…Lazard Wind and Solar Costs, Part 1…
The media consistently cites Lazard to claim that wind and solar cost less than electricity from natural gas combined cycle (NGCC), coal-fired and nuclear power plants.
In 2017, my article published a review of Lazard’s methodology, using the limited information they provided.
This review established that Lazard’s methodology was compromised and that the levelized cost of electricity from wind and solar were not lower than the LCOEs from fossil fuel and nuclear power plants.
Lazard has never refuted my review, so I can only assume my review correctly reflects Lazard’s procedure.
This article will republish the information published in 2017. A few additional comment are contained in the conclusion.
Lazard held financial costs, such as the cost of debt and equity, constant when making calculations for each type of facility. This was an effort to ensure that calculations between facility types were fair. However, there were at least two instances where this assumption was misleading.
- Natural gas combined cycle (NGCC) plants were assumed to have a life of twenty years, which is half the life that should have been used. Financial costs should have been amortized over 40, not 20 years.
- The investment cost for a coal-fired power plant was assumed to be $3,000 per KW. This is higher than actual historical costs for supercritical plants ($2,100/KW) and slightly higher than for ultra-supercritical plants ($2,800/KW). This imposed a financial penalty for coal-fired power plants.
There were two important assumptions in the Lazard study that were either questionable or that slanted conclusions unfairly to the benefit of wind and solar. These are addressed in (1) and (2). A third factor was omitted from the study and is addressed in (3).
- Capacity Factor
Capacity factor (CF) is defined as the amount of electricity produced over a year by an installation, compared with the amount that could theoretically be produced based on the facility’s nameplate rating.
The Lazard study refers to “resource availability”, and it is unclear whether the CFs used in the study are true CFs or ersatz CFs based on some undefined resource availability calculation.
Because this is unclear, both possibilities are addressed for wind.
Alt 1: Traditionally Defined CFs
The capacity factor (CF) for wind used in the Lazard study was significantly higher than experience from existing installations. The study used 55% in one instance and 38% in another.
Actual CFs, as reported by DOE in its 2015 Wind Technology Report, averaged 32.8%, between 2011 and 2015; 31.8% between 2006 and 2010; and 30.3% between 2000 and 2005.
New, taller units with longer blades will probably have higher CFs, but not anywhere near 55%. (Probably closer to 40%, based on installations since 2017.)
Wind installations in high wind areas, such as Montana where CFs could be higher, require long and expensive transmission lines, the costs of which are not included in the Lazard or many other studies.
The use of higher CFs and lower capital costs in the Lazard study, skewed the LCOEs for wind, making them unreasonably low.
Alt 2: Ersatz CFs
The Lazard study may have used a specially designed “capacity factor as a proxy for resource availability”.
Why this would be done is unclear since actual wind resources have been carefully mapped across the United States for heights of 30 meters, 80 meters and 100 meters above ground level.
The best winds for generating electricity are predominantly in the upper plains states such as Montana, and across the front range of the Rocky Mountains.
The regional factors used in the Lazard study do not appear to align with the wind maps available from NREL, though these regional factors were apparently used to represent wind availability across the country.
The Lazard study did not explain how these ersatz capacity factors were determined, so there is no way to determine their appropriateness or accuracy.
For this reason, the LCOEs developed by Lazard using ersatz CFs for wind are suspect, and not comparable to traditionally determined LCOEs.
The Lazard study seems to have used a specially designed “capacity factor as a proxy for resource availability” when determining LCOEs for solar.
Presumably “resource availability” refers, in some manner, to insolation levels.
“Resource availability” was apparently used to establish, what can best be described as ersatz capacity factors for solar installations.
Insolation levels are readily available for all areas of the world, so it begs the question of why Lazard chose to create a “resource availability” factor for solar.
Insolation levels for the Southwestern United States are substantially greater than those for the Midwestern United States, yet the LCOEs arrived at for solar by the Lazard study did not reflect these substantial differences.
For this reason, the solar LCOEs developed by Lazard are suspect, and not comparable to traditionally determined LCOEs.
Again, The Lazard study did not explain how these ersatz capacity factors were determined, so there is no way to determine their appropriateness or accuracy.
The report did confirm that rooftop PV solar is uncompetitive. As demonstrated in Nothing to Fear, PV rooftop solar is uneconomic in every state except possibly Hawaii.
Both wind and solar are intermittent, and in some respects unreliable.
Beyond small amounts, it’s impossible to replace coal and natural gas power plants with wind and solar on a one for one basis. As mentioned earlier, these are not interchangeable LEGO pieces.
The CAISO Duck curve demonstrates this very clearly.
For example, wind and solar must also include expensive storage if the evening ramp-up is to be minimized. Coal and natural gas power plants must be retained to provide power at night and for when the sun stops shining or the wind stops blowing.
These limitations become increasingly worse as greater amounts of wind and solar are placed on the grid.
At the very least, LCOEs for wind and solar are misleading because wind and solar require the use of costly storage. More about the CAISO Duck curve is found in the book Nothing to Fear.
Part 2 provides conclusions and some new information.
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