Renewable Energy Technologies Just as Reliable as Fossil Fuel Plants
24 Jan, 2008 01:15 pm
The "intermittency" of wind and solar is not a reason to reject renewables
While it is certainly true that the output from conventional power plants can be measured quite accurately, virtually every other aspect of planning for and implementing that resource is riddled with uncertainty. Three types of uncertainty are most common: variance in construction costs, variance in short-term demand forecasts, and variance in long-term demand forecasts.
First, a large variance exists between the projected costs and actual costs of conventional power plant construction. Experience has shown that there can be project delays and other unforeseen problems that can lead to considerable cost overruns and even project cancellations. Generally, the larger the project (in terms of installed capacity and thus cost), the longer it takes to complete and the more it is at risk to unforeseen changes (such as interest rates, labor costs, environmental regulations, etc.). The very fact that large power plants take many years to construct and complete dates are imprecise, adds uncertainty to the electric system.
Second, once large projects get built, their output is often subject to rapidly changing patterns in consumer demand (and thus required load). Weather events such as sudden thunderstorms can persuade customers to switch on lights, just as unexpected hours of sunshine can convince them to turn them off. Millions of people are constantly switching on and off equipment—televisions, lights, computers—that demand instant power.
In the modern, restructured electricity market, system operators typically employ complicated forecasting techniques to minimize such uncertainty. New York, New England, and PJM independent system operators determine load imbalance on five-minute intervals and use supply curves to dispatch the load-following units participating in the real-time market. System operators employ an automatic generation control (AGC) system to manage minute-to-minute load imbalances (a service known as “regulation”). Units participating in the AGC are equipped with governors that sense a change in frequency and automatically adjust output. Intra-hour dispatch every few minutes allows the units providing regulation to return to their nominal set points. To enhance system reliability, AGC units operate at lower power output than would be dictated by optimal economic dispatch without the requirement to following changing loads. Thus the entire electric utility system is already built to address variability, just of a different type.
Third, utility resource acquisition decisions are based on forecasts of future customer demand, which can be ridiculously uncertain. We have a hard enough time predicting the weather or political elections; imagine the difficulty in projecting how an entire industry will be 10 to 20 years down the road. Changes in industry structure and long-term climatic conditions such as drought or unpredicted heat can particularly impact large hydroelectric and nuclear facilities. Uncertainty in long-term forecasting was widely encountered in the utility industry in the 1970s and 1980s, when excessively high forecasts of growth in demand for electricity led to overbuilding of electric generating plants and massive electric system cost over-runs in many states. A somewhat infamous example of this was in Washington State, where the Washington Public Power System (WPPS) began a construction program for as many as seven new nuclear power plants in the early 1970s.
After large cost overruns and collapsing electricity demand growth in the late 1970s and early 1980s, the power system faced financial disaster and all but one of those plants was cancelled, leading to, at the time, the country’s largest municipal bond default. The entire experience came to be called the “WHOOPS” fiasco (as a play off of the WPPS acronym) and experts have called it “an enduring illustration of the risk associated with large electric system supply-side investments.”
Renewable energy technologies such as wind and solar minimize each of these sources of variability by deploying technologies that are smaller, more modular, and less capital intense. Classic grid systems are typically “lumpy systems” in the sense that additions to capacity are made in primarily large lumps (gargantuan power plants, new transmission lines). These plants have long lead times and uncertainties, making planning and construction difficult, especially when the balance of supply and demand can change rapidly within a short period of time.
In contrast, renewable energy technologies tend to have a quicker lead time than conventional coal and nuclear plants that can take 5 to 15 years to plan, permit, and construct. Quicker lead times enable a more accurate response to load growth, and minimize the financial risk associated with borrowing hundreds of millions of dollars while plants are built. Florida Power and Light says it can take as little as 3-6 months from groundbreaking to commercial operation of new wind farms.
Because renewable energy technologies can be produced at smaller scale, they can be located (or situated) almost anywhere, enhancing their ability to match smaller increments of demand. In the case of unexpected changes, renewable energy technologies limit financial risk and capital exposure. Modular plants can be cancelled easier, so that stopping a project is not a complete loss (and the portability of most renewable energy systems means value can still be recovered if the technologies would need to be resold as commodities in a secondary market). Smaller units with shorter lead times reduce the risk of purchasing a technology that becomes obsolete before it is installed, and quick installations can better exploit rapid learning, as many generations of product development can be compressed into the time it would take to build one giant plant.
Conventional power plants operating on coal, natural gas, and uranium are subject to an immense amount of variability. The issue, therefore, is not one of variability or intermittency per se, but how such variability and intermittency can best be managed, predicted, and mitigated. And the advantages of renewables—in addition to being theorized for the past three decades—have been empirically proven in large parts of the world in the past few years.
Christopher Cooper and Benjamin Sovacool, Renewing America: The Case for a National Renewable Portfolio Standard (New York: Network for New Energy Choices, 2007), ix + 158pp, available at http://www.newenergychoices.org/dev/uploads/RPS%20Report_Cooper_Sovacool_FINAL_HILL.pdf.
Ed Vine, Marty Kushler, and Dan York, “Energy Myth Ten—Energy Efficiency Measures are Unreliable, Unpredictable, and Unenforceable,” In B.K. Sovacool and M.A. Brown (Eds.) Energy and American Society—Thirteen Myths (New York: Springer, 2007), pp. 265-288.