Spending part of her early years in Nigeria, RBC’s Nneka Bowen experienced the effects of air pollution, clean water scarcity, and power outages. She knew she wanted a better world for her future children and her children’s children.
Returning home to Canada, Bowen studied business in Halifax and Ottawa. Showing skills in leadership and change management, she quickly rose through the banking world, becoming RBC’s Managing Director in Calgary Commercial Financial Services for Energy Services, Public Sector, and Business Services by 2018.
Her role involves working directly with Alberta’s energy industry. And it’s been in that role that Bowen learned about the Energy.AI initiative — where innovative solutions to climate change issues are developed by Energy Futures Lab using a technological approach.
When RBC announced their support of Energy.AI through the RBC Tech for Nature program last year, Bowen saw a chance to use her skills and apply them to environmental issues. In 2019 she became a member of the Energy Futures Lab fellowship program, made up of over 60 of Alberta’s innovators and influencers from industry, government, non-profit organizations, First Nations, academia and community interest groups, providing expertise in energy sector insights and funding advocacy.
Here is a look at two prototypes the EFL has been working on with support from RBC and people like Bowen: how they work, and how their success could help all of Canada move towards a greener future.
Increasing Oil and Gas Facility Energy Efficiency
For the first time, Energy.AI is testing the potential of applying a machine learning model to predict the energy use of an existing Cenovus oil and gas facility. This is an exciting initiative, says Bowen.
Machine learning is a kind of artificial intelligence where computers are taught to identify patterns and make predictions based on large amounts of data. Based on the information that comes back, Cenovus can take opportunity to maximize the energy efficiency of the facility. Improved energy efficiency means reduced greenhouse gas emissions — and that’s an important part of tackling climate change.
To address carbon emissions on a greater level, the same machine learning model could be applied in the future for other oil and gas facilities in Alberta, and beyond.
Making Credits for Reducing Emissions More Accessible
Alberta is one of the sunniest provinces in the country, giving it considerable solar energy-producing potential. One issue Energy.AI is addressing is how to help smaller solar power producers (or “micro-solar”) in Alberta receive carbon credits for reducing their emissions.
According to Energy.AI’s team, blockchain technology might be used to verify the solar production across rural Albertan communities in a cheaper, less manual way. Aggregating smaller producers this way could potentially support a co-op model, making emissions reductions credits more accessible to small producers.
A pilot with small-scale solar producers has already been completed. The test’s success could light the way for a future Alberta with a more adaptable, interconnected, and accessible energy system. For consumers, it could mean a future where rural communities securely participate in clean power generation — and where they get to reap the economic benefits of lower energy costs.
Both of these Energy.AI initiatives are focused on finding ways for new technologies (like machine learning) to provide solutions to complex environmental issues. With continued explorations into new technologies and ideas, Canadian innovators like Nneka Bowen and other Energy Futures Lab fellows could help other nations in accelerating our collective transition to a future of sustainable and more affordable energy.
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