“Imagine you’ll be launching a new digital service that helps someone understand how their daily choices have an impact on their environment. The service would make it easy for someone to log their information every day to help them gradually make more informed and sensible choices for their health and the environment’s. It is also important that the user can assess their progress in a way that helps them understand their impact, and improve it moving forward.”

The Problem

With rising concerns in energy usage across Canada, how can the government take action to reduce energy usage effectively?

Hypothesis

Canada can reduce it’s environmental impact by targeting the most wasteful provinces and launching digital services that effectively reduce their energy usage without reducing quality of life.

Design Process

Discover

Secondary Research
IESO, Statistics Canada, Ottawa Insights

Analyzing a data set made available by Statistics Canada on energy usage per province and populations gave important insight into energy demand between provinces.

By taking a look at energy consumption by province we can start to gain insight into energy usage across the country.

Energy Per Province (CANADA)

Ontario's energy consumption is the highest of any other province.

Ontario has the highest energy consumption, but also has the highest population. To get a more accurate picture of energy consumption, we can normalize by energy consumption per household and graph that against population.

Population vs Energy Per Household (CANADA)

Population does not appear to have a significant effect on energy consumption. Maybe population density will tell a more interesting story.

Population vs Energy Per Household (CANADA)

Population density does not appear to have a significant effect on energy consumption either.

So population doesn’t tell the whole story about energy usage across Canada, but the graphs do give us key insights.

  • Quebec has the second highest population and the lowest energy consumption per household

  • The prairies had the highest energy usage per household

Define

Synthesis
Insights, clustering

Focusing the research on the outliers (namely: the prairies and Quebec), we might be able to understand why energy usage habits differ across Canada.

The Cost of Electricity

(Based on Hydro costs data from Manitoba Hydro)

Can the cost of energy affect consumption?

Alberta is Canada’s energy production province. Maybe energy is very cheap and as a result, the residents are not incentivized to use less energy as much as other provinces.

Cost of electricity per province (CANADA)

Quebec has the cheapest hydro when compared to all the provinces. While, the prairies (Alberta, Saskatchewan, and Manitoba) varied.

Maybe electricity usage and cost have a correlation.

Cost of electricity per province (CANADA)

The graph suggests that cheaper electricity does not necessarily mean consumers will use more electricity.

What else could be incentivizing citizens to use less electricity in Quebec? Alternatively, why are prairie residents using so much more electricity?

Residential Income

How can income affect energy consumption?

We can compare the average weekly earnings, including overtime, against the energy consumption per household.

Energy Usage VS Weekly Earnings per province (CANADA)

Albertans make the most money on average and spend more money on and use more energy per household than other provinces.

The Quebecois are the fourth lowest income earners and use the least amount of energy per household when compared to other provinces.

Climate

(Based on data from Canadian Weather Forecasts)

Looking at the climate differences, we may be able to find that energy consumption varies because residents in the prairies are spending more energy heating their homes when compared to the rest of Canada.

Energy Usage VS Weekly Earnings per province (CANADA)

Comparing two cities, Montreal, Quebec and Edmonton, Alberta, we can see that the normal climate does not vary greatly throughout the year. As a result, there does not appear to be a significant relationship between normal temperature and energy consumption for the entire year.

Looking at the three hottest months in the year, June, July and August, we can see if the cost of air conditioning relates to energy consumption.

Energy Usage VS Temperature (Summer) per province (CANADA)

Based on the data, it appears that most Canadian provinces have relatively similar summer weather.

But Canadian winters are much harsher than their summers. We can focus a climate analysis on the three core months of winter: December, January and February.

Energy Usage VS Temperature (Winter) per province (CANADA)

The prairies are the coldest provinces and also consume the most energy.

The data suggests that the prairies consumes more energy to heat up their homes.

We can validate that the reason for high energy consumption per household in the prairies is due to home heating by looking at heating factors, including:

  • The type of energy used

  • The size of homes

Natural Gas Usage Across Canada

(Based on data from Statistics Canada)

High usage of natural gas heating is a strong indicator of energy used for heating (but high electricity use is not an indication of heating).

Several provinces were omitted from the results because of insufficient or unreliable data.

Natural Gas Percentage per province (CANADA)

Alberta has the highest percentage of energy usage in natural gas, followed by Saskatchewan. Mentioned previously, natural gas usage is a strong indicator of home and water heating.

Home Sizes Across Canada

(Based on data from point2homes)

As houses get bigger, more energy is needed to heat the house.

Point2homes News, an online source for real estate market trends and news, did an analysis on 3-months’ worth of home buying search behavior on Point2 Homes Canada.

The preference for bigger homes is more evident in Alberta and Saskatchewan, where more than 80% of searchers were interested in homes with 3, 4 or more bedrooms

As supported in the report, home buyers in the prairies are more interested in larger homes.

Develop

Ideation
Brainstorm, Impact x Feasibility Matrix

With this knowledge, we can start to ideate ways to reduce energy consumption in the prairies.

Residents in the prairies are spending the most energy heating their homes; to reduce energy consumption we can investigate ways to heat homes more efficiently.

Some existing solutions on the market include:

  • MyHeat: a home heat loss visualizer, available to select cities (including Calgary)

  • Smart Thermostats: preprogrammed timing of heating periods

  • Home maintenance, including insulating, and sealing

The problem can be broken down further to facilitate idea generation:

  • Efficient Heating: How can we increase the internal temperature of homes more efficiently

  • Heat Preservation: How can we improve heat preservation

  • Smarter Heating: How can we heat homes smarter

Some new ideas were generated and diagrammed in a Brainstorm.

Brainstorm

To evaluate the ideas, an impact-feasibility matrix was used to effectively compare ideas.

Brainstorm

Based on the impact-feasibility matrix, the Isolated “Zone” Home Heating will be pursued.

Deliver

Implementation
Wireframes, use-cases, scenario diagrams

The Isolated “Zone” Home Heating, hereafter called The Smart Heater, will heat certain zones in the house and act as a visualizer for their Smart Heater.

The Smart Heater will select which rooms to heat based on several factors, including:

  • Date (Day, Month, Year)

  • Geographic Location

  • Historic data

E.g. In January, on a Monday morning at 8:00AM, the bathroom and common area will be heated to 20 (celsius) because the residents spend the majority of their time in the morning getting ready in the bathroom, and leave after an hour.

The Smart Heater will also provide energy usage analysis to provide the user with visibility on energy consumption.

Smart Heater - Energy Saver Mode
Smart Heater - Midday Use
Smart Heater - Stats
Smart Heater - Midday Use

The above, a rough outline of what the applications alpha might look like, contains a house layout with real-time heat and draft data provided by a paired real-time embedded device that would be placed in the house.