S. 60 households have 50 75% of the households2.4 don't need more than 1.52.4 average loads not 40 average kW of power 30 exceeding 2.4 kW 20 2.4 av. kW (EIA statistical 1.5 av. kW 10 sample, 7/93) 0 0 20 40 60 80 100 120 millions of U.S. households at consumption level Average electricity consumption Three-fourths of U.S. per U.S. commercial customer 10000000 74% of the commercial custom- commercial units don't 100000 need more than 10 ers have average average kW of power 1000 loads not exceeding 10 av. kW 10 10 kW (EIA statistical 0.1 sample, 1992, loga- 0.001 0 1000 2000 3000 4000 rithmic vertical axis) thousands of U.S. commercial customers at consumption level © 2001 Rocky Mountain Institute, www.rmi.org Codifying distributed benefits • Four kinds: financial economics, electrical engineering, miscellaneous, externalities • Many pioneered by utilities, mainly in ’90s • As commercial value was discovered and demonstrated while competition loomed, most public-benefit research was halted; most interesting data became proprietary • While respecting confidences, RMI has sought to compile enough data to form the understanding required for public benefit © 2001 Rocky Mountain Institute, www.rmi.org Where does the order-of-magnitude typical value increase come from? • Financial-economics benefits: often nearing ~10 renewables, ~3–5 others • Electrical-engineering benefits: normal- ly ~2–3, far more if the distribution grid is congested or if premium power relia- bility/quality is required • Miscellaneous benefits: often around 2 , more with thermal integration • Externalities: indeterminate but may be important; not quantified here © 2001 Rocky Mountain Institute, www.rmi.org 101: Minimizing regret (financial ecs.) • Short lead times & small modules cut risk – Financial, forecasting, & obsolescence risks – Overshoot /“lumpiness” in generation & grid Tom Hoff’s analytic Smaller, faster grid-support investments are worth more solution shows it’s 3,000 worth paying ~2.7 2,500 10 kW (upper) and 1 MW (lower) more per kW for a 10- 2,000 kW instant resource 10 MW 1,500 than for a 50-MW 2-y cost ($/kW) 1,000 50 MW distributed resource breakeven capital 500– + (with +0 or +5 MW demand/y, 25 MW spare grid capacity, 10%/y 0 discount rate, $500/kW 5-y-lead- –012345Or time grid expansion; based on lead time (years) decision or option theory approach) © 2001 Rocky Mountain Institute, www.rmi.org Financial-Economics Benefits (cont’d) – Benefit of modularity benefit of short lead time...especially strong when they’re correlated – Portable resources are redeployable • Benefits’ expected value rises and risk falls – Rapid learning, mass-production economies • Modularity captures falling costs, e.g. of PVs – “Load-growth insurance” of cogen/efficiency – 10 lower working capital can cut interest rate – Genuinely diversified supply portfolios • U.S. coal and gas prices are ~84% correlated • Include higher-cost, constant-price resources in portfolio for the same reason that Treasuries are included in an optimized financial portfolio © 2001 Rocky Mountain Institute, www.rmi.org Financial-economics benefits (cont’d) – Constant-price resources vs.