Electricity Generation: Wind Power is more Than Twice the Cost of Coal

                                                               Cartoon by Josh cartoonsbyjosh.com

Proponents of renewable energy often cite GenCost 2018 to argue that wind power is now less costly than coal-fired power. However, inspection of GenCost 2018 shows that not all of the costs of electricity generation are included in its estimate of the Levelised Cost of Electricity (LCOE). The LCOE presented in GenCost 2018 is effectively the “farm-gate” cost of energy, i.e., the price required by the generator to break even at its site of generation.

In a similar manner to the “farm-gate” cost of milk, the GenCost 2108 LCOE does not represent the final price to the consumer, since it fails to include the cost of transportation (transmission lines). GenCost 2018 also does not include the cost of power plant degradation and demolition, etc. These (omitted) costs are not insignificant as explained below:

  1. GenCost 2018 uses it uses very high capacity factors for wind (from 38% to 44%), whereas real-world capacity factors are in the range 33% to 38% or lower. For example, Rutovitz et al (2017) state that wind farms in Australia have an average capacity factor of 33% and GHD (2018) assumes a 38% capacity factor. Reducing the capacity factor from 44% to 33% increases the LCOE for wind by approximately 33%.
  2. GenCost 2018 does not include degradation in performance with time, which is estimated to be 1.6% per annum (Staffell & Green, 2014). Including the loss in performance increases the LCOE for wind by approximately 20%.
  3. GenCost 2018 uses a design life of 25 years but, typically, wind turbines do not last longer than 20 years (Coultate & Hornemann, 2018) and Hughes (2012) suggests a 15-year economic life for wind turbines. Reducing the design life from 25 years to 20 years increases the LCOE for wind by approximately 8%.
  4. GenCost 2018 neglects the cost of transmission lines and demolition, which are usually higher for renewables than for coal-fired power. Including the costs of transmission and demolition increases the LCOE for wind by an average of 35%.

Including all of the items listed in (1) to (4) above more than doubles the GenCost 2018 LCOE for wind power as shown in Figure 1.

These costs should be included in the GenCost 2018 LCOE calculation if an accurate comparison with other sources of power is to be made.

Figure 1:  Comparison of GenCost 2018 LCOE’s with Real-world LCOE (i.e., when the Cost of Transmission Lines, Demolition, etc., are Included), Source: McFarlane (2019)

It is evident from Figure 1(b) that:

  1. The cost of wind power (with 6 hours storage) is approximately 2½ to 3¼ times the cost of existing coal power and approximately 2 to 2½ times the cost of new coal power.
  2. The cost of standalone wind power (with no storage) is approximately 1½ to 2 times the cost of existing coal power and approximately 1¼ to 1½ times the cost of new coal power. However, no storage would incur the additional cost of back-up by fossil-fuel plants.

It should be emphasised that the real-world LCOE values for standalone wind presented in Figure 1(b) are verified by Stock et al (2016), which presents reverse auction values for wind power in ACT that are in the $73 to $92 per MWh range. This range compares well with the $79 to $95 per MWh range for the real-world values presented in Figure 1(b) above, which gives confidence in the accuracy of the real-world LCOE estimates presented in this review.

Furthermore, the conclusion from Figure 1(b) that wind power is more expensive than conventional generation is corroborated by the fact that real-world experience shows that those countries with the highest generation from renewables also have the highest electricity costs as shown in Figure 2.

Figure 2:  Cost of Residential Electricity Compared with Installed Capacity of Renewables (after MacDonald, 2018)

It is evident from Figure 2 that those countries with the highest penetration of renewable electricity (Germany and Denmark) have the highest electricity costs, which leads to the obvious conclusion that renewables are more costly than conventional generation.

In summary, it is shown that the levelised cost of electricity generated by wind power is significantly more expensive than coal-fired power (by a factor of 2 to 3).

Therefore, it is recommended that any new generation capacity in Australia should include coal-fired power, not only because it is cheaper than wind but also because it is more reliable and provides power on an as-needed basis.


Brailsford et al, 2018, Powering Progress: States Renewable Energy Race, Louis Brailsford, Andrew Stock, Greg Bourne and Petra Stock, published by Climate Council of Australia Ltd 2018


Coultate & Hornemann, 2018, Why wind-turbine gearboxes fail to hit the 20-year mark, The Renewable Energy Handbook (Wind), 2018

GenCost 2018, Graham, P.W., Hayward, J, Foster, J., Story and Havas, L., 2018, GenCost 2018 CSIRO, Australia


Hughes, 2012, The Performance of Wind Farms in the United Kingdom and Denmark, Published by the Renewable Energy Foundation


MacDonald, 2018, A Look at Impacts of Wind and Solar Electric Generation on Electricity Price, Energy Performance Measurement Institute (EPMI)

McFarlane, 2019, Levelised Cost of Electricity: A Comparison between Wind and Coal Power


Rutovitz et al, 2017, Rutovitz, J., McIntosh, B., Morris, T. and Nagrath, K. (2017) Wind Power in Australia: Quick Facts. Prepared for the Climate Media Centre and Australian Wind Alliance by the Institute for Sustainable Futures, UTS

Click to access 2017_Wind_Power_in_Australia_ISF.pdf

Staffell & Green, 2014, How does wind farm performance decline with age? Renewable Energy


Stock et al, 2016, Territory trailblazer: How the ACT became the renewable capital of Australia, published by the Climate Council of Australia Limited

Reliability of Hansen’s Climate Change Models

It would appear that Hansen’s 1988 climate models are beginning to diverge from the actual temperature observations

The latest GISS readings are shown in the diagram below:

Scenarios A, B and C Compared with Measured GISS Surface Station and Land-Ocean Temperature Data
Scenarios A, B and C Compared with Measured GISS Surface Station and Land-Ocean Temperature Data

The original diagram can be found in Fig 2 of Hansen (2006) and the latest temperature data can be obtained from GISS. The red line in the diagram denotes the Surface Station data and the black line the Land-Ocean data. My estimate for 2008 is based on the first six months of the year.

Scenarios A and C are upper and lower bounds. Scenario A is “on the high side of reality” with an exponential increase in emissions. Scenario C has “a drastic curtailment of emissions”, with no increase in emissions after 2000. Scenario B is described as “most plausible” and closest to reality.

Hansen (2006) states that the best temperature data for comparison with climate models is probably somewhere between the Surface Station data and the Land-Ocean data. A good agreement between Hansen’s premise and measured data is evident for the period from 1988 to circa 2005; especially if the 1998 El Nino is ignored and the hypothetical volcanic eruption in 1995, assumed in Scenarios B and C, were moved to 1991 when the actual Mount Pinatubo eruption occurred.

However, the post-2005 temperature trend is below the zero-emissions Scenario C and it is apparent that a drastic increase in global temperature would be required in 2009 and 2010 for there to be a return to the “Most-Plausible” Scenario B.

Will global warming resume in 2009-2010, as predicted by the CO2 forcing paradigm, or will there be a stabilsation of temperatures and/or global cooling, as predicted by the solar-cycle/cosmic-ray fraternity?

Watch this space!

P.S: It would be very interesting to run an “Actual Emissions” Scenario on the Hansen model to compare it with actual measurements. The only comments that I can glean from a literature survey is that Scenario B is closest to reality, but it would appear that CO2 measurements are above this scenario, but unexpectedly, methane emissions are significantly below. Does anyone have the source code and/or input data to enable this run?