This week Business in Vancouver (BiV) printed an article about the Site C project titled: B.C. might not need any additional wind power either which included a number of quotations from Dr. Harry Swain a gent with whom I have disagreed on the topic of Site C. In the article Dr. Swain stated that BC has all the power-generating capacity it needs for the next 20 years and therefore does not need Site C. He indicated that the basis of his claim was his modelling on the topic. This led me to wonder what was in that model and how the opponents of the Site C dam were able to generate numbers that ran completely contrary to both my findings and those of BC Hydro. This blog post examines that question and demonstrates, once again, the importance of looking at the underlying data used in environmental decision-making. By the time you finish reading this blog post I think you will agree with me that the modelling used by the opponents of Site C is flawed and not worthy of consideration in the Site C debate.
To begin I had to get the model described in the article. As many of you know Dr. Swain et al. presented a forecast model to the BCUC (link downloads an Excel model from BCUC website). I downloaded that model a while back and discovered that the critical inputs were not included in the spreadsheet but rather referred back to a secondary spreadsheet called 2016-2036-Forecast-w-Revised-Trade-BCUC-RB-Eoin-Finn-Oct18.xlsx. At that point I was stymied, since I didn’t think that Dr. Swain or his colleagues would give me a copy of their model. However, when the BiV article came out I asked the article’s author if he had been given any information to support Dr. Swain’s claims. The response was a copy of Dr. Swain’s updated model titled BC-Hydro pro-forma 2017-37Rev5SiteC.xls. Moreover, much to my surprise I was informed that Dr. Swain had agreed to the release of the file to me. This represents a level of professional courtesy that was much appreciated and hopefully represents a step towards working together to meet BC’s continued energy challenges.
Now as a first note, I will point out that the 2017-37 Model differs in output from the 2016-36 model used in the BCUC submission. As I do not have the earlier model I cannot see the difference between the two but I can point out what I view as limitations with the 2017-2037 model (called the Model hereafter) and explanations for why I believe it does not present a reasonable estimation of future demand in BC.
In the BiV article Dr. Swain stated:
With the modelling that I did, I assumed – as BC Hydro did – that the population is going to increase, that GDP will increase
While that is strictly true (the Model has a correction for inflation) it does not tell the whole story. According to BC Statistics British Columbia’s population is expected to rise from 4.8 million in 2017 to 5.9 million in 2037. This represents an increase of 23% over the time covered by the Model. The problem is that the Model does not address that population growth directly. Rather than looking at per capita demand it simply assumes that demand will grow or decline using the average of historic residential demand growth between 2006 and 2016. The choice of dates is very significant since it includes the market crash from 2008-2009 which caused a retraction in our economy and associated energy use. The inclusion of the recession in the input number for the spreadsheet results in lower growth in residential demand for the entire time frame covered by the Model.
Moreover, looking at the residential sector demand estimates I identified a number of further critical flaws. The time period under consideration (2006-2016) was one where BC Hydro carried out intense demand-side management activities which temporarily de-coupled residential energy growth from population growth. To further lower the future residential demand the Model includes an elasticity factor (addressed later) which is sufficiently high to essentially eliminate demand increases associated with population growth over the last 10 years of modelling (2027-2037). According to projections the population of BC is supposed to grow by 550,000 souls between 2027-2037 but under the Model residential energy use will stagnate during that period. In total, the Model projects residential demand to increase by 7% over the entire 20 years of the Model. Not 7% per year but 7% over the period from 2017 to 2037 even as the population increases by 23% during that time.
On the commercial demand side the model has similar flaws. As I noted in my previous blog post on electricity demand commercial demand in BC pretty much mirrors GDP growth. The Model has commercial demand increasing by only 3% between 2017 and 2037. In a province with a 23% growth in population the service and commercial parts of our economy are only going to grow at 3%? This is simply not a reasonable assumption.
On the industrial side it gets even worse. I don’t look forward to living in the British Columbia the Model projects for 2037 as we will have no industrial base to pay taxes to fund our services. The Model has industrial use dropping by 66% over the 20 year period. It projects total industrial demand at 4,431 GWh in 2037. According to BC Hydro statistics mining alone used 3,800 GWh in 2017. The forestry sector used around 6,800 GWh with pulp and paper using about 4,400 GWh of that forestry number. Think of it, under the Model in 2037 BC will use the same amount of power in its entire industrial base that it currently uses for pulp and paper. Is this a reasonable number? If I told you that BC’s mining industry would be completely gone by 2037 and its forestry sector would be cut by more than half would you believe me? Funny thing Swain et al. said that very thing to the BCUC and no one called them on it. Looking at how BC Hydro generated its projected demand you discover that BC Hydro looked at each of its large industrial customers individually to project industrial demand in the future. I think I will trust BC Hydro on this topic.
Continuing our look at demand we have electric vehicles. On the topic of electric vehicles (EVs) the Model once again ignores population changes and assumes that the personal vehicle fleet will remain static with the same number of passenger vehicles on the road in 2037 as in 2016. This decreases the number of EVs needing electricity. The Model assumes that there will be no attempt to electrify commercial or transport trucks so there is no demand there. Moreover, the increase in EV uptake is extremely back-loaded with a net total increase in EVs of 29,310 between 2017 and 2024. [The Model uses compounding interest in their rows so the big increases on the demand end are located at the later end of the model.] This allows the Model to minimize the electricity demand in the early years while claiming larger numbers at the end of the model run (so they can claim they had those higher numbers). Interestingly, based on the numbers from FleetCarma.com by early Q3-2017 EV sales in BC had surpassed the Model’s projections for the entire year. Right now EV uptake is running at about twice the rate projected by the Model which will have a commensurate increase in electricity demand.
Looking what we have found so far, the Model presents unreasonably low demand numbers for every significant column on the demand side of the ledger. Based on this there is no wonder how they got their numbers so low. Now I could stop here but there are two other points about the Model that should be exposed. The first is the price elasticity component.
As we know, price elasticity addresses how demand goes down as price goes up. BC Hydro was criticized for using a relatively low elasticity value. BC Hydro’s research indicates that price elasticity should range between -0.08 and -0.13 (even as they used a lower number). The Model uses a residential elasticity of -0.15. This results in a larger than is typically observed reduction in demand associated with hydro rate increases.
Coincidentally, the model assumes rate increases in the Residential, Commercial and Industrial sectors of 3.8% per year every single year between 2017 and 2037 (no rate freezes here). The result in the unseemly residential power rate of $234/MWh and commercial rate at $201/MWH in 2037. Needless to say that huge number has the effect of driving down residential and commercial demand based on price elasticity. Admittedly it makes that $88/MWh Site C power look pretty good. Combining the extremely high power rates and extremely high elasticity rate results in massively suppressed demand numbers in 2037. These basic assumptions in the Model are the reason demand is so low in 2037.
Amusingly, while the Model projects incredibly expensive power for residential and commercial customers it assumes virtually no increase in the price received for electricity through sales. The Model assumes that the trade price for electricity will rise all the way to $40/MWh in 2025 and no further increases thereafter. In 2037 they have Hydro selling electricity to California at $40/KWh while simultaneously selling it to residential customers at $234/MWh. Why would the Model do such a thing? Well that way it can minimize the amount of income generated by the dam so the incongruous combination of stratospheric residential rates and negligible export rates results in a decrease in demand and a minimization of the income generated by the dam. The best of both worlds if you don’t want the dam built but absolutely unsupportable if you care about reliable data being used in decision-making.
Ultimately what this blog post shows is that the model used by Dr. Swain and his colleagues is so completely flawed that it is simply not a reasonable tool to be used in any decision-making process. What I find most confusing is why I haven’t read about this from anyone else. The assumptions for this model were all out there and yet no one went through the effort of examining them. The people pushing for the dam needs to shake their heads. So much misinformation is coming out about this project and the people supporting it simply shrug and move on. Wouldn’t it be nice if the people supporting the project put in the sweat equity that the opponents of the dam have been contributing. Then, maybe, we might have enough useful information on the table to make a good decision as to whether we complete or scrap the dam.