NewEnergyNews: TODAY’S STUDY: ALL NEW ENERGY BY 2030 (Part 2)

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    Wednesday, January 26, 2011

    TODAY’S STUDY: ALL NEW ENERGY BY 2030 (Part 2)

    Highlights of the first part of the thoroughly researched and well-documented study highlighted below were posted yesterday. All together, the two-part study represents conclusive evidence that the only thing preventing a shift to 100% New Energy over the next 2 decades is the heart to fight for a better quality of life for the next generation.

    Not demanding a New Energy economy today condemns tomorrow to floods like the one this month that is drowning Australia, fires like the one last summer that choked and fried Russia and the growing ills of displacement, poverty, disease and misery that come with such events. If those things seem appealing, don't demand anything of the nation's leaders and the people who manage investments.


    Providing all global energy with wind, water, and solar power, Part II: Reliability, system and transmission costs, and policies
    Mark Z.Jacobson and Mark A. Delucchi, November 2010 (Stanford University via Science Direct)

    Abstract

    This is Part II of two papers evaluating the feasibility of providing all energy for all purposes (electric power, transportation, and heating/cooling), everywhere in the world, from wind, water, and the sun (WWS). In Part I, we described the prominent renewable energy plans that have been proposed and discussed the characteristics of WWS energy systems, the global demand for and availability of WWS energy, quantities and areas required for WWS infrastructure, and supplies of critical materials. Here, we discuss methods of addressing the variability of WWS energy to ensure that power supply reliably matches demand (including interconnecting geographically dispersed resources, using hydroelectricity, using demand-response management, storing electric power on site, over-sizing peak generation capacity and producing hydrogen with the excess, storing electric power in vehicle batteries, and forecasting weather to project energy supplies), the economics ofWWSgeneration and transmission, the economics of WWS use in transportation, and policy measures needed to enhance the viability of a WWS system. We find that the cost of energy in a 100%WWSwill be similar to the cost today. We conclude that barriers to a 100% conversion to WWS power worldwide are primarily social and political, not technological or even economic.

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    Variability and reliability in a 100%WWSenergy system in all regions of the world

    One of the major concerns with the use of energy supplies, such as wind, solar, and wave power, which produce variable output is whether such supplies can provide reliable sources of electric power second-by-second, daily, seasonally, and yearly. A new WWS energy infrastructure must be able to provide energy on demand at least as reliably as does the current infrastructure (e.g., De Carolis and Keith, 2005). In general, any electricity system must be able to respond to changes in demand over seconds, minutes, hours, seasons, and years, and must be able to accommodate unanticipated changes in the availability of generation. With the current system, electricity-system operators use ‘‘automatic generation control’’ (AGC) (or frequency regulation) to respond to variation on the order of seconds to a few minutes; spinning reserves to respond to variation on the order of minutes to an hour; and peak-power generation to respond to hourly variation (De Carolis and Keith, 2005; Kempton and Tomic, 2005a; Electric Power Research Institute, 1997). AGC and spinning reserves have very low cost, typically less than 10% of the total cost of electricity (Kempton and Tomic, 2005a), and are likely to remain this inexpensive even with large amounts of wind power (EnerNex, 2010; DeCesaro et al., 2009), but peak-power generation can be very expensive.

    The main challenge for the current electricity system is that electric power demand varies during the day and during the year, while most supply (coal, nuclear, and geothermal) is constant during the day, which means that there is a difference to be made up by peak- and gap-filling resources such as natural gas and hydropower. Another challenge to the current system is that extreme events and unplanned maintenance can shut down plants unexpectedly. For example, unplanned maintenance can shut down coal plants, extreme heat waves can cause cooling water to warm sufficiently to shut down nuclear plants, supply disruptions can curtail the availability of natural gas, and droughts can reduce the availability of hydroelectricity.

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    A WWS electricity system offers new challenges but also new opportunities with respect to reliably meeting energy demands. On the positive side, WWS technologies generally suffer less downtime than do current electric power technologies. For example, the average coal plant in the US from 2000 to 2004 was down 6.5% of the year for unscheduled maintenance and 6.0% of the year for scheduled maintenance (North American Electric Reliability Corporation, 2009a), but modern wind turbines have a down time of only 0–2% over land and 0–5% over the ocean (Dong Energy et al., 2006, p. 133). Similarly, commercial solar projects are expected to have downtimes of !1% on average, although some have experienced zero downtime during a year and some have experienced downtimes of up to 10% (Banke, 2010). Moreover, there is an important difference between outages of centralized power plants (coal, nuclear, and natural gas) and outages of distributed plants (wind, solar, and wave): when individual solar panels or wind turbines are down, only a small fraction of electrical production is affected, whereas when a centralized plant is down, a large fraction of the grid is affected. And when more than one large, centralized plant is offline at the same time, due to a common problem, the entire national grid can be affected. For example, the Nuclear Power Daily reported that on November 2, 2009, one-third of France’s nuclear power plants were shut down ‘‘due to a maintenance and refueling backlog,’’ and that as a consequence France’s power distribution firm stated ‘‘that it could be forced to import energy from neighboring markets for two months from mid-November’’ (Nuclear Power Daily, 2009)…

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    …there are at least seven ways to design and operate a WWS energy system so that it will reliably satisfy demand and not have a large amount of capacity that is rarely used: (A) interconnect geographically dispersed naturally variable energy sources (e.g., wind, solar, wave, and tidal), (B) use a nonvariable energy source, such as hydroelectric power, to fill temporary gaps between demand and wind or solar generation, (C) use ‘‘smart’’ demand-response management to shift flexible loads to better match the availability of WWS power, (D) store electric power, at the site of generation, for later use, (E) over-size WWS peak generation capacity to minimize the times when available WWS power is less than demand and to provide spare power to produce hydrogen for flexible transportation and heat uses, (F) store electric power in electric-vehicle batteries, and (G) forecast the weather to plan for energy supply needs better. (See Holttinen et al. (2005), for a related list, and Denholm et al. (2010), for a similar discussion.)…

    The cost of WWS electricity generation and ‘‘supergrid’’ transmission and decentralized V2G storage

    An important criterion in the evaluation of WWS systems is the full cost of delivered power, including annualized total capital and land costs, operating and maintenance costs, storage costs, and transmission costs, per unit of energy delivered with overall reliability comparable with that of current systems. In this section, we present estimates of the cost of WWS generation and of the likely additional cost of ensuring that WWS generation reliably matches demand by the use of V2G storage and a ‘‘supergrid’’ that interconnects dispersed generators and load centers.

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    Cost of generation and conventional transmission

    Table 1 presents estimates of current (2005–2010) and future (2020 and beyond) $/kWh costs of power generation and conventional (i.e., not extra-long-distance) transmission for WWS systems, with average US delivered electricity prices based on conventional (mostly fossil) generation (excluding electricity distribution) shown for comparison. For fossil-fuel generation, the social cost, which includes the value of air pollution and climate change damage costs, is also shown. The estimates of Table 1 indicate that onshore wind, hydroelectric, and geothermal systems already can cost less than typical fossil and nuclear generation, and that in the future onshore wind power is expected to cost less than any other form of large-scale power generation.3 If alternatives are compared on the basis of social cost, all WWS options, including solar PVs, are projected to cost less than conventional fossil-fuel generation in 2030.

    The cost ranges shown in Table 1 are based partly on our own cost estimates, detailed in Tables A.1c and A.1d of Appendix A.1. Appendix A.1 presents two sets of calculations: one with the reference-case parameter values used by the by the Energy Information Administration (EIA) in its Annual Energy Outlook (our Tables A.1a and A.1b), and one with what we think are more realistic values for some key parameters (Tables A.1c and A.1d). The estimates based on the EIA reference-case are higher than the estimates shown in Table 1 because of the relatively high discount rate, relatively short amortization period, and (in some cases) relatively high capital costs used by the EIA. However, when we use what we believe are more realistic values for the discount rate and the amortization period, and also use the EIA’s lower ‘‘falling cost’’ case estimates of $/kW capital costs, the resultant estimates of the total $/kWh generating costs for wind, geothermal, hydro, and solar thermal are lower, and comparable with the other estimates in Table 1. This exercise gives us confidence in the estimates of Table 1…

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    Cost of extra-long-distance transmission

    The estimates of Table 1 include the cost of electricity transmission in a conventionally configured system, over distances common today. However, as discussed in Section 1, the more that dispersed wind and solar generating sites are interconnected, the less the variability in output of the whole interconnected system. A system of interconnections between widely dispersed generators and load centers has been called a ‘‘supergrid.’’ The configuration and length of transmission lines in a supergrid will depend on the balance between the cost of adding more transmission lines and the benefit of reducing system output variability as a result of connecting more dispersed generation sites. As mentioned above, no such cost optimization study has been performed for the type of WWS system we propose, and as a result, the optimal transmission length in a supergrid is unknown. It is almost certain, however, that the average transmission distances from generators to load centers in a supergrid will be longer – and perhaps much longer – than the average transmission distance in the current system. The cost of this extra transmission distance is an additional cost (compared with the cost of the current conventional system) of ensuring that WWS generation reliably matches demand.

    Appendix A.2 presents our calculation of the additional $/kWh cost of extra-long-distance transmission on land with high-voltage direct-current (HVDC) lines. The $/kWh cost is a function of the cost of the towers and lines per unit of wind capacity and per km of transmission, the cost of equipment such as converters, transformers, filters, and switchgear, the distance of transmission, the capacity factor for the wind farm, electricity losses in lines and equipment, the life of the transmission line, maintenance costs, and the discount rate. Table A.2a presents our low-cost, mid-cost, and high-cost assumptions for these parameters. The most important and uncertain cost component is the cost of lines and towers per km and per MW. In Appendix A.2 we discuss several estimates of this cost.The unit cost of lines and towers isuncertain because it depends on factors that vary from project to project: the capacity of the wind farm, the capacity of the transmission line relative to the capacity of the wind farm, system design, right-of-way acquisition costs, construction costs, and other factors. Construction costs and right-of-way acquisition costs are especially variable because they are related to highly variable site-specific characteristics of the land, such as slope, accessibility, and the potential for alternative uses…

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    V2G decentralized storage

    As discussed in Section 1, the use of EV batteries to store electrical energy, known as ‘‘vehicle-to-grid,’’ or V2G, is an especially promising method for matching WWS generation with demand. V2G systems have three kinds of costs: they might accelerate the battery’s loss of capacity, they require extra electronics for managing V2G operations, and they lose energy during charge/discharge cycling. In Appendix A.3, we estimate all three costs of a V2G scheme, and draw three conclusions:

    (1) If Li-ion batteries have a cycle life 45000 and a calendar life about equal to the life of a vehicle, then V2G cycling will not change battery replacement frequency and will have a battery replacement cost of zero and a total cost of only $0.01–$0.02 per kWh diverted to V2G. (We think that this case, or something close to it, is the most likely.)

    (2) Otherwise, if the calendar life is very long (30 years), but if V2G cycling can be managed so as to cause minimal degradation of battery capacity, then the total cost of V2G cycling will be in the range of 0.03/kWhto$0.11/kWh,depending on the type of vehicle and the value of the other variables considered in Appendix A.3.

    (3) Otherwise, if the calendar life is long and V2G cycling causes the same degradation of capacity as does charging and discharging during driving, then the cost of V2G cycling will be in the range of $0.05–$0.26/kWh. (This case is unlikely, because there is evidence that V2G cycling does not cause the same battery degradation as does driving.)

    Note that these cost estimates are per kWh diverted to V2G. To get an estimate of the cost per kWh of all WWS generation, we multiply the cost per kWh diverted by the ratio of kWhs diverted to total kWhs of WWS generation. This ratio will depend on the design and operation of an optimized system, which are not yet known, but we speculate that the ratio is not likely to exceed 25%. If so, then the cost of V2G storage is likely to be on the order of $0.01/kWh-generated or less.

    We conclude that in an intelligently designed and operated WWS system, the system-wide average additional cost (relative to the cost of a conventional system) of using a supergrid and V2G storage (along with demand management, hydropower, and weather forecasting) to ensure that WWS generation reliably satisfies demand is not likely to exceed $0.02/kWh-generated. Even with this additional cost, future wind power is likely to have a lower private cost than future conventional fossil generation, and all WWS alternatives are likely to have a lower social cost than fossil-fuel generation (Table 1)…

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    Policy issues and needs

    Current energy markets, institutions, and policies have been developed to support the production and use of fossil fuels. Because fossil-fuel energy systems have different production, transmission, and end-use costs and characteristics than do WWS energy systems, new policies are needed to ensure that WWS systems develop as quickly and broadly as is socially desirable. Schmalensee (2009) lists four kinds of economic policies that have been adopted in the US and abroad to stimulate production of renewable energy: feed-in tariffs, output subsidies, investment subsidies, and output quotas (sometimes called ‘‘renewables portfolio standards’’—see e.g., Wiser et al., 2010). Dusonchet and Telaretti (2010) analyze the economics of policies that support the development of photovoltaic energy in Europe. Most studies find that feed-in tariffs (FITs), which are subsidies to cover the difference between generation cost (ideally including grid connection costs (Swider et al., 2008)) and wholesale electricity prices, are especially effective at stimulating generation from renewable fuels (Fthenakis et al., 2009; Sovacool and Watts, 2009; Couture and Cory, 2009;Wei and Kammen, 2010). A recent survey of venture capitalists investing in renewable energy technologies found that the investors ranked FITs as the most effective policy for stimulating the market for renewable energy (B¨urer and W¨ustenhagen, 2009). To encourage innovation and economies of scale that can lower costs, FITs should be reduced gradually (Couture and Cory, 2009 call this an ‘‘annual tariff degression’’). An example of this is a ‘‘declining clock auction,’’ in which the right to sell power to the grid goes to the bidders willing to do it at the lowest price, providing continuing incentive for developers and generators to lower costs (New York State Energy Research and Development Authority, 2004). A risk of any auction, however, is that the developerwillunderbid and be leftunable to profitably develop the proposed project (Macauley, 2008; KEMA, 2006; Wiser et al., 2005). Regardless of the actual mechanism, the goal of ‘‘tariff degression’’ is that as the cost of producing power from WWS technologies (particularly photovoltaics) declines, FITs can be reduced and eventually phased out.

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    Other economic policies include eliminating subsidies for fossil fuel energy systems (for estimates of subsidies, see Koplow, 2004, 2009; Koplow and Dernbach, 2001; The Environmental Law Institute, 2009; The Global Studies Initiative, 2010; and http://subsidyscope.org/energy/) or taxing fossil-fuel production and use to reflect its environmental damages, for example with ‘‘carbon’’ taxes that represent the expected cost of climate change due to CO2 emissions (for estimates of environmental damages, see National Research Council (2010) (Table 2 here) and Krewitt, 2002). However, it appears that eliminating fossil-fuel subsidies and charging environmental-damage taxes would compensate for the extra cost of the currently most expensive WWS systems only if climate change damage was valued at the upper end of the range of estimates in the literature. For example. The Environmental Law Institute (2009) estimates that US government subsidies to fossil fuel energy amount to about $10 billion per year, which is less than 5% of the roughly $300 billion value of fossil-fuel production (EIA, 2010d)). Regarding environmental damages, the US National Research Council (2010) estimates that the external costs of air pollution and climate change from coal and natural-gas electricity generation in the US total $0.03–$0.11/kWh for 2005 emissions, and $0.03–$0.15/kWh for 2030 emissions (using the mean air pollution damages and the low and high climate change damages from Table 2). Only the upper end of the 2005 range, which is driven by assumed high climate-change damages, can begin to compensate for the more than $0.10/kWh higher current private cost of solar PVs and tidal power (Table 1). Assuming that it is politically infeasible to add to fossil-fuel generation carbon taxes that would more than double the price of electricity, eliminating subsidies and charging environmental damage taxes cannot by themselves make the currently most expensive WWS options economical.

    Two important non-economic programs that will help in the development of WWS are reducing demand, and planning and managing the development of the appropriate energy-system infrastructure (Sovacool and Watts, 2009). Reducing demand by improving the efficiency of end use or substituting low-energy activities and technologies for high-energy ones, directly reduces the pressure on energy supply, which means less need for higher cost, less environmentally suitable resources.

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    Because a massive deployment of WWS technologies requires an upgraded and expanded transmission grid and the smart integration of the grid with BEVs and HFCVs as decentralized electricity storage and generation components, governments need to carefully fund, plan and manage the long-term, large scale restructuring of the electricity transmission and distribution system. In muchof the world, international cooperation in planning and building ‘‘supergrids’’ that span across multiple countries, is needed. Some supergrids will span large countries alone. A supergrid has been proposed to link Europe and North Africa (e.g., Czisch, 2006;www.desertec.org), and ten northern European countries are beginning to plan a North Sea supergrid for offshore wind power (Macilwain, 2010; www.offshoregrid.eu). Supergrids are needed for Australia/Tasmania (e.g., Beyond Zero Emissions, 2010); North America, South America, Africa, Russia (The Union for the Co-ordination of Transmission of Electricity (2008) has studied the feasibility of a supergrid linking Russia, the Baltic States, and all of Europe), China, Southeastern and Eastern Asia, and the Middle East. Thus, a high priority for national and international governing bodies will be to cooperate and help to organize extra-long distance transmission and interconnections, particularly across international boundaries.

    Another policy issue is how to encourage end users to adopt WWS systems or end-use technologies (e.g., residential solar panels, and electric vehicles) different from conventional (fossil fuel) systems. Municipal financing for residential energy-efficiency retrofits or solar installations can help end users overcome the financial barrier of the high upfront cost of these systems (Fuller et al., 2009). Purchase incentives and rebates and public support of infrastructure development can help stimulate the market for electric vehicles (A° hman, 2006). Recent comprehensive analyses have indicated that government support of a large-scale transition to hydrogen fuel-cell vehicles is likely to cost just a few tens of billions of dollars—a tiny fraction of the total cost of transportation (National Research Council, 2008; Greene et al., 2007, 2008).

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    Finally, we note that a successful rapid transition to a WWS world may require more than targeted economic policies: it may require a broad-based action on a number of fronts to overcome what Sovacool (2009) refers to as the ‘‘socio-technical impediments to renewable energy:’’

    Extensive interviews of public utility commissioners, utility managers, system operators, manufacturers, researchers, business owners, and ordinary consumers reveal that it is these socio-technical barriers that often explain why wind, solar, biomass, geothermal, and hydroelectric power sources are not embraced. Utility operators reject renewable resources because they are trained to think only in terms of big, conventional power plants. Consumers practically ignore renewable power systems because they are not given accurate price signals about electricity consumption. Intentional market distortions (such as subsidies), and unintentional market distortions (such as split incentives) prevent consumers from becoming fully invested in their electricity choices. As a result, newer and cleaner technologies that may offer social and environmental benefits but are not consistent with the dominant paradigm of the electricity industry continue to face comparative rejection (p. 4500).

    Changing this ‘‘dominant paradigm’’ may require concerted social and political efforts beyond the traditional sorts of economic incentives outlined here…

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