Harrison article revisited

On October 3, 2011, we published a reference to  John Harrison's analysis of wind farm economics.  In his article, Professor Harrison attempts to dissuade further wind farm investment in Ontario because he believes that the financial returns are poor and getting worse. 


We therefore posed the question, "Why are sophisticated organizations with long histories of renewable energy development in other jurisdictions continuing to invest in Ontario?".

We promised some follow-up analysis and this is the third and final instalment.  In instalment two, we looked at Dr. Harrison's technique of correcting historical capacity factors for annual wind speed variation.  We demonstrated that his fundamental assumption that wind turbine output varies with the cube of wind velocity wasn't true and therefore its use as a normalizing function is flawed.  We concluded that his normalizing factors could be off by 5 to 10%.

What Dr. Harrison was attempting to do was to remove the year-to-year variations in wind speed and just look at the operational performance of the wind farms.  Just like a high tide can lift all boats, high annual wind speeds can mask poor performance.  The performance factor that he was seeking is called availability.  It's the measure of the potential for a wind farm to generate electrical power.  100% is perfection.  It's analogous to whether your car will start in the morning, blow a tire, run out of gas, be in the garage for repairs, etc.

Since Dr. Harrison didn't have availability data from Ontario wind farms, he attempted to "back in" to the number by taking published capacity factors (i.e. the ratio of actual power produced, divided by the theoretical power produced by a wind farm if it ran 24/7 at full capacity) and normalizing those factors for year-to-year wind variations.

As we proved in the previous instalment, Dr. Harrison made two false assumptions:

1. All wind farms in Ontario experience the same wind in a particular year (he naively chose Toronto as the surrogate for all wind farms in Ontario)

2. Wind farm output varies with the cube of wind speed (it actually varies closer to the square of wind speed)

Based on those false assumptions, Dr Harrison reached the following conclusion:

Typically, the individual Ontario WEGS [Wind Energy Generating System] start within the first year or two at a capacity factor of about 30% (Kingsbridge, on the shore of Lake Huron, is an exception) which then declines. This decline is about 2% per year. This of course augurs very badly for a generating system designed for a 20 year life and with capital funding based upon a 20 year life. 

Rather than trying to correct Dr. Harrison's line of logic with localized wind speed data and actual wind turbine power curves, we went directly to availability data within the wind industry.  Each of the six wind farms mentioned in Dr. Harrison's analysis are unlikely to reveal their individual availability data publicly.  Their ability to maintain a fleet of turbines at top availability is proprietary.

However, we found something even better.  Garrard Hassan is the globally pre-eminent consultant in wind farm design and operational improvement.  As part of their service offerings, they accumulate data from a large number of clients and publish the findings without identifying individuals.  They recently published a report  on the availability of over 100 wind farms in North America.  The key graphic is shown below.

The graphic might be confusing (hint: just follow the purple bouncing ball - it's the average), but the takeaway is that availability suffers in the first year or two as wind farms work through what is called, in the reliability arena, "infant mortality".  That's when installation errors (typically loose wires or inadequate lubrication) are exposed.  However, those errors and weak components are weeded out fairly quickly without a safety issue and the wind farm settles into a very consistent level of availability. 

So, what does this mean for Ontario wind farms?  It means that Ontario wind farms run a close line to a fair return on capital and that power consumers in Ontario can expect them to be viable power producers for many years into the future.

Harrison article revisited - Harrison's cube isn't real

On September 13, 2011, we published a reference to John Harrison's analysis of wind farm economics.  In his article, Professor Harrison attempts to dissuade further wind farm investment in Ontario because the financial returns are poor and getting worse. We therefore posed the question, "Why are sophisticated organizations with long histories of renewable energy development in other jurisdictions continuing to invest in Ontario?".

We promised some follow-up analysis and this is the first instalment.  We'll start with Dr. Harrison's technique of correcting historical capacity factors for annual wind speed variation.  We'll demonstrate that his fundamental assumption that wind turbine output varies with the cube of wind velocity isn't true and therefore its use as a normalizing function is flawed.  If you're not interested in the technical details, scroll to the bottom of this post where we conclude that his normalizing factors could be off by 5 to 10%.

The normalizing technique is also used by wind industry professionals to evaluate a wind farm's long term expectation of annual wind speeds.  This is quite an elaborate analytic exercise using data from meteorological towers placed in the wind farm area.  The data is then compared to a number of long term (typically, ten years) wind series maintained by Environment Canada.  Those sites with the highest correlation to the field site are used to normalize the field measurements.

Dr. Harrison has chosen to use Toronto as the reference site for all wind farms in Ontario.  He then combines that data somehow with five other cities to come up with a normalizing factor that he applies to all wind farms in Ontario.  In other words, he assumes that year to year variations at each and every wind farm in Ontario are predominately determined by some averaging of wind over most of the province.  This is similar to saying that the variations in every city's rainfall or temperatures could be accurately predicted by the province's average variations.  If it was rainy in North Bay one year then it must have been rainy in Toronto, as well.  We're not meteorologists, but that doesn't seem intuitively correct.

Secondly, Dr. Harrison assumes that the cube law can be used to predict capacity factors from average wind speed.  He is quite right in stating that the power in the wind goes up by the cube of wind velocity.  However, the power from the turbine does not.  There are many technical reasons why this is so but the performance of a turbine versus wind speed is depicted by a power curve that is specific to each turbine design.  Further, the wind speed variation over the course of a year tends to follow a Weibull distribution that is unique to each wind farm.  He further assumes that  the distribution of wind power in all of Ontario is representative of that seen by each individual turbine and, therefore, that the output of each turbine seldom exceeds 85%.  He is not privy to the operating characteristics of each wind farm (e.g. array losses versus wind direction, availability of turbines, the reset time required when a turbine exceeds rated output, etc.) but most individual turbines frequently operate above 85% of their nameplate capacity.

To put all this into perspective, I approached Tom Lambert, P.Eng.,  owner of Mistaya Engineering, the makers of Windographer.  Windographer has been used by many wind consulting firms for many years with demonstrated accuracy.  He plotted the Windographer model results against a cubic function, forcing the two lines to meet at 5 m/s.  Obviously, the cubic function overstates the amount of energy (a surrogate for capacity factor) dramatically.   Keep in mind that the Windographer model has been verified many times in real situations.

The implications of all this of is that Dr. Harrison's normalizing factor dramatically penalizes all wind farms in 2010-2011.  His normalizing factor could easily be off by 5 to 10%.

Dr. Harrison's well intended analysis is laced with some flawed premises and therefore errs in his concluding message "wind in Ontario doesn't make financial sense".

For our next instalment, we'll look at wind farm availability.

WCO publishes that wind profits are negligible

John Harrison, a retired Queens University physics professor has just published an analysis showing that wind turbine developers in Ontario are just scraping by.   

This finding is in stark contrast to claims made by Wind Concerns Ontario's (WCO) John Laforet that "[Those who push industrial wind .... are mere puppets for someone's profit...]".   Ironically, Harrison is a Director of Research, Association to Protect Amherst Island - an organization that is closely associated with WCO.

The paper, that can be accessed here, poses the argument that:

• the optimistic predictions of the wind energy developers are unlikely to be met or sustained

• there are significant risk factors associated with wind energy in Ontario

• despite the above-market prices offered by the Ontatio Government under the RESOP and FIT programs and despite the 20-year length of the contract, investors are unlikely to see the long-term return on investment that they might expect for a development with such risk factors.

Obviously, Dr. Harrison is trying to scare wind power investors away from Ontario.  However, what we are seeing in Ontario is continued investment by sophisticated organizations with long histories of renewable energy development in many jurisdictions.  So, who is right and who is wrong?

Future postings on this blog will explore Dr. Harrison's paper with an eye to answering that question.