Archive for June, 2017

Estimating Canadian electricity CO₂ intensities

Sunday, June 18th, 2017

I recently became interested in the Electricity Map project. It uses real-time electricity generation data to estimate real-time CO₂-equivalent emissions and intensity per kilowatt-hour — essentially, how green a region’s electricity generation is.

For instance, Germany routinely varies from over 450 g CO₂eq/kWh (grams CO₂-equivalent per kilowatt-hour) to under 250 g CO₂eq/kWh on windy or sunny days, while Poland varies from over 750 to 600 g/kWh. Other jurisdictions, like France or Ontario, have large baseline low-emission generators (often nuclear and hydro) and might vary from 20 to 50 g/kWh. The idea behind Electricity Map and the related CO₂ Signal API is that energy-storage consumer-level devices like batteries, heaters, or coolers can use electricity when it’s greener, or in case of an electric vehicle crossing a regional border, where it’s greener.

For this we need real-time information, for some definition of real-time. Electricity Map can show changes for every 15 minutes, but hourly updates are also common for some jurisdictions. Daily updates are too coarse. Generally, the availability of real-time data is correlated with privatization or decentralization of electricity systems: when different companies operate power stations, the transmission grid, and consumer billing (or some mix of these), real-time information on supply and demand is normally needed to determine purchasing price and in turn generation mix.

The site currently includes data for a few Canadian provinces: Alberta, Nova Scotia, Ontario, Prince Edward Island, and partial data for New Brunswick. Alberta and Ontario have privatized markets, and Prince Edward Island is showcasing how much wind generation is currently taking place (remainder of PEI’s electricity is imported from New Brunswick). New Brunswick provides interchange data (how much electricity it’s importing and exporting) and their demand — possibly driven by their relatively central location, passing on cheap plentiful hydroelectricity from Québec to Nova Scotia, PEI, and the U.S. I want to give credit to Nova Scotia: despite not being privatized nor particularly green, they report their generation mix hourly (in an attempt to highlight their renewables — but they report their coal faithfully too).

Spurring this particular write-up is Prince Edward Island. They report on-island generation and load, and imports can be inferred from this. However, the imports are from New Brunswick, which doesn’t have real-time information, so Electricity Map doesn’t know their generation CO₂ intensity. In these cases, Electricity Map by default assumes the import is the same intensity as the in-province generation.

This assumption doesn’t hold for PEI: local generation is almost always all wind, which has a much lower CO₂ intensity than the electricity imported from New Brunswick. As a result, the value shown in Electricity Map is often too optimistic and too low.

We don’t know New Brunswick’s real-time generation mix — but we can estimate it based on historical data, to at least get within an order of magnitude and hopefully within a margin of 2.

Statistics Canada has the data. The most interesting source is CANSIM Table 127-0002 (linked from CANSIM Energy consumption and disposition). Use “Add/remove data” to control it:

  1. select the desired province or territory in Step 1;
  2. deselect the subcategories “electric utilities” and “industries” in Step 2 since that’s not useful for us;
  3. select all types of electricity generation in Step 3. (The types in Statistics Canada don’t line up with Electricity Map’s fuel divisions – for instance, StatCan distinguishes “Conventional steam turbine”, “Internal combustion turbine”, and “Combustion turbine”, but won’t tell you if the turbines are heated by coal or gas – but we can estimate this later.)
  4. in step 4, select a date range – Table 127-0002 has monthly data from 2008 until 2015, which while not perfect (2016 data would be nice), is not too bad.

The second useful source is CANSIM Table 127-0008, which gives local supply and use vs imports and exports. Unfortunately, this only provides yearly data, but can be used to get a general sense of how electricity systems in the province are used. In this table, “interprovincial deliveries” are exports from a province, and “interprovincial receipts” are imports to the province.

I have put together a Jupyter notebook showing how to obtain and process the data — the numbers below mostly come from there and straight from the StatCan tables.

Because of a chain of imports within Atlantic and Eastern Canada, a brief overview of a few provincial electricity systems might be helpful.

Newfoundland and Labrador

Newfoundland and Labrador (population 530 thousand, GDP around $30 billion) largely runs on hydroelectricity. There is one particularly large hydroelectric project in Labrador, Churchill Falls, the electricity from which is exported to Québec. Per Table 127-0008, about 70-75% of all generation in the province is exported. Québec is Newfoundland and Labrador’s only current export link; an undersea link to Nova Scotia is under construction and should finish in late 2017 or early 2018.

Per Table 127-0002, in 2014-2015, between 94.1% and 97.6% of NL generation came from hydro. By monthly averages, the ratio was higher in the summer and lower in the winter. Between 0.2% and 0.3% of NL generation came from wind. The remaining generation was turbine generation, which, according to Wikipedia’s list of generating stations, consists of a vast majority of fuel oil/diesel and a tiny bit of biomass.

The monthly CO₂ intensity for electricity generated in Newfoundland and Labrador as a whole is around 30 to 70 g/kWh (higher in winter). The electricity exported to Québec is all hydroelectricity (assigned 24 g/kWh on Electricity Map). I haven’t yet calculated the intensity of the local supply excluding the Québec export.

Québec

Québec (population 8.4 million, GDP around $380 billion) mostly runs on hydroelectricity. It imports around 18% of its supply, mostly from Labrador (Labrador’s exports are 15% of Québec’s supply). It exports around 13% of its supply (16% of its generation), 10% of it to the U.S. and 3.3% to other provinces. Its import-export balance ends up fairly neutral, and it essentially acts as a conduit from Labrador to the U.S. (Newfoundlanders and Labradorians aren’t too happy about the economic arrangement.)

Between January 2014 and December 2015, Québec’s generation has been between 98.8% and 99.3% hydroelectricity. Fossil generation varied between 0.5% and 0.7% (for offgrid, peakers, and back-ups), and wind generation varied between 0.2% and 0.6%. The only nuclear plant in Québec (Gentilly) shut down in December 2012.

Estimated CO₂ intensity of Québec’s generation is around 25-30 g/kWh. Imports from Labrador, at 24 g/kWh, keep the supply intensity around the same value; the remaining imports, at 3% of the supply, likely come mostly from the other big Canadian province, Ontario, which has CO₂ intensities below 100 g/kWh and thus will not change the Québec intensity significantly.

New Brunswick

New Brunswick (population 760 thousand, GDP around $33 billion), the subject of the post, has a diverse generation mix. Since restarting their nuclear power plant (Point Lepreau) in late 2013, they have had around a third-each split in generation from nuclear, fossil fuel (coal, gas, and oil), and hydroelectricity; however, this varied a lot month-to-month. The CO₂ intensity of generation has bounced around a lot depending on the mix, but stayed around 300 to 400 g CO₂eq/kWh most of the time.

Between 2011 and 2015, imports constituted between 25% and 40% of the supply. Most of the imports come from Québec, at 25-30 g/kWh, thus reducing the CO₂ intensity of the supply by around a third. Over several years, about 33% of supply is exported — around 10% to other provinces and 23% to the U.S.

I would then suggest, in absence of better data, to assume that Prince Edward Island imports electricity which is around 300 g CO₂eq/kWh.

Prince Edward Island

Prince Edward Island (population 150 thousand, GDP around $6 billion), as mentioned, mostly imports electricity from New Brunswick. Local fossil plants (oil and diesel) serve as back-up and sometimes winter load peakers. There has been an increasing amount of wind turbines, which sometimes — but so far not often — cover the island’s complete load.

The Statistics Canada data for PEI is not terribly accurate. There is a large discrepancy between “Total all types of electricity generation” from Table 127-0002 and “Total generation of electricity” from Table 127-0008, present in StatCan’s source table and visible in the Jupyter notebook charts. Perhaps the system is too small to have accurate data.

Sources and programming

The source data is from Statistics Canada. The programming is in a Jupyter notebook on Github Gist. Further analysis or improvements could start from the notebook.

I hope to write further posts about the other provinces and territories.

When a phone is not a phone

Monday, June 5th, 2017

A brief taxonomy of mobile computing devices.

I have been writing a post about my Nexus 5 phone and came across a theory: the Nexus 5 is not, in fact, a phone.

I suggest that modern mobile computers that are between smartwatches and tablets in size can be roughly split into two categories:

  1. “Phone” – use mainly for text and voice, single-handed, will be dropped, will be used on the go
  2. “Mobile device” – two-handed, used in safe locations, seated or at least securely standing

Size impacts how you use a device. It is difficult to use a device bigger than early smartphones one-handed. The situation isn’t helped by slippery surfaces like glass or metal on both sides of many new phones. If you regularly attempt to pull a large smartphone out of a pocket while walking or cycling, you’ll drop it eventually.

And while phones were designed to be dropped with minimum damage – compact shape, non-structural outer body, rounded plastic corners that take in most of the crash energy, even battery covers that pop off – modern devices might as well be designed to take maximum damage when dropped, with rigid materials throughout and functional edge-to-edge glass on a large front face.

Fragile smartphones that don’t take being dropped well have been a problem for almost a decade now and there’s little to indicate that the situation is getting better. Workarounds include protective or grippy cases, but I would much rather just have a phone that doesn’t need a case in the first place. I understand their value for specialized needs or carrying methods – for couriers or sport – but I just want to send short text messages and check next bus time a couple of times a day.

Here is a small selection of phones and mobile devices released over the past two decades:

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