There are a number of relevant, notable characteristics of the 2008 Texas electricity production profile, 85% of which is managed by ERCOT:

• The utility portion of the total electricity production is only about 24% of the total, with independent suppliers providing 57% and CHP installations, 19%. This distribution suggests that ERCOT’s ability to balance wind production is more limited than what might first appear.
• Wind production is 5% of the total (less CHP), but a very large 17% of the utilities portion.
• A large proportion of gas production is provided by independent suppliers and CHP, 45% and 39% respectively, again likely limiting ERCOT’s ability to balance wind with gas.
• The ratio of utility gas to wind production is 192%, which suggests that this is tight if dedicated to wind balancing. This, plus high production from wind at night, explains the high degree of cycling of coal plants required.

Because of recycling events, arguably attributable to the presence of wind plants, the results are the same as for PSCO, that is, there is an increase in CO₂ emissions with the presence of wind. In ERCOT, the coal plants produced an additional CO₂ emissions in 2008 of about 0-566,000 tons over running stably without these events, and in 2009, an additional 772,000-1,102,000 tons.

Wind Capacity Factor

Based on the information in the Bentek report, the wind capacity factor within ERCOT in 2009 is 22.7%, which is low and likely due to curtailment of wind, as is the case in Germany, which has a similar wind penetration of about 6% and wind capacity factors below 20%. There is notable curtailment in ERCOT as reported by NREL. The DOE/EIA published information for 2008 indicates a wind capacity factor of 25%. The difference could well be year to year variations in the wind regime. A capacity factor of 23% will be used in calculator runs.

Heat Rate Penalty and CO2 Emissions Increase Factor

From DOE/EIA published information, for Texas in 2008, for utility fossil fuel plants only, at ΔF=0, this is:

ΔR = (16,200/93,400) x 41% = 7.1%

For all fossil fuel plants in the system (less CHP) this becomes:

ΔR = (16,200/265,100) x 41% = 2.5%

Based on the totals used in Figure VI-4 (2009 data) for ERCOT, there might be some suggestion of using independent suppliers to balance wind. The 2.5% value assumes all the independent suppliers are used, which is unlikely. In the absence of more information, the PSCO calculated ΔR of 3.3% will be used for the deriving the calculator input for heat rate penalty, which is the same as for PSCO at starting at 35% but adjusted down to 20-25% for the lower capacity factor as used in Figure 4 of the calculator Part V post.

Calculator Results for ERCOT

The resulting calculator CO₂ emissions increases are: coal cycling only – 0.7 million tonnes (0.77 million tons) per year.

As for PSCO, a reasonable view is that both coal and gas plants will be involved in cycling at different times. Although coal and gas production are about the same in ERCOT, because wind is strongest at night, coal is more heavily weighted in the wind balancing mix at 67% coal and 33% gas. The total ERCOT gas mix is heavily weighted to CCGT production, but for wind balancing about an equal split with OCGT is assumed. This means more production from existing OCGT or possibly some CCGT plants being run as OCGT. Frequent cycling of CCGT plants damages the HRSGs so single stage operation is needed. In summary, more OCGT production is used than would be required if wind was not present in the system. The emissions increase over normal coal/CCGT operations becomes 2.3 million tons per year. This is an aspect not addressed in the Bentek paper. Table 1 shows the comparison of the Bentek results with the calculator.

Table 1 – Comparison of Bentek Study and Calculator results for ERCOT

The calculator results directly comparable to the Bentek findings are very close to Bentek’s. It should be emphasized that this is not likely the whole story as the gas cycling impacts should also be taken into account.

Summary of Dutch and Bentek Studies

Table 2 provides an overview of the findings of this series on wind integration. In summary, the Netherlands experience is that at wind penetration of about 3% the fossil fuel and CO₂ emissions saving is reduced to zero. As wind penetration is increased, the Colorado and Texas experience shows that the savings become negative, that is, fossil fuel and CO2 emissions are increased. The integration of all the considerations for the three approaches is complex and necessarily simplified. Any additional insights are welcome.

Table 2 – Summary of the Three Approaches Analyzed in this Series

There is a notable consistency among these three approaches. Look for more studies, based on actual experience, to emerge from countries not now dependent on foreign markets for export of wind turbine products and services, confirming the inability of new renewables, especially wind, to contribute to the reduction in fossil fuel use and CO₂ emissions reduction in electricity generation. In the absence of comprehensive, objective and transparent studies that finally settle the matter, policies in support of new renewables should be severely curtailed.

The Bentek study is a significant contribution to the wind/fossil-fuel emission literature despite some notable limitations. The study analyzes the PSCO system, which dominates Colorado’s needs, and the ERCOT system in Texas, which manages 85% of that state’s electricity.

The analysis includes SO₂, NO_x and CO₂ emissions. Bentek looks at coal cycling events only in both cases, ignoring any gas cycling, while noting PSCO’s acknowledgement that wind impacts gas as well as coal.

There are reasons why coal cycling is focused upon:

• Although gas turbine plants are better suited for cycling to support wind, for both PSCO and ERCOT gas resources are insufficient to balance all the wind energy produced.
• There is a small amount of pumped storage available to PSCO, which can run for only four consecutive hours.
• Wind is strongest at night when base load coal plants predominate, and there is reduced gas generation, which may not be sufficient to safely cycle gas plants.
• As a result, reported gas cycling events at PSCO are less frequent than that for coal.

Both analyses utilize published production information. As PSCO does not reveal hourly wind production, for emissions analysis purposes, Bentek has to rely on a few coal cycling events in relation to detailed wind production provided in PSCO training manuals. This limitation is offset by the information available on a notable increase in coal cycling, which has occurred during the period of wind introduction, and which is arguably attributable to wind. As ERCOT does release wind production at 15 minute intervals, the same analysis approach is used in the Texas system to validate the Colorado results, which it does.

Criticisms that the PSCO analysis is based on two days experience only, are well answered in the Bentek report. The reality is that PSCO does not make the necessary information available, and Bentek has done well with what they had to work with. Also, the validation of results based on the ERCOT experience is important. Finally, Bentek appropriately acknowledges limitations by calling for more comprehensive studies based on detailed information.

Having established that RPS appear to add to the emissions problem, Bentek concludes that, given RPS, it will be necessary to incorporate adequate flexible fuel capacity facilities (gas plants) to ensure reduction in emissions, which is true enough. What is missed in this logic is that incorporating such new facilities without RPS will achieve even lower emissions. More on this is provided below. There are not only more emissions with RPS than without them, but also there is duplicate capacity installed (wind) at significantly higher costs, which adds notably to the costs of electricity.

PSCO Results

This section looks at the PSCO system in more detail and compares results with the Netherland’s study in Part II and my CO₂ emissions calculator.

First, there are a number of relevant, notable characteristics of the 2008 Colorado electricity production profile.

• The utility portion of the total electricity production is about 80% of the total.
• Wind penetration is 6% of the total production, including independent suppliers, which is high and in the same range as Germany, where wind curtailment is necessary.
• The ratio of gas to wind production (excluding independent suppliers) is about 150%. It is necessary to have a ratio of 200-300% for gas to operate in the wind balancing role. This, plus the nature of wind production to be highest at night, explains the high degree of cycling required by the coal plants.

Because of cycling events, arguably attributable to the presence of wind plants, the findings are that in 2008 the coal plants produced an additional 152,000 tons of CO₂ emissions over running stably without these events, and in 2009, an additional 93,000-147,000 tons.

How does this compare to what my calculator predicts? The following are the input considerations.

Wind Capacity Factor

The referenced NREL metadata file indicates a theoretical capacity factor of about 31% based on the wind profile. However other published data from the DOE/EIA shows a wind capacity factor 35% in 2008. Colorado does have a stronger wind regime than Texas with a similar relative wind penetration at about 5%. This means that curtailment should be the practice, as is the case in Germany. Surprisingly, given the capacity factor and penetration, there is not much curtailment of wind production in PSCO during 2008 as reported by the NREL.

Heat Rate Penalty and CO2 Emissions Increase Factor

One of the calculator inputs is heat rate penalty or the loss in efficiency due to the presence of wind for the fossil fuel plants used in the wind balancing role. The study of the Netherlands system by Le Pair and de Groot developed a way of calculating this (at ΔF=0) as follows:

ΔR = (E_w / E) x R

Where:

ΔR = the overall efficiency loss due to the presence of wind plants of the power station fleet

E_w = the electricity production of the wind plants

E = The total electricity production of the wind plants and the fleet of other power stations

R = The efficiency of the these power stations without wind present

From DOE/EIA published information, for Colorado in 2008, and an assumed R of 41% based on the U.S. national average, this is:

ΔR = (3,200/39,400) x 41% = 3.3%

Bentek shows a 2% increase in all plants on one day on page 42. For the following analysis however, 3.3% will be used, based generally on the strength of the Colorado wind regime. Also, on this basis, there is consistency with the ERCOT analysis in the next part of this series.

Based on the Netherlands study’s Table 3, and using a ΔR of 3.3%, means a heat rate penalty for plants in the wind mirroring role of (45.0-29.2)/45.0 = 35%. As indicated in Part II, using a different initial R value produces the same percent heat rate penalty. The calculator factor for fossil fuel and CO2 emissions increase is therefore 56% (an extension of the table in the calculator, which stops at 30%)

Calculator Results for PSCO

The resulting calculator CO₂ emissions increases for coal cycling only are 100,000 tonnes (110,000 tons) per year, which is in the same range as the Bentek results.

A reasonable view is that both coal and gas plants will be involved in cycling at different times, so the calculator was used to show this as well, although there are no comparable Bentek results. As PSCO-owned coal capacity significantly exceeds that of gas and, because wind is strongest at night, coal is more heavily weighted in the wind balancing mix at 80% coal and 20% gas. The total ERCOT gas mix is heavily weighted to OCGT on a capacity basis, and for wind balancing all the gas is assumed to be OCGT, or CCGT operating as OCGT. Frequent cycling of CCGT plants damages the HRSGs (Heat Recovery Steam Generators) so single stage operation is needed. In summary, more OCGT production is used than would be required if wind was not present in the system. The emissions increase over normal coal/CCGT operations becomes 0.44 million tons per year. Table 1 shows the comparison of the Bentek results with the calculator.

Table 1 – Comparison of Bentek Study and Calculator results for PSCO

The results are remarkably close considering that the calculator provides a general model, which is a working hypothesis of expected fossil fuel consumption and CO₂ emissions with the introduction of wind power into an electricity system. In the absence of adequate studies using finely time-grained (less than one hour) production information and fuel consumption for the applicable generation elements over sufficiently long periods of time and dealing with the fast ramp rates required, it was developed as an interim measure and framework.

If the coal/gas results look odd, it is necessary to look at the absolute numbers, which are provided in Table 2. The calculator results are in tonnes, but this has been converted to tons in the last row.

Table 2 – Absolute Levels of CO2 Emissions for Wind Mirroring Fossil Fuel Plants (Without and With Wind Present)

This shows that by introducing CCGT plants to replace the portion of coal plant production that would be used for wind balancing, but operating normally in wind’s absence, there is an immediate saving of 0.8 million tonnes of CO₂ emissions (7.1-6.3), as shown in row (1). As shown in row (3), with wind present, the CO2 emissions increase is higher in the coal/gas case largely because of the need to use OCGT (or CCGT operating as OCGT) plants. However, row (2) shows the absolute level of CO2 emissions is less than using coal solely to balance wind. One of the key findings of the Bentek study is that adding flexible generation resources, such as that provided by natural gas, facilitates the goals of RPS without increasing emissions. This is true enough, but this ignores the reality that using gas without wind is a better solution, by 0.4 million tonnes per year (6.7-6.3), as shown in rows (1) and (2).

Conclusion

In summary, Table 1 shows that the Bentek study findings for PSCO are consistent with the Netherlands study, given the higher wind penetration, and in the same range as the the calculator results.

Part IV in this series will analyze the Bentek results for ERCOT in a similar manner, which validates these results, and addresses the issue about the limited information available from PSCO.

Here are links to the previous posts in this series:

Part I – Introduction

Part II – The Netherlands Study

[Editor's note: This is the second part in a four-part series on two new studies examining the negation of windpower emissions savings from fossil-fuel firming. The Netherlands study below, which is found to be consistent to Mr. Hawkins's calculator approach, indicates a total negation of emissions savings from fossil-fuel fill-in.]

Windpower has traditionally been considered a substitute for carbon-based energy and thus a strategy for reducing related emissions, including that of carbon dioxide (CO2). However, reality is more complicated. Either natural gas-fired or coal-fired power must rescue wind from its intermittency problem, a role that creates incremental fuel usage and emissions compared to a situation where the conventional capacity could operate on a steadier basis.

Previous studies have highlighted this unsettling tradeoff for proponents of windpower. And a new study by C. le Pair and K. de Groot based on actual experience in the Netherlands finds:

The use of wind energy for electricity generation in combination with the requirement for fossil fuel powered stations to compensate for wind fluctuations can easily lead to loss of the expected saving in fuel use and CO2 emission. In addition, the conventional stations will be subject to accelerated wear and tear.

It is recommended to get an accurate and quantitative insight into these extra effects before society sets out to apply wind energy on a large scale. All producers must be required to publish data on the efficiency effects and fuel use when wind energy is added on.

This post reviews their study and compares its results with that produced by my fossil fuel and CO₂ emissions calculator, both of which show how quickly any claimed saving from wind can become negative given the reality of fossil-fuel backup to firm-up intermittent power.

Le Pair and de Groot analyze the published information on fossil fuel consumption and produced electricity for the generation plants in the Netherlands to determine the associated decrease in efficiency of fossil fuel plants in a wind mirroring role–and hence its effect on claimed reductions on CO₂ emissions. However, their mathematical model is also generally applicable and will be used in subsequent parts of this series for actual experience with wind power in Colorado and Texas.

Technical Analysis

In the absence of specific information on the efficiency loss of individual fossil-fuel plants operating in a wind balancing role, they determine the effect in the efficiency loss in the total fossil-fuel fleet for the amount of wind generation present in the Netherlands in 2007. These calculations are possible due to the availability of published data on fuel input and electricity output for the total amounts of the various types of the power stations. The logic and associated algebra are challenging, but it is possible to reproduce their results.

Their analysis determines that the overall efficiency loss of the power station fleet due to the presence of wind plants at ΔF=0 is:

ΔR = (E_w / E) x R

Where:

ΔR = the overall efficiency loss due to the presence of wind plants of the power station fleet

E_w = the electricity production of the wind plants

E = The total electricity production of the wind plants and the power plant fleet

R = The efficiency of the these power plants without wind present

R is not known. The observed efficiencies in their Table 1 are the effect of the presence of wind plants and reported as R_i. This is solved by substituting (R_i + ΔR) for R.

The resulting efficiency loss for the Netherlands central fossil fuel fleet is 2.11% as is shown in their Table 2. Policy makers take note that this corresponds to a wind penetration in terms of electricity produced of about only 3% and this results in no fossil fuel or C0₂ emissions savings.

The underlying assumptions are that (1) there is efficiency loss due to the presence of wind, and (2) the losses since the introduction of wind in the Netherlands are attributable to wind. These are reasonable because:

1. There are sufficient indications of loss of efficiency from many studies including those provided in their paper and those listed here. Many fossil fuel and CO₂ emissions saving projected by wind proponents ignore this essential consideration.
2. The factors affecting fleet plant efficiency over time will be: deterioration with age, offset by effective maintenance and upgrades; replacement of plants with more efficient types; and parasitic loads of pollution reduction technologies. A study by the National Petroleum Council indicates that the overall trend is to improved efficiencies and a level efficiency profile for existing plants.

Translating this into the efficiency loss for the fossil fuel plants that are operating in the wind balancing role requires the determination of the electricity that must be produced by these, as all fossil-fuel plants are not being cycled to balance wind. Assuming le Pair and de Groot’s capacity factor for wind of 25%, the amount of electricity generation that is needed for wind mirroring can be calculated as 100%-25% or 75%. This is what must be produced on average over, say one year, to accommodate wind variations from 0-100% of wind capacity (which has an annual average of 25% of capacity). The efficiency loss for the fossil-fuel plants in the wind mirroring role can then be calculated by attributing the total loss to this subset. The results are shown in le Pair and de Groot’s Table 3, which is reproduced here as Table 1. In this case they have chosen to start from an assumed efficiency in normal operations of 45%.

Table 1 – Le Pair and de Groot’s Table 3 Showing Efficiency Loss of Fossil Fuel Plants

In Table 1, column one is the effect on the fossil-fuel fleet as a whole as wind production is increased from zero. Column two (R_bu) shows the resulting efficiency of the backup (wind mirroring) plants. Column three provides the equivalent values for twice the wind presence, which shows that for a wind mirroring plant efficiency loss of 34.12%, the expected efficiency reduction across the fossil-fuel fleet would be about 4%.

Le Pair and de Groot calculate that the threshold for no savings in fossil fuel consumed at the wind penetration rate for the Netherlands of 3.2% is about 2% (ΔR) for the central fleet of fossil fuel plants, or about their calculated actual value of 2.11%. The associated percentage reduction in the efficiency (heat rate penalty) of backup plants is calculated as follows from Table 1:

Backup plant efficiency is derived from the interpolated value between a ΔR of 2.00% and 2.50% for 0.11 percentage points, or (0.11/0.5) x (34.10-32.05) = 0.45

Subtracting the interpolated value for ΔR yields a backup plant efficiency of 34.10-0.45 (percentage points) = 33.65%

This means there is an efficiency loss (heat rate penalty) of (45.00-33.65)/45.00 = 25.2%. Changing the starting point of 45.0 does not affect the percentage calculation.

Comparison to Calculator Results

Table 2 shows the calculator results, setting the wind input at the Netherlands production of 0.39 GWy, their assumed 25% wind capacity factor and using the heat rate penalty of 25.2%. This calculator run assumes gas plants alone are used for wind balancing (shown with and without the need for OCGT) and Table 3 assumes that the proportion of gas and coal used for wind balancing is that of the overall installed mix.

Table 2 – Calculator Results for Wind Balancing Plants (Gas Alone) in the Netherlands

Wind proponents will typically assume the saving in fossil fuel will be the same as the wind capacity factor (in this case a wind capacity of 25% is used by le Pair and de Groot). This ignores the effects of wind on the efficiency of the fossil fuel plants in the wind mirroring role. When this efficiency loss is taken into account the calculator shows between 0.5% saving and 1.7% increase in fossil fuel consumption across the total fossil fuel fleet compared to the le Pair and de Groot level of 0%.  Note also that the CO₂ emissions are in proportion to fossil fuel consumption.

A second calculator run, now including coal plants in the wind mirroring role, was performed assuming that the fossil fuel plants in wind backup are in proportion to the overall ratio. A proxy for the combination, CO₂ emissions, is shown.

Table 3 – Calculator Results for Wind Balancing Plants (Using Gas and Coal) in the Netherlands

Conclusion

The study under review found that 100 percent of the claimed emissions savings from windpower was negated by fossil fuel backup to firm up wind’s intermittency. The calculator finds roughly similar results to that of le Pair and de Groot for the level of wind penetration in the Netherlands.

[Part III tomorrow will examine the results of the Bentek study starting with Colorado.]

To determine the actual effects will require long-term time series, at intervals significantly less than one hour, of wind production and fuel consumption due to fast ramping of fossil fuel plants to compensate for wind’s volatility in an electricity system where wind represents approximately at least 1-2% of production.

As opposed to wind proponents’ claims, studies based on actual experience with wind integration are emerging  that demonstrate the fossil fuel and CO₂ emissions gains are not valid. The two reviewed here are examples but are limited by the lack of availability of complete information on operational performance, especially of wind plants. Fortunately, enough information can be gleaned that provides a strong indication of what those who have studied this objectively have long suspected.

Why is more complete information about wind performance and integration not available? Is it because wind proponents, including some policy makers and wind industries, do not want the realities disclosed, or, in the case of many environmentalist organizations, because they would interrupt established agendas? Or is it that these groups believe it unnecessary because they do not understand the realities of utility-scale wind power?

Two New Studies: le Pair/de Groot (Netherlands) and Bentek (Colorado, Texas)

The two studies reviewed were released this year and show increases in fossil fuel or CO₂ emissions with the introduction of wind plants. The first is based on the Netherlands experience by C. le Pair and K. de Groot, and the second for Colorado and Texas by Bentek Energy. Their findings will be compared to each other, as well as to results from my fossil fuel and CO₂ emissions calculator. The analytical approaches taken by le Pair and de Groot, Bentek and the calculator are different, but the results are very similar. This is therefore a very revealing and instructive exercise.

Le Pair and de Groot take a very analytical path and apply the formulas they derived to published information on the Netherlands system, for which some actual information on fossil fuel inputs for electricity production is available. Bentek uses detailed information on increases in coal-plant cycling since the introduction of wind plants, along with the impact of wind “events” on reported emissions. Because the Public Service Company of Colorado (PSCO) does not publish hourly wind production, Bentek is restricted to a few such events, from which they draw general conclusions for Colorado.

To validate the Colorado findings, Bentek uses the same analysis approach for Texas with information from the Electricity Reliability Council of Texas (ERCOT), which reports wind production at 15 minute intervals. This not only provides validation of the PSCO analysis, but also conveniently adds experience from a third jurisdiction. The calculator is a general model of the interaction between an amount of wind generation in an electricity system and the fossil fuel plants (coal and gas) involved in balancing wind’s volatility.

Summary of Results

This is the first in a four part series that analyzes and compares the findings of these studies with each other and to the calcualtor. Briefly, the results are:

The Netherlands

Le Pair and de Groot show that when the entire fossil fuel fleet efficiency is reduced by about 2% due to the presence of wind, the fossil fuel consumption saving is zero. This is the calculated efficiency reduction in the fossil fuel fleet for the Netherlands for a wind penetration of about 3% based on the published fossil fuel input and electricity production information. Their conclusions include the following:

The use of wind energy for electricity generation in combination with the requirement for fossil fuel powered stations to compensate for wind fluctuations can easily lead to loss of the expected saving in fuel use and CO2 emission. In addition, the conventional stations will be subject to accelerated wear and tear.

It is recommended to get an accurate and quantitative insight into these extra effects before society sets out to apply wind energy on a large scale. All producers must be required to publish data on the efficiency effects and fuel use when wind energy is added on.

Colorado and Texas

The study by Bentek Energy, aptly named “How Less Became More: Wind, Power and Unintended Consequences in the Colorado Energy Market,” is a ground-breaking analysis of the effects of the introduction of wind power into electricity systems. The study is based on actual results for the PSCO system in Colorado and ERCOT in Texas and their overarching conclusion is that there are unintended consequences to the implementation of Renewable Portfolio Standards (RPS). One of the key findings is:

Contrary to their stated goals, implementation of RPS in Colorado and Texas appear to be adding to the air pollution problem, especially in areas where older plants are cycled more frequently.

Calculator

The fossil fuel and CO2 emissions calculator was applied to each of the jurisdictions studied and shows similar results. In each case an explanation of the calculator input parameters is provided.

Comparison of Results

The congruence of results from these three different approaches is a convincing confirmation of the questionable value of new alternative energy sources, especially wind, in an electricity system. RPS programs, and similar initiatives to encourage new renewables, should be withheld until such time as objective and comprehensive evaluations can be made in a completely transparent manner about the real benefits.

Part II will provide more details on the Netherlands study and Parts III and IV for the Bentek study on Colorado and Texas respectively.

The ASA has also taken on the claims of sustainability seen so often nowadays. In August 2008 World Wildlife Fund UK challenged two claims in a Shell ad: [1] By exploiting Canadian oil sands with its new technology, the company was helping to provide a sustainable future; and [2] Expanding the capacity of its Port Arthur, Texas, refinery was “helping sustainable energy production.” Shell correctly noted a consensus that, even if investment in renewables continued its upward trend, fossil energy would dominate the market and grow in absolute terms for some time to come, then somehow concluded that its investments would somehow get us closer to a sustainable future. The ASA rejected the ad on grounds that both projects increased the size of Shell’s carbon footprint, noting that the company provided no evidence that its carbon or other emissions would reach sustainable levels (however defined) in the foreseeable future. I have nothing against Shell producing hydrocarbons, but I would welcome a prohibition on specious claims of sustainability.

As far as I know, no one in the U.S. has ever complained about false statements of fact by renewables advocates or claims of sustainability by anyone. But imagine the future of the Pickens Plan or sustainability in a more transparent world.

Guest blogger Robert Michaels is a professor of economics at California State University, Fullerton. http://business.fullerton.edu/Economics/rmichaels/030131%20stars/index.html